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Merge remote-tracking branch 'upstream/develop' into refactorStringInterpolationStridedPart2
2 parents 99c815f + 647a947 commit 5013030

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lib/node_modules/@stdlib/blas/base/ndarray/README.md

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@@ -45,6 +45,7 @@ The namespace exposes the following APIs:
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<div class="namespace-toc">
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- <span class="signature">[`caxpy( arrays )`][@stdlib/blas/base/ndarray/caxpy]</span><span class="delimiter">: </span><span class="description">multiply a one-dimensional single-precision complex floating-point ndarray `x` by a constant `alpha` and add the result to a one-dimensional single-precision complex floating-point ndarray `y`.</span>
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- <span class="signature">[`dasum( arrays )`][@stdlib/blas/base/ndarray/dasum]</span><span class="delimiter">: </span><span class="description">calculate the sum of absolute values for all elements in a one-dimensional double-precision floating-point ndarray.</span>
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- <span class="signature">[`daxpy( arrays )`][@stdlib/blas/base/ndarray/daxpy]</span><span class="delimiter">: </span><span class="description">multiply a one-dimensional double-precision floating-point ndarray `x` by a constant `alpha` and add the result to a one-dimensional double-precision floating-point ndarray `y`.</span>
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- <span class="signature">[`ddot( arrays )`][@stdlib/blas/base/ndarray/ddot]</span><span class="delimiter">: </span><span class="description">calculate the dot product of two one-dimensional double-precision floating-point ndarrays.</span>
@@ -54,6 +55,7 @@ The namespace exposes the following APIs:
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- <span class="signature">[`sasum( arrays )`][@stdlib/blas/base/ndarray/sasum]</span><span class="delimiter">: </span><span class="description">calculate the sum of absolute values for all elements in a one-dimensional single-precision floating-point ndarray.</span>
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- <span class="signature">[`saxpy( arrays )`][@stdlib/blas/base/ndarray/saxpy]</span><span class="delimiter">: </span><span class="description">multiply a one-dimensional single-precision floating-point ndarray `x` by a constant `alpha` and add the result to a one-dimensional single-precision floating-point ndarray `y`.</span>
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- <span class="signature">[`sdot( arrays )`][@stdlib/blas/base/ndarray/sdot]</span><span class="delimiter">: </span><span class="description">calculate the dot product of two one-dimensional single-precision floating-point ndarrays.</span>
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- <span class="signature">[`zaxpy( arrays )`][@stdlib/blas/base/ndarray/zaxpy]</span><span class="delimiter">: </span><span class="description">multiply a one-dimensional double-precision complex floating-point ndarray `x` by a constant `alpha` and add the result to a one-dimensional double-precision complex floating-point ndarray `y`.</span>
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</div>
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@@ -96,6 +98,8 @@ console.log( objectKeys( ns ) );
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<!-- <toc-links> -->
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[@stdlib/blas/base/ndarray/caxpy]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/base/ndarray/caxpy
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[@stdlib/blas/base/ndarray/dasum]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/base/ndarray/dasum
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[@stdlib/blas/base/ndarray/daxpy]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/base/ndarray/daxpy
@@ -114,6 +118,8 @@ console.log( objectKeys( ns ) );
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[@stdlib/blas/base/ndarray/sdot]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/base/ndarray/sdot
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[@stdlib/blas/base/ndarray/zaxpy]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/base/ndarray/zaxpy
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<!-- </toc-links> -->
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</section>

lib/node_modules/@stdlib/blas/base/ndarray/docs/types/index.d.ts

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/* eslint-disable max-lines */
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import caxpy = require( '@stdlib/blas/base/ndarray/caxpy' );
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import dasum = require( '@stdlib/blas/base/ndarray/dasum' );
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import daxpy = require( '@stdlib/blas/base/ndarray/daxpy' );
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import ddot = require( '@stdlib/blas/base/ndarray/ddot' );
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import sasum = require( '@stdlib/blas/base/ndarray/sasum' );
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import saxpy = require( '@stdlib/blas/base/ndarray/saxpy' );
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import sdot = require( '@stdlib/blas/base/ndarray/sdot' );
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import zaxpy = require( '@stdlib/blas/base/ndarray/zaxpy' );
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/**
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* Interface describing the `ndarray` namespace.
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*/
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interface Namespace {
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/**
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* Multiplies a one-dimensional single-precision complex floating-point ndarray `x` by a constant `alpha` and adds the result to a one-dimensional single-precision complex floating-point ndarray `y`.
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*
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* @param arrays - array-like object containing an input ndarray, an output ndarray, and a zero-dimensional ndarray containing a scalar constant
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* @returns output ndarray
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*
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* @example
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* var Complex64Array = require( '@stdlib/array/complex64' );
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* var Complex64 = require( '@stdlib/complex/float32/ctor' );
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* var scalar2ndarray = require( '@stdlib/ndarray/base/from-scalar' );
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* var ndarray = require( '@stdlib/ndarray/base/ctor' );
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*
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* var xbuf = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0 ] );
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* var x = new ndarray( 'complex64', xbuf, [ 5 ], [ 1 ], 0, 'row-major' );
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*
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* var ybuf = new Complex64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );
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* var y = new ndarray( 'complex64', ybuf, [ 5 ], [ 1 ], 0, 'row-major' );
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*
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* var alpha = scalar2ndarray( new Complex64( 1.0, 2.0 ), 'complex64', 'row-major' );
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*
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* var z = ns.caxpy( [ x, y, alpha ] );
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* // returns <ndarray>[ <Complex64>[ -2.0, 5.0 ], <Complex64>[ -4.0, 11.0 ], <Complex64>[ -6.0, 17.0 ], <Complex64>[ -8.0, 23.0 ], <Complex64>[ -10.0, 29.0 ] ]
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*
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* var bool = ( z === y );
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* // returns true
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*/
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caxpy: typeof caxpy;
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/**
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* Computes the sum of absolute values for all elements in a one-dimensional double-precision floating-point ndarray.
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*
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* // returns -5.0
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*/
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sdot: typeof sdot;
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/**
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* Multiplies a one-dimensional double-precision complex floating-point ndarray `x` by a constant `alpha` and adds the result to a one-dimensional double-precision complex floating-point ndarray `y`.
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*
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* @param arrays - array-like object containing an input ndarray, an output ndarray, and a zero-dimensional ndarray containing a scalar constant
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* @returns output ndarray
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*
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* @example
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* var Complex128Array = require( '@stdlib/array/complex128' );
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* var Complex128 = require( '@stdlib/complex/float64/ctor' );
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* var scalar2ndarray = require( '@stdlib/ndarray/base/from-scalar' );
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* var ndarray = require( '@stdlib/ndarray/base/ctor' );
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*
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* var xbuf = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0 ] );
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* var x = new ndarray( 'complex128', xbuf, [ 5 ], [ 1 ], 0, 'row-major' );
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*
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* var ybuf = new Complex128Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );
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* var y = new ndarray( 'complex128', ybuf, [ 5 ], [ 1 ], 0, 'row-major' );
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*
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* var alpha = scalar2ndarray( new Complex128( 1.0, 2.0 ), 'complex128', 'row-major' );
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*
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* var z = ns.zaxpy( [ x, y, alpha ] );
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* // returns <ndarray>[ <Complex128>[ -2.0, 5.0 ], <Complex128>[ -4.0, 11.0 ], <Complex128>[ -6.0, 17.0 ], <Complex128>[ -8.0, 23.0 ], <Complex128>[ -10.0, 29.0 ] ]
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*
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* var bool = ( z === y );
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* // returns true
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*/
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zaxpy: typeof zaxpy;
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/**

lib/node_modules/@stdlib/napi/create-complex-like/README.md

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napi_value value;
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napi_status status = stdlib_napi_create_complex_like( env, 3.0, 5.0, &value );
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assert( status == napi_ok );
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if ( err != NULL ) {
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assert( napi_throw( env, err ) == napi_ok );
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return NULL;
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}
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// ...
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}

lib/node_modules/@stdlib/napi/create-complex-like/src/main.c

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* napi_value value;
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* napi_status status = stdlib_napi_create_complex_like( env, 3.0, 5.0, &value );
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* assert( status == napi_ok );
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* if ( err != NULL ) {
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* assert( napi_throw( env, err ) == napi_ok );
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* return NULL;
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* }
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*
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* // ...
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* }

lib/node_modules/@stdlib/napi/create-double/README.md

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napi_value value;
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napi_status status = stdlib_napi_create_double( env, 1.0, &value );
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assert( status == napi_ok );
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if ( err != NULL ) {
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assert( napi_throw( env, err ) == napi_ok );
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return NULL;
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}
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// ...
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}

lib/node_modules/@stdlib/napi/create-double/src/main.c

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* napi_value value;
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* napi_status status = stdlib_napi_create_double( env, 1.0, &value );
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* assert( status == napi_ok );
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* if ( err != NULL ) {
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* assert( napi_throw( env, err ) == napi_ok );
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* return NULL;
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* }
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*
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* // ...
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* }

lib/node_modules/@stdlib/napi/create-int32/README.md

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napi_value value;
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napi_status status = stdlib_napi_create_int32( env, 1, &value );
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assert( status == napi_ok );
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if ( err != NULL ) {
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assert( napi_throw( env, err ) == napi_ok );
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return NULL;
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}
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// ...
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}

lib/node_modules/@stdlib/napi/create-int32/src/main.c

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* napi_status status = stdlib_napi_create_int32( env, 1, &value );
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* assert( status == napi_ok );
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* if ( err != NULL ) {
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* assert( napi_throw( env, err ) == napi_ok );
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* return NULL;
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* }
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*
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* // ...
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* }

lib/node_modules/@stdlib/napi/create-int64/README.md

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napi_value value;
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napi_status status = stdlib_napi_create_int64( env, 1, &value );
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assert( status == napi_ok );
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if ( err != NULL ) {
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assert( napi_throw( env, err ) == napi_ok );
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return NULL;
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}
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// ...
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}

lib/node_modules/@stdlib/napi/create-int64/src/main.c

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* napi_value value;
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* napi_status status = stdlib_napi_create_int64( env, 1, &value );
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* assert( status == napi_ok );
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* if ( err != NULL ) {
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* assert( napi_throw( env, err ) == napi_ok );
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* return NULL;
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* }
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*
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* // ...
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* }

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