Merge branch 'develop' into blas/scartesian-power

Author: headlessNode

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

@@ -47,6 +47,7 @@ The namespace exposes the following APIs:
 
 -   <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>
 -   <span class="signature">[`ccopy( arrays )`][@stdlib/blas/base/ndarray/ccopy]</span><span class="delimiter">: </span><span class="description">copy values from a one-dimensional single-precision complex floating-point ndarray `x` into a one-dimensional single-precision complex floating-point ndarray `y`.</span>
+-   <span class="signature">[`cswap( arrays )`][@stdlib/blas/base/ndarray/cswap]</span><span class="delimiter">: </span><span class="description">interchange two one-dimensional complex single-precision floating-point ndarrays.</span>
 -   <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>
 -   <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>
 -   <span class="signature">[`dcopy( arrays )`][@stdlib/blas/base/ndarray/dcopy]</span><span class="delimiter">: </span><span class="description">copy values from a one-dimensional double-precision floating-point ndarray `x` into a one-dimensional double-precision floating-point ndarray `y`.</span>
@@ -64,6 +65,7 @@ The namespace exposes the following APIs:
 -   <span class="signature">[`sswap( arrays )`][@stdlib/blas/base/ndarray/sswap]</span><span class="delimiter">: </span><span class="description">interchange two one-dimensional single-precision floating-point ndarrays.</span>
 -   <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>
 -   <span class="signature">[`zcopy( arrays )`][@stdlib/blas/base/ndarray/zcopy]</span><span class="delimiter">: </span><span class="description">copy values from a one-dimensional double-precision complex floating-point ndarray `x` into a one-dimensional double-precision complex floating-point ndarray `y`.</span>
+-   <span class="signature">[`zswap( arrays )`][@stdlib/blas/base/ndarray/zswap]</span><span class="delimiter">: </span><span class="description">interchange two one-dimensional complex double-precision floating-point ndarrays.</span>
 
 </div>
 
@@ -110,6 +112,8 @@ console.log( objectKeys( ns ) );
 
 [@stdlib/blas/base/ndarray/ccopy]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/base/ndarray/ccopy
 
+[@stdlib/blas/base/ndarray/cswap]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/base/ndarray/cswap
+
 [@stdlib/blas/base/ndarray/dasum]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/base/ndarray/dasum
 
 [@stdlib/blas/base/ndarray/daxpy]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/base/ndarray/daxpy
@@ -144,6 +148,8 @@ console.log( objectKeys( ns ) );
 
 [@stdlib/blas/base/ndarray/zcopy]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/base/ndarray/zcopy
 
+[@stdlib/blas/base/ndarray/zswap]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/base/ndarray/zswap
+
 <!-- </toc-links> -->
 
 </section>

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

@@ -22,6 +22,7 @@
 
 import caxpy = require( '@stdlib/blas/base/ndarray/caxpy' );
 import ccopy = require( '@stdlib/blas/base/ndarray/ccopy' );
+import cswap = require( '@stdlib/blas/base/ndarray/cswap' );
 import dasum = require( '@stdlib/blas/base/ndarray/dasum' );
 import daxpy = require( '@stdlib/blas/base/ndarray/daxpy' );
 import dcopy = require( '@stdlib/blas/base/ndarray/dcopy' );
@@ -39,6 +40,7 @@ import sdot = require( '@stdlib/blas/base/ndarray/sdot' );
 import sswap = require( '@stdlib/blas/base/ndarray/sswap' );
 import zaxpy = require( '@stdlib/blas/base/ndarray/zaxpy' );
 import zcopy = require( '@stdlib/blas/base/ndarray/zcopy' );
+import zswap = require( '@stdlib/blas/base/ndarray/zswap' );
 
 /**
 * Interface describing the `ndarray` namespace.
@@ -105,6 +107,34 @@ interface Namespace {
 	*/
 	ccopy: typeof ccopy;
 
+	/**
+	* Interchanges two one-dimensional complex single-precision floating-point ndarrays.
+	*
+	* ## Notes
+	*
+	* -   The function expects the following ndarrays:
+	*
+	*     -   first one-dimensional input ndarray.
+	*     -   second one-dimensional input ndarray.
+	*
+	* @param arrays - array-like object containing ndarrays
+	* @returns second input ndarray
+	*
+	* @example
+	* var Complex64Vector = require( '@stdlib/ndarray/vector/complex64' );
+	*
+	* var x = new Complex64Vector( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );
+	* var y = new Complex64Vector( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );
+	*
+	* var z = ns.cswap( [ x, y ] );
+	* // x => <ndarray>[ <Complex64>[ 7.0, 8.0 ], <Complex64>[ 9.0, 10.0 ], <Complex64>[ 11.0, 12.0 ] ]
+	* // y => <ndarray>[ <Complex64>[ 1.0, 2.0 ], <Complex64>[ 3.0, 4.0 ], <Complex64>[ 5.0, 6.0 ] ]
+	*
+	* var bool = ( z === y );
+	* // returns true
+	*/
+	cswap: typeof cswap;
+
 	/**
 	* Computes the sum of absolute values for all elements in a one-dimensional double-precision floating-point ndarray.
 	*
@@ -567,6 +597,34 @@ interface Namespace {
 	* // returns true
 	*/
 	zcopy: typeof zcopy;
+
+	/**
+	* Interchanges two one-dimensional complex double-precision floating-point ndarrays.
+	*
+	* ## Notes
+	*
+	* -   The function expects the following ndarrays:
+	*
+	*     -   first one-dimensional input ndarray.
+	*     -   second one-dimensional input ndarray.
+	*
+	* @param arrays - array-like object containing ndarrays
+	* @returns second input ndarray
+	*
+	* @example
+	* var Complex128Vector = require( '@stdlib/ndarray/vector/complex128' );
+	*
+	* var x = new Complex128Vector( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ] );
+	* var y = new Complex128Vector( [ 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );
+	*
+	* var z = ns.zswap( [ x, y ] );
+	* // x => <ndarray>[ <Complex128>[ 7.0, 8.0 ], <Complex128>[ 9.0, 10.0 ], <Complex128>[ 11.0, 12.0 ] ]
+	* // y => <ndarray>[ <Complex128>[ 1.0, 2.0 ], <Complex128>[ 3.0, 4.0 ], <Complex128>[ 5.0, 6.0 ] ]
+	*
+	* var bool = ( z === y );
+	* // returns true
+	*/
+	zswap: typeof zswap;
 }
 
 /**

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

@@ -0,0 +1,120 @@
+<!--
+
+@license Apache-2.0
+
+Copyright (c) 2026 The Stdlib Authors.
+
+Licensed under the Apache License, Version 2.0 (the "License");
+you may not use this file except in compliance with the License.
+You may obtain a copy of the License at
+
+   http://www.apache.org/licenses/LICENSE-2.0
+
+Unless required by applicable law or agreed to in writing, software
+distributed under the License is distributed on an "AS IS" BASIS,
+WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+See the License for the specific language governing permissions and
+limitations under the License.
+
+-->
+
+# dscal
+
+> Multiply a one-dimensional double-precision floating-point ndarray by a scalar constant.
+
+<section class="intro">
+
+</section>
+
+<!-- /.intro -->
+
+<section class="usage">
+
+## Usage
+
+```javascript
+var dscal = require( '@stdlib/blas/base/ndarray/dscal' );
+```
+
+#### dscal( arrays )
+
+Multiplies a one-dimensional double-precision floating-point ndarray by a scalar constant.
+
+```javascript
+var Float64Vector = require( '@stdlib/ndarray/vector/float64' );
+var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
+
+var x = new Float64Vector( [ 1.0, 2.0, 3.0, 4.0, 5.0 ] );
+
+var alpha = scalar2ndarray( 5.0, {
+    'dtype': 'float64'
+});
+
+var y = dscal( [ x, alpha ] );
+// returns <ndarray>[ 5.0, 10.0, 15.0, 20.0, 25.0 ]
+
+var bool = ( y === x );
+// returns true
+```
+
+The function has the following parameters:
+
+-   **arrays**: array-like object containing the following ndarrays:
+
+    -   a one-dimensional input ndarray.
+    -   a zero-dimensional ndarray containing a scalar constant.
+
+</section>
+
+<!-- /.usage -->
+
+<section class="notes">
+
+</section>
+
+<!-- /.notes -->
+
+<section class="examples">
+
+## Examples
+
+<!-- eslint no-undef: "error" -->
+
+```javascript
+var discreteUniform = require( '@stdlib/random/discrete-uniform' );
+var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
+var ndarray2array = require( '@stdlib/ndarray/to-array' );
+var dscal = require( '@stdlib/blas/base/ndarray/dscal' );
+
+var opts = {
+    'dtype': 'float64'
+};
+
+var x = discreteUniform( [ 10 ], 0, 100, opts );
+console.log( ndarray2array( x ) );
+
+var alpha = scalar2ndarray( 5.0, opts );
+
+var out = dscal( [ x, alpha ] );
+console.log( ndarray2array( out ) );
+```
+
+</section>
+
+<!-- /.examples -->
+
+<!-- Section for related `stdlib` packages. Do not manually edit this section, as it is automatically populated. -->
+
+<section class="related">
+
+</section>
+
+<!-- /.related -->
+
+<!-- Section for all links. Make sure to keep an empty line after the `section` element and another before the `/section` close. -->
+
+<section class="links">
+
+</section>
+
+<!-- /.links -->

lib/node_modules/@stdlib/blas/base/ndarray/dscal/benchmark/benchmark.js

@@ -0,0 +1,109 @@
+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2026 The Stdlib Authors.
+*
+* Licensed under the Apache License, Version 2.0 (the "License");
+* you may not use this file except in compliance with the License.
+* You may obtain a copy of the License at
+*
+*    http://www.apache.org/licenses/LICENSE-2.0
+*
+* Unless required by applicable law or agreed to in writing, software
+* distributed under the License is distributed on an "AS IS" BASIS,
+* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+* See the License for the specific language governing permissions and
+* limitations under the License.
+*/
+
+'use strict';
+
+// MODULES //
+
+var bench = require( '@stdlib/bench' );
+var uniform = require( '@stdlib/random/uniform' );
+var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var pow = require( '@stdlib/math/base/special/pow' );
+var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
+var format = require( '@stdlib/string/format' );
+var pkg = require( './../package.json' ).name;
+var dscal = require( './../lib' );
+
+
+// VARIABLES //
+
+var options = {
+	'dtype': 'float64'
+};
+
+
+// FUNCTIONS //
+
+/**
+* Creates a benchmark function.
+*
+* @private
+* @param {PositiveInteger} len - array length
+* @returns {Function} benchmark function
+*/
+function createBenchmark( len ) {
+	var alpha;
+	var x;
+
+	x = uniform( [ len ], -100.0, 100.0, options );
+	alpha = scalar2ndarray( 5.0, options );
+
+	return benchmark;
+
+	/**
+	* Benchmark function.
+	*
+	* @private
+	* @param {Benchmark} b - benchmark instance
+	*/
+	function benchmark( b ) {
+		var z;
+		var i;
+
+		b.tic();
+		for ( i = 0; i < b.iterations; i++ ) {
+			z = dscal( [ x, alpha ] );
+			if ( typeof z !== 'object' ) {
+				b.fail( 'should return an ndarray' );
+			}
+		}
+		b.toc();
+		if ( isnan( z.get( i%len ) ) ) {
+			b.fail( 'should not return NaN' );
+		}
+		b.pass( 'benchmark finished' );
+		b.end();
+	}
+}
+
+
+// MAIN //
+
+/**
+* Main execution sequence.
+*
+* @private
+*/
+function main() {
+	var len;
+	var min;
+	var max;
+	var f;
+	var i;
+
+	min = 1; // 10^min
+	max = 6; // 10^max
+
+	for ( i = min; i <= max; i++ ) {
+		len = pow( 10, i );
+		f = createBenchmark( len );
+		bench( format( '%s:len=%d', pkg, len ), f );
+	}
+}
+
+main();

lib/node_modules/@stdlib/blas/base/ndarray/dscal/docs/repl.txt

@@ -0,0 +1,33 @@
+
+{{alias}}( arrays )
+    Multiplies a one-dimensional double-precision floating-point ndarray by a
+    scalar constant.
+
+    If provided an empty input ndarray, the function returns the input ndarray
+    unchanged.
+
+    Parameters
+    ----------
+    arrays: ArrayLikeObject<ndarray>
+        Array-like object containing the following ndarrays:
+
+        - a one-dimensional input ndarray.
+        - a zero-dimensional ndarray containing a scalar constant.
+
+    Returns
+    -------
+    out: ndarray
+        Input ndarray.
+
+    Examples
+    --------
+    > var x = new {{alias:@stdlib/ndarray/vector/float64}}( [ 4.0, 2.0, -3.0, 5.0, -1.0 ] );
+    > var alpha = {{alias:@stdlib/ndarray/from-scalar}}( 5.0, { 'dtype': 'float64' } );
+
+    > {{alias}}( [ x, alpha ] );
+    > x
+    <ndarray>[ 20.0, 10.0, -15.0, 25.0, -5.0 ]
+
+    See Also
+    --------
+