Merge remote-tracking branch 'upstream/develop' into philipp/fix-propagation-2026-04-18

Author: stdlib-bot

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

@@ -45,6 +45,7 @@ The namespace exposes the following APIs:
 
 <div class="namespace-toc">
 
+-   <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">[`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">[`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:
 -   <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>
 -   <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>
 -   <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>
+-   <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>
 
 </div>
 
@@ -96,6 +98,8 @@ console.log( objectKeys( ns ) );
 
 <!-- <toc-links> -->
 
+[@stdlib/blas/base/ndarray/caxpy]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/base/ndarray/caxpy
+
 [@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
@@ -114,6 +118,8 @@ console.log( objectKeys( ns ) );
 
 [@stdlib/blas/base/ndarray/sdot]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/base/ndarray/sdot
 
+[@stdlib/blas/base/ndarray/zaxpy]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/blas/base/ndarray/zaxpy
+
 <!-- </toc-links> -->
 
 </section>

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

@@ -20,6 +20,7 @@
 
 /* eslint-disable max-lines */
 
+import caxpy = require( '@stdlib/blas/base/ndarray/caxpy' );
 import dasum = require( '@stdlib/blas/base/ndarray/dasum' );
 import daxpy = require( '@stdlib/blas/base/ndarray/daxpy' );
 import ddot = require( '@stdlib/blas/base/ndarray/ddot' );
@@ -29,11 +30,40 @@ import gdot = require( '@stdlib/blas/base/ndarray/gdot' );
 import sasum = require( '@stdlib/blas/base/ndarray/sasum' );
 import saxpy = require( '@stdlib/blas/base/ndarray/saxpy' );
 import sdot = require( '@stdlib/blas/base/ndarray/sdot' );
+import zaxpy = require( '@stdlib/blas/base/ndarray/zaxpy' );
 
 /**
 * Interface describing the `ndarray` namespace.
 */
 interface Namespace {
+	/**
+	* 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`.
+	*
+	* @param arrays - array-like object containing an input ndarray, an output ndarray, and a zero-dimensional ndarray containing a scalar constant
+	* @returns output ndarray
+	*
+	* @example
+	* var Complex64Array = require( '@stdlib/array/complex64' );
+	* var Complex64 = require( '@stdlib/complex/float32/ctor' );
+	* var scalar2ndarray = require( '@stdlib/ndarray/base/from-scalar' );
+	* var ndarray = require( '@stdlib/ndarray/base/ctor' );
+	*
+	* var xbuf = new Complex64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0 ] );
+	* var x = new ndarray( 'complex64', xbuf, [ 5 ], [ 1 ], 0, 'row-major' );
+	*
+	* var ybuf = new Complex64Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );
+	* var y = new ndarray( 'complex64', ybuf, [ 5 ], [ 1 ], 0, 'row-major' );
+	*
+	* var alpha = scalar2ndarray( new Complex64( 1.0, 2.0 ), 'complex64', 'row-major' );
+	*
+	* var z = ns.caxpy( [ x, y, alpha ] );
+	* // 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 ] ]
+	*
+	* var bool = ( z === y );
+	* // returns true
+	*/
+	caxpy: typeof caxpy;
+
 	/**
 	* Computes the sum of absolute values for all elements in a one-dimensional double-precision floating-point ndarray.
 	*
@@ -228,6 +258,34 @@ interface Namespace {
 	* // returns -5.0
 	*/
 	sdot: typeof sdot;
+
+	/**
+	* 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`.
+	*
+	* @param arrays - array-like object containing an input ndarray, an output ndarray, and a zero-dimensional ndarray containing a scalar constant
+	* @returns output ndarray
+	*
+	* @example
+	* var Complex128Array = require( '@stdlib/array/complex128' );
+	* var Complex128 = require( '@stdlib/complex/float64/ctor' );
+	* var scalar2ndarray = require( '@stdlib/ndarray/base/from-scalar' );
+	* var ndarray = require( '@stdlib/ndarray/base/ctor' );
+	*
+	* var xbuf = new Complex128Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0 ] );
+	* var x = new ndarray( 'complex128', xbuf, [ 5 ], [ 1 ], 0, 'row-major' );
+	*
+	* var ybuf = new Complex128Array( [ 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0 ] );
+	* var y = new ndarray( 'complex128', ybuf, [ 5 ], [ 1 ], 0, 'row-major' );
+	*
+	* var alpha = scalar2ndarray( new Complex128( 1.0, 2.0 ), 'complex128', 'row-major' );
+	*
+	* var z = ns.zaxpy( [ x, y, alpha ] );
+	* // 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 ] ]
+	*
+	* var bool = ( z === y );
+	* // returns true
+	*/
+	zaxpy: typeof zaxpy;
 }
 
 /**

lib/node_modules/@stdlib/blas/base/ndarray/lib/index.js

@@ -63,6 +63,15 @@ setReadOnly( ns, 'dasum', require( '@stdlib/blas/base/ndarray/dasum' ) );
 */
 setReadOnly( ns, 'daxpy', require( '@stdlib/blas/base/ndarray/daxpy' ) );
 
+/**
+* @name dcopy
+* @memberof ns
+* @readonly
+* @type {Function}
+* @see {@link module:@stdlib/blas/base/ndarray/dcopy}
+*/
+setReadOnly( ns, 'dcopy', require( '@stdlib/blas/base/ndarray/dcopy' ) );
+
 /**
 * @name ddot
 * @memberof ns

lib/node_modules/@stdlib/blas/ext/base/gunitspace/README.md

@@ -0,0 +1,156 @@
+<!--
+
+@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.
+
+-->
+
+# gunitspace
+
+> Fill a strided array with linearly spaced numeric elements which increment by `1` starting from a specified value.
+
+<section class="usage">
+
+## Usage
+
+```javascript
+var gunitspace = require( '@stdlib/blas/ext/base/gunitspace' );
+```
+
+#### gunitspace( N, start, x, strideX )
+
+Fills a strided array with linearly spaced numeric elements which increment by `1` starting from a specified value.
+
+```javascript
+var x = [ 0.0, 0.0, 0.0, 0.0 ];
+
+gunitspace( x.length, 3.0, x, 1 );
+// x => [ 3.0, 4.0, 5.0, 6.0 ]
+```
+
+The function has the following parameters:
+
+-   **N**: number of indexed elements.
+-   **start**: starting value.
+-   **x**: input array.
+-   **strideX**: stride length.
+
+The `N` and stride parameters determine which elements in the strided array are accessed at runtime. For example, to fill every other element:
+
+```javascript
+var x = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];
+
+gunitspace( 3, 3.0, x, 2 );
+// x => [ 3.0, 0.0, 4.0, 0.0, 5.0, 0.0 ]
+```
+
+Note that indexing is relative to the first index. To introduce an offset, use [`typed array`][mdn-typed-array] views.
+
+```javascript
+var Float64Array = require( '@stdlib/array/float64' );
+
+// Initial array...
+var x0 = new Float64Array( [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ] );
+
+// Create an offset view...
+var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
+
+// Fill every other element...
+gunitspace( 3, 3.0, x1, 2 );
+// x0 => <Float64Array>[ 0.0, 3.0, 0.0, 4.0, 0.0, 5.0 ]
+```
+
+#### gunitspace.ndarray( N, start, x, strideX, offsetX )
+
+Fills a strided array with linearly spaced numeric elements which increment by `1` starting from a specified value using alternative indexing semantics.
+
+```javascript
+var x = [ 0.0, 0.0, 0.0, 0.0 ];
+
+gunitspace.ndarray( x.length, 3.0, x, 1, 0 );
+// x => [ 3.0, 4.0, 5.0, 6.0 ]
+```
+
+The function has the following additional parameters:
+
+-   **offsetX**: starting index.
+
+While [`typed array`][mdn-typed-array] views mandate a view offset based on the underlying buffer, the offset parameter supports indexing semantics based on a starting index. For example, to access only the last three elements:
+
+```javascript
+var x = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];
+
+gunitspace.ndarray( 3, 3.0, x, 1, x.length-3 );
+// x => [ 0.0, 0.0, 0.0, 3.0, 4.0, 5.0 ]
+```
+
+</section>
+
+<!-- /.usage -->
+
+<section class="notes">
+
+## Notes
+
+-   If `N <= 0`, both functions return `x` unchanged.
+-   Both functions support array-like objects having getter and setter accessors for array element access (e.g., [`@stdlib/array/complex64`][@stdlib/array/complex64]).
+
+</section>
+
+<!-- /.notes -->
+
+<section class="examples">
+
+## Examples
+
+<!-- eslint no-undef: "error" -->
+
+```javascript
+var discreteUniform = require( '@stdlib/random/array/discrete-uniform' );
+var gunitspace = require( '@stdlib/blas/ext/base/gunitspace' );
+
+var x = discreteUniform( 10, -100, 100, {
+    'dtype': 'generic'
+});
+console.log( x );
+
+gunitspace( x.length, 0.0, x, 1 );
+console.log( x );
+```
+
+</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">
+
+[mdn-typed-array]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/TypedArray
+
+[@stdlib/array/complex64]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/array/complex64
+
+</section>
+
+<!-- /.links -->

lib/node_modules/@stdlib/blas/ext/base/gunitspace/benchmark/benchmark.js

@@ -0,0 +1,103 @@
+/**
+* @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/array/uniform' );
+var isnan = require( '@stdlib/math/base/assert/is-nan' );
+var pow = require( '@stdlib/math/base/special/pow' );
+var format = require( '@stdlib/string/format' );
+var pkg = require( './../package.json' ).name;
+var gunitspace = require( './../lib/main.js' );
+
+
+// VARIABLES //
+
+var options = {
+	'dtype': 'generic'
+};
+
+
+// FUNCTIONS //
+
+/**
+* Create a benchmark function.
+*
+* @private
+* @param {PositiveInteger} len - array length
+* @returns {Function} benchmark function
+*/
+function createBenchmark( len ) {
+	var x = uniform( len, -100, 100, options );
+	return benchmark;
+
+	/**
+	* Benchmark function.
+	*
+	* @private
+	* @param {Benchmark} b - benchmark instance
+	*/
+	function benchmark( b ) {
+		var y;
+		var i;
+
+		b.tic();
+		for ( i = 0; i < b.iterations; i++ ) {
+			y = gunitspace( x.length, 0.0, x, 1 );
+			if ( isnan( y[ i%x.length ] ) ) {
+				b.fail( 'should not return NaN' );
+			}
+		}
+		b.toc();
+		if ( isnan( y[ i%x.length ] ) ) {
+			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();