feat: add blas/ext/axpb

lib/node_modules/@stdlib/blas/ext/axpb/README.md

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+<!--
+
+@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.
+
+-->
+
+# axpb
+
+> Multiply each element in an input [ndarray][@stdlib/ndarray/ctor] by a scalar constant and add a scalar constant to each result along one or more [ndarray][@stdlib/ndarray/ctor] dimensions.
+
+<section class="intro">
+
+This BLAS extension implements the operation
+
+<!-- <equation class="equation" label="eq:axpb" align="center" raw="\mathbf{x} = \alpha \mathbf{x} + \beta" alt="Equation for axpb operation."> -->
+
+```math
+\mathbf{x} = \alpha \mathbf{x} + \beta
+```
+
+<!-- </equation> -->
+
+</section>
+
+<!-- /.intro -->
+
+<section class="usage">
+
+## Usage
+
+```javascript
+var axpb = require( '@stdlib/blas/ext/axpb' );
+```
+
+#### axpb( x, alpha, beta\[, options] )
+
+Multiplies each element in an input [ndarray][@stdlib/ndarray/ctor] by a scalar constant and adds a scalar constant to each result along one or more [ndarray][@stdlib/ndarray/ctor] dimensions.
+
+```javascript
+var array = require( '@stdlib/ndarray/array' );
+
+var x = array( [ -2.0, 1.0, 3.0, -5.0 ] );
+
+var y = axpb( x, 5.0, 3.0 );
+// returns <ndarray>[ -7.0, 8.0, 18.0, -22.0 ]
+
+var bool = ( x === y );
+// returns true
+```
+
+The function has the following parameters:
+
+-   **x**: input [ndarray][@stdlib/ndarray/ctor]. Must have a floating-point or "generic" [data type][@stdlib/ndarray/dtypes].
+-   **alpha**: scalar constant to multiply. May be a numeric scalar (number or complex number) or an [ndarray][@stdlib/ndarray/ctor] having a floating-point or "generic" [data type][@stdlib/ndarray/dtypes]. If provided an [ndarray][@stdlib/ndarray/ctor], the value must have a shape which is [broadcast-compatible][@stdlib/ndarray/base/broadcast-shapes] with the complement of the shape defined by `options.dims`. For example, given the input shape `[2, 3, 4]` and `options.dims=[0]`, an [ndarray][@stdlib/ndarray/ctor] alpha must have a shape which is [broadcast-compatible][@stdlib/ndarray/base/broadcast-shapes] with the shape `[3, 4]`. Similarly, when performing the operation over all elements in a provided input [ndarray][@stdlib/ndarray/ctor], an [ndarray][@stdlib/ndarray/ctor] alpha must be a zero-dimensional [ndarray][@stdlib/ndarray/ctor].
+-   **beta**: scalar constant to add. May be a numeric scalar (number or complex number) or an [ndarray][@stdlib/ndarray/ctor] having a floating-point or "generic" [data type][@stdlib/ndarray/dtypes]. Broadcasting semantics are the same as for alpha.
+-   **options**: function options (_optional_).
+
+The function accepts the following options:
+
+-   **dims**: list of dimensions over which to perform operation. If not provided, the function performs the operation over all elements in a provided input [ndarray][@stdlib/ndarray/ctor].
+
+Both `alpha` and `beta` can be complex numbers:
+
+```javascript
+var Complex128 = require( '@stdlib/complex/float64/ctor' );
+var Complex128Vector = require( '@stdlib/ndarray/vector/complex128' );
+
+var x = new Complex128Vector( [ 1.0, 2.0, 3.0, 4.0 ] );
+
+var alpha = new Complex128( 2.0, 1.0 );
+var beta = new Complex128( 1.0, 0.0 );
+
+var y = axpb( x, alpha, beta );
+// returns <ndarray>[ <Complex128>[ 1.0, 5.0 ], <Complex128>[ 3.0, 11.0 ] ]
+```
+
+The function also supports complex-valued floating-point ndarrays:
+
+```javascript
+var Complex128Vector = require( '@stdlib/ndarray/vector/complex128' );
+
+var x = new Complex128Vector( [ 1.0, 2.0, 3.0, 4.0 ] );
+
+var y = axpb( x, 2.0, 1.0 );
+// returns <ndarray>[ <Complex128>[ 3.0, 4.0 ], <Complex128>[ 7.0, 8.0 ] ]
+```
+
+By default, the function performs the operation over all elements in a provided input [ndarray][@stdlib/ndarray/ctor]. To perform the operation over specific dimensions, provide a `dims` option.
+
+```javascript
+var array = require( '@stdlib/ndarray/array' );
+
+var x = array( [ -2.0, 1.0, 3.0, -5.0 ], {
+    'shape': [ 2, 2 ],
+    'order': 'row-major'
+});
+// returns <ndarray>[ [ -2.0, 1.0 ], [ 3.0, -5.0 ] ]
+
+var y = axpb( x, 5.0, 3.0, {
+    'dims': [ 0 ]
+});
+// returns <ndarray>[ [ -7.0, 8.0 ], [ 18.0, -22.0 ] ]
+```
+
+</section>
+
+<!-- /.usage -->
+
+<section class="notes">
+
+## Notes
+
+-   The input [ndarray][@stdlib/ndarray/ctor] is modified **in-place** (i.e., the input [ndarray][@stdlib/ndarray/ctor] is **mutated**).
+-   The function iterates over [ndarray][@stdlib/ndarray/ctor] elements according to the memory layout of the input [ndarray][@stdlib/ndarray/ctor]. Accordingly, performance degradation is possible when operating over multiple dimensions of a large non-contiguous multi-dimensional input [ndarray][@stdlib/ndarray/ctor]. In such scenarios, one may want to copy an input [ndarray][@stdlib/ndarray/ctor] to contiguous memory before performing the operation.
+
+</section>
+
+<!-- /.notes -->
+
+<section class="examples">
+
+## Examples
+
+<!-- eslint no-undef: "error" -->
+
+```javascript
+var discreteUniform = require( '@stdlib/random/discrete-uniform' );
+var ndarray2array = require( '@stdlib/ndarray/to-array' );
+var axpb = require( '@stdlib/blas/ext/axpb' );
+
+// Create an input ndarray:
+var x = discreteUniform( [ 5, 2 ], -100, 100, {
+    'dtype': 'generic'
+});
+
+// Print the input ndarray:
+console.log( ndarray2array( x ) );
+
+// Perform operation:
+axpb( x, 2.0, 5.0 );
+
+// Print the result:
+console.log( ndarray2array( 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">
+
+[@stdlib/ndarray/ctor]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/ctor
+
+[@stdlib/ndarray/dtypes]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/dtypes
+
+[@stdlib/ndarray/base/broadcast-shapes]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/broadcast-shapes
+
+</section>
+
+<!-- /.links -->

lib/node_modules/@stdlib/blas/ext/axpb/benchmark/benchmark.js

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+/**
+* @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 isnan = require( '@stdlib/math/base/assert/is-nan' );
+var pow = require( '@stdlib/math/base/special/pow' );
+var uniform = require( '@stdlib/random/uniform' );
+var format = require( '@stdlib/string/format' );
+var pkg = require( './../package.json' ).name;
+var axpb = 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 x = uniform( [ len ], -50.0, 50.0, options );
+	return benchmark;
+
+	/**
+	* Benchmark function.
+	*
+	* @private
+	* @param {Benchmark} b - benchmark instance
+	*/
+	function benchmark( b ) {
+		var o;
+		var i;
+
+		b.tic();
+		for ( i = 0; i < b.iterations; i++ ) {
+			o = axpb( x, 5.0, 3.0 );
+			if ( typeof o !== 'object' ) {
+				b.fail( 'should return an ndarray' );
+			}
+		}
+		b.toc();
+		if ( isnan( o.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:dtype=%s,len=%d', pkg, options.dtype, len ), f );
+	}
+}
+
+main();

lib/node_modules/@stdlib/blas/ext/axpb/docs/repl.txt

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+
+{{alias}}( x, alpha, beta[, options] )
+    Multiplies each element in an input ndarray by a scalar constant and adds a
+    scalar constant to each result along one or more ndarray dimensions.
+
+    The function performs the operation in-place and thus mutates the input
+    ndarray.
+
+    Parameters
+    ----------
+    x: ndarray
+        Input array. Must have a numeric or "generic" data type.
+
+    alpha: ndarray|number|ComplexLike
+        Scalar constant to multiply. May be either a scalar value, or an ndarray
+        having a floating-point or "generic" data type. If provided an ndarray,
+        the value must have a shape which is broadcast compatible with the
+        complement of the shape defined by `options.dims`. For example, given
+        the input shape `[2, 3, 4]` and `options.dims=[0]`, an ndarray alpha
+        must have a shape which is broadcast compatible with the shape `[3, 4]`.
+        Similarly, when performing the operation over all elements in a provided
+        input ndarray, an ndarray alpha must be a zero-dimensional ndarray.
+
+    beta: ndarray|number|ComplexLike
+        Scalar constant to add. May be either a scalar value, or an ndarray
+        having a floating-point or "generic" data type. Broadcasting semantics
+        are the same as for alpha.
+
+    options: Object (optional)
+        Function options.
+
+    options.dims: Array<integer> (optional)
+        List of dimensions over which to perform operation. If not provided, the
+        function performs the operation over all elements in a provided input
+        ndarray.
+
+    Returns
+    -------
+    out: ndarray
+        Input array.
+
+    Examples
+    --------
+    > var x = {{alias:@stdlib/ndarray/array}}( [ -2.0, 1.0, 3.0, -5.0 ] );
+    > var y = {{alias}}( x, 5.0, 3.0 )
+    <ndarray>[ -7.0, 8.0, 18.0, -22.0 ]
+
+    See Also
+    --------