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feat: add blas/base/ndarray/gscal
PR-URL: #11946 Co-authored-by: Athan Reines <kgryte@gmail.com> Reviewed-by: Athan Reines <kgryte@gmail.com>
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‎lib/node_modules/@stdlib/blas/base/ndarray/gscal/README.md‎

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

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

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

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

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{{alias}}( arrays )
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Multiplies a one-dimensional ndarray by a scalar constant.
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If provided an empty input ndarray, the function returns the input ndarray
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unchanged.
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Parameters
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----------
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arrays: ArrayLikeObject<ndarray>
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Array-like object containing the following ndarrays:
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- a one-dimensional input/output ndarray.
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- a zero-dimensional ndarray containing a scalar constant.
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Returns
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-------
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out: ndarray
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Input ndarray.
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Examples
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--------
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> var x = {{alias:@stdlib/ndarray/vector/ctor}}( [ 4.0, 2.0, -3.0, 5.0, -1.0 ], 'generic' );
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> var alpha = {{alias:@stdlib/ndarray/from-scalar}}( 5.0, { 'dtype': 'generic' } );
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> {{alias}}( [ x, alpha ] );
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> x
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<ndarray>[ 20.0, 10.0, -15.0, 25.0, -5.0 ]
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See Also
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--------
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‎lib/node_modules/@stdlib/blas/base/ndarray/gscal/docs/types/index.d.ts‎

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/*
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* @license Apache-2.0
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*
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* Copyright (c) 2026 The Stdlib Authors.
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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// TypeScript Version: 4.1
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/// <reference types="@stdlib/types"/>
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import { typedndarray } from '@stdlib/types/ndarray';
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/**
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* Multiplies a one-dimensional ndarray by a scalar constant.
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*
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* ## Notes
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*
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* - The function expects the following ndarrays:
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*
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* - a one-dimensional input ndarray.
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* - a zero-dimensional ndarray containing a scalar constant.
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*
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* @param arrays - array-like object containing ndarrays
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* @returns input ndarray
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*
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* @example
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* var vector = require( '@stdlib/ndarray/vector/ctor' );
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* var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
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*
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* var x = vector( [ 1.0, 2.0, 3.0, 4.0, 5.0 ], 'generic' );
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*
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* var alpha = scalar2ndarray( 5.0, {
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* 'dtype': 'generic'
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* });
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*
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* var y = gscal( [ x, alpha ] );
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* // returns <ndarray>[ 5.0, 10.0, 15.0, 20.0, 25.0 ]
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*
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* var bool = ( y === x );
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* // returns true
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*/
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declare function gscal<T extends typedndarray<number> = typedndarray<number>>( arrays: [ T, typedndarray<number> ] ): T;
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// EXPORTS //
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export = gscal;

‎lib/node_modules/@stdlib/blas/base/ndarray/gscal/docs/types/test.ts‎

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/*
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* @license Apache-2.0
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*
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* Copyright (c) 2026 The Stdlib Authors.
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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/* eslint-disable space-in-parens */
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import zeros = require( '@stdlib/ndarray/zeros' );
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import gscal = require( './index' );
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// TESTS //
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// The function returns an ndarray...
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{
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const x = zeros( [ 10 ], {
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'dtype': 'generic'
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});
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const alpha = zeros( [], {
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'dtype': 'generic'
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});
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gscal( [ x, alpha ] ); // $ExpectType genericndarray<number>
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}
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// The compiler throws an error if the function is provided a first argument which is not an array of ndarrays...
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{
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gscal( '10' ); // $ExpectError
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gscal( 10 ); // $ExpectError
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gscal( true ); // $ExpectError
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gscal( false ); // $ExpectError
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gscal( null ); // $ExpectError
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gscal( undefined ); // $ExpectError
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gscal( [] ); // $ExpectError
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gscal( {} ); // $ExpectError
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gscal( ( x: number ): number => x ); // $ExpectError
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}
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// The compiler throws an error if the function is provided an unsupported number of arguments...
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{
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const x = zeros( [ 10 ], {
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'dtype': 'generic'
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});
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const alpha = zeros( [], {
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'dtype': 'generic'
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});
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gscal(); // $ExpectError
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gscal( [ x, alpha ], {} ); // $ExpectError
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}

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