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120 changes: 120 additions & 0 deletions
120
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"); | ||
| you may not use this file except in compliance with the License. | ||
| 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 | ||
| 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. | ||
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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 | ||
| var gscal = require( '@stdlib/blas/base/ndarray/gscal' ); | ||
| ``` | ||
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| #### gscal( arrays ) | ||
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| Multiplies a one-dimensional ndarray by a scalar constant. | ||
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| ```javascript | ||
| var vector = require( '@stdlib/ndarray/vector/ctor' ); | ||
| 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, { | ||
| 'dtype': 'generic' | ||
| }); | ||
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| var y = gscal( [ x, alpha ] ); | ||
| // returns <ndarray>[ 5.0, 10.0, 15.0, 20.0, 25.0 ] | ||
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| var bool = ( y === x ); | ||
| // returns true | ||
| ``` | ||
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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. | ||
| - 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 | ||
| var discreteUniform = require( '@stdlib/random/discrete-uniform' ); | ||
| var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); | ||
| var ndarray2array = require( '@stdlib/ndarray/to-array' ); | ||
| var gscal = require( '@stdlib/blas/base/ndarray/gscal' ); | ||
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| var opts = { | ||
| 'dtype': 'generic' | ||
| }; | ||
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| var x = discreteUniform( [ 10 ], 0, 100, opts ); | ||
| console.log( ndarray2array( x ) ); | ||
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| var alpha = scalar2ndarray( 5.0, opts ); | ||
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| var out = gscal( [ x, alpha ] ); | ||
| console.log( ndarray2array( out ) ); | ||
| ``` | ||
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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 --> |
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109
lib/node_modules/@stdlib/blas/base/ndarray/gscal/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. | ||
| */ | ||
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| 'use strict'; | ||
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| // MODULES // | ||
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| 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 gscal = require( './../lib' ); | ||
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| // VARIABLES // | ||
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| var options = { | ||
| 'dtype': 'generic' | ||
| }; | ||
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| // FUNCTIONS // | ||
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| /** | ||
| * Creates a benchmark function. | ||
| * | ||
| * @private | ||
| * @param {PositiveInteger} len - array length | ||
| * @returns {Function} benchmark function | ||
| */ | ||
| function createBenchmark( len ) { | ||
| var alpha; | ||
| var x; | ||
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| x = uniform( [ len ], -100.0, 100.0, options ); | ||
| alpha = scalar2ndarray( 5.0, options ); | ||
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| return benchmark; | ||
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| /** | ||
| * Benchmark function. | ||
| * | ||
| * @private | ||
| * @param {Benchmark} b - benchmark instance | ||
| */ | ||
| function benchmark( b ) { | ||
| var z; | ||
| var i; | ||
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| b.tic(); | ||
| for ( i = 0; i < b.iterations; i++ ) { | ||
| z = gscal( [ 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(); | ||
| } | ||
| } | ||
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| // MAIN // | ||
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| /** | ||
| * Main execution sequence. | ||
| * | ||
| * @private | ||
| */ | ||
| function main() { | ||
| var len; | ||
| var min; | ||
| var max; | ||
| var f; | ||
| var i; | ||
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| min = 1; // 10^min | ||
| max = 6; // 10^max | ||
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| for ( i = min; i <= max; i++ ) { | ||
| len = pow( 10, i ); | ||
| f = createBenchmark( len ); | ||
| bench( format( '%s:len=%d', pkg, len ), f ); | ||
| } | ||
| } | ||
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| main(); |
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32
lib/node_modules/@stdlib/blas/base/ndarray/gscal/docs/repl.txt
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| {{alias}}( arrays ) | ||
| 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 | ||
| unchanged. | ||
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| Parameters | ||
| ---------- | ||
| arrays: ArrayLikeObject<ndarray> | ||
| Array-like object containing the following ndarrays: | ||
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| - a one-dimensional input/output ndarray. | ||
| - a zero-dimensional ndarray containing a scalar constant `alpha`. | ||
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| Returns | ||
| ------- | ||
| out: ndarray | ||
| Input ndarray. | ||
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| Examples | ||
| -------- | ||
| > var x = {{alias:@stdlib/ndarray/vector/ctor}}( [ 4.0, 2.0, -3.0, 5.0, -1.0 ], 'generic' ); | ||
| > var alpha = {{alias:@stdlib/ndarray/from-scalar}}( 5.0, { 'dtype': 'generic' } ); | ||
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| > {{alias}}( [ x, alpha ] ); | ||
| > x | ||
| <ndarray>[ 20.0, 10.0, -15.0, 25.0, -5.0 ] | ||
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| See Also | ||
| -------- | ||
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59 changes: 59 additions & 0 deletions
59
lib/node_modules/@stdlib/blas/base/ndarray/gscal/docs/types/index.d.ts
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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. | ||
| */ | ||
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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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| /** | ||
| * Multiplies a one-dimensional ndarray by a scalar constant. | ||
| * | ||
| * ## Notes | ||
| * | ||
| * - The function expects the following ndarrays: | ||
| * | ||
| * - a one-dimensional input ndarray. | ||
| * - a zero-dimensional ndarray containing a scalar constant. | ||
| * | ||
| * @param arrays - array-like object containing ndarrays | ||
| * @returns input ndarray | ||
| * | ||
| * @example | ||
| * var vector = require( '@stdlib/ndarray/vector/ctor' ); | ||
| * var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' ); | ||
| * | ||
| * var x = vector( [ 1.0, 2.0, 3.0, 4.0, 5.0 ], 'generic' ); | ||
| * | ||
| * var alpha = scalar2ndarray( 5.0, { | ||
| * 'dtype': 'generic' | ||
| * }); | ||
| * | ||
| * var y = gscal( [ x, alpha ] ); | ||
| * // returns <ndarray>[ 5.0, 10.0, 15.0, 20.0, 25.0 ] | ||
| * | ||
| * var bool = ( y === x ); | ||
| * // returns true | ||
| */ | ||
| 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; |
63 changes: 63 additions & 0 deletions
63
lib/node_modules/@stdlib/blas/base/ndarray/gscal/docs/types/test.ts
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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. | ||
| */ | ||
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| /* eslint-disable space-in-parens */ | ||
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| import zeros = require( '@stdlib/ndarray/zeros' ); | ||
| import gscal = require( './index' ); | ||
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| // TESTS // | ||
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| // The function returns an ndarray... | ||
| { | ||
| const x = zeros( [ 10 ], { | ||
| 'dtype': 'generic' | ||
| }); | ||
| const alpha = zeros( [], { | ||
| 'dtype': 'generic' | ||
| }); | ||
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| gscal( [ x, alpha ] ); // $ExpectType genericndarray<number> | ||
| } | ||
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| // The compiler throws an error if the function is provided a first argument which is not an array of ndarrays... | ||
| { | ||
| gscal( '10' ); // $ExpectError | ||
| gscal( 10 ); // $ExpectError | ||
| gscal( true ); // $ExpectError | ||
| gscal( false ); // $ExpectError | ||
| gscal( null ); // $ExpectError | ||
| gscal( undefined ); // $ExpectError | ||
| gscal( [] ); // $ExpectError | ||
| gscal( {} ); // $ExpectError | ||
| gscal( ( x: number ): number => x ); // $ExpectError | ||
| } | ||
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| // The compiler throws an error if the function is provided an unsupported number of arguments... | ||
| { | ||
| const x = zeros( [ 10 ], { | ||
| 'dtype': 'generic' | ||
| }); | ||
| const alpha = zeros( [], { | ||
| 'dtype': 'generic' | ||
| }); | ||
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| gscal(); // $ExpectError | ||
| gscal( [ x, alpha ], {} ); // $ExpectError | ||
| } |
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