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feat: add ndarray/some
PR-URL: #8514 Closes: stdlib-js/metr-issue-tracker#83 Ref: #2656 Co-authored-by: Athan Reines <kgryte@gmail.com> Reviewed-by: Athan Reines <kgryte@gmail.com>
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‎lib/node_modules/@stdlib/ndarray/some/README.md‎

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<!--
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@license Apache-2.0
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Copyright (c) 2025 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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# some
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> Test whether at least `n` elements along one or more [`ndarray`][@stdlib/ndarray/ctor] dimensions are truthy.
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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 some = require( '@stdlib/ndarray/some' );
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```
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#### some( x, n\[, options] )
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Tests whether at least `n` elements along one or more [`ndarray`][@stdlib/ndarray/ctor] dimensions are truthy.
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```javascript
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var array = require( '@stdlib/ndarray/array' );
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// Create an input ndarray:
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var x = array( [ [ [ 1.0, 0.0 ] ], [ [ 3.0, 4.0 ] ], [ [ 0.0, 6.0 ] ] ] );
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// returns <ndarray>
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// Perform reduction:
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var out = some( x, 3 );
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// returns <ndarray>
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var v= out.get();
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// returns true
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```
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The function accepts the following arguments:
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- **x**: input [`ndarray`][@stdlib/ndarray/ctor].
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- **n**: number of elements which must be truthy. May be either a scalar or an [`ndarray`][@stdlib/ndarray/ctor]. Must be [broadcast-compatible][@stdlib/ndarray/base/broadcast-shapes] with the non-reduced dimensions of input [`ndarray`][@stdlib/ndarray/ctor]. Must have an integer [data type][@stdlib/ndarray/dtypes].
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- **options**: function options (_optional_).
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The function accepts the following options:
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- **dims**: list of dimensions over which to perform a reduction.
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- **keepdims**: boolean indicating whether the reduced dimensions should be included in the returned [`ndarray`][@stdlib/ndarray/ctor] as singleton dimensions. Default: `false`.
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By default, the function performs a reduction over all elements in a provided [`ndarray`][@stdlib/ndarray/ctor]. To reduce specific dimensions, set the `dims` option.
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```javascript
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var array = require( '@stdlib/ndarray/array' );
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var ndarray2array = require( '@stdlib/ndarray/to-array' );
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// Create an input ndarray:
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var x = array( [ [ [ 1.0, 0.0 ] ], [ [ 3.0, 4.0 ] ], [ [ 0.0, 6.0 ] ] ] );
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// returns <ndarray>
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var opts = {
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'dims': [ 0, 1 ]
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};
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// Perform reduction:
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var out = some( x, 2, opts );
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// returns <ndarray>
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var v = ndarray2array( out );
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// returns [ true, true ]
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```
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By default, the function returns an [`ndarray`][@stdlib/ndarray/ctor] having a shape matching only the non-reduced dimensions of the input [`ndarray`][@stdlib/ndarray/ctor] (i.e., the reduced dimensions are dropped). To include the reduced dimensions as singleton dimensions in the output [`ndarray`][@stdlib/ndarray/ctor], set the `keepdims` option to `true`.
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```javascript
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var array = require( '@stdlib/ndarray/array' );
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var ndarray2array = require( '@stdlib/ndarray/to-array' );
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// Create an input ndarray:
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var x = array( [ [ [ 1.0, 0.0 ] ], [ [ 3.0, 4.0 ] ], [ [ 0.0, 6.0 ] ] ] );
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// returns <ndarray>
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var opts = {
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'dims': [ 0, 1 ],
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'keepdims': true
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};
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// Perform reduction:
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var out = some( x, 2, opts );
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// returns <ndarray>
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var v = ndarray2array( out );
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// returns [ [ [ true, true ] ] ]
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```
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#### some.assign( x, n, out\[, options] )
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Tests whether at least `n` elements along one or more [`ndarray`][@stdlib/ndarray/ctor] dimensions are truthy and assigns the results to an output [`ndarray`][@stdlib/ndarray/ctor].
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```javascript
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var array = require( '@stdlib/ndarray/array' );
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var empty = require( '@stdlib/ndarray/empty' );
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// Create an input ndarray:
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var x = array( [ [ [ 1.0, 0.0 ] ], [ [ 3.0, 4.0 ] ], [ [ 0.0, 6.0 ] ] ] );
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// returns <ndarray>
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// Create an output ndarray:
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var y = empty( [], {
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'dtype': 'bool'
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});
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// Perform reduction:
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var out = some.assign( x, 3, y );
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// returns <ndarray>
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var bool = ( out === y );
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// returns true
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var v = y.get();
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// returns true
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```
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The function accepts the following arguments:
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- **x**: input [`ndarray`][@stdlib/ndarray/ctor].
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- **n**: number of elements which must be truthy. May be either a scalar or an [`ndarray`][@stdlib/ndarray/ctor]. Must be [broadcast-compatible][@stdlib/ndarray/base/broadcast-shapes] with the non-reduced dimensions of input [`ndarray`][@stdlib/ndarray/ctor]. Must have an integer [data type][@stdlib/ndarray/dtypes].
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- **out**: output [`ndarray`][@stdlib/ndarray/ctor]. The output [`ndarray`][@stdlib/ndarray/ctor] must have a shape matching the non-reduced dimensions of the input [`ndarray`][@stdlib/ndarray/ctor].
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- **options**: function options (_optional_).
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The function accepts the following `options`:
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- **dims**: list of dimensions over which to perform a reduction.
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By default, the function performs a reduction over all elements in a provided [`ndarray`][@stdlib/ndarray/ctor]. To reduce specific dimensions, set the `dims` option.
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```javascript
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var array = require( '@stdlib/ndarray/array' );
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var empty = require( '@stdlib/ndarray/empty' );
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var ndarray2array = require( '@stdlib/ndarray/to-array' );
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// Create an input ndarray:
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var x = array( [ [ [ 1.0, 0.0 ] ], [ [ 3.0, 4.0 ] ], [ [ 0.0, 6.0 ] ] ] );
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// returns <ndarray>
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// Create an output ndarray:
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var y = empty( [ 2 ], {
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'dtype': 'bool'
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});
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var opts = {
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'dims': [ 0, 1 ]
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};
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// Perform reduction:
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var out = some.assign( x, 2, y, opts );
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// returns <ndarray>
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var bool = ( out === y );
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// returns true
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var v = ndarray2array( out );
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// returns [ true, true ]
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```
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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/base/discrete-uniform' ).factory;
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var ndarray2array = require( '@stdlib/ndarray/to-array' );
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var scalar2ndarray = require( '@stdlib/ndarray/from-scalar' );
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var fillBy = require( '@stdlib/ndarray/fill-by' );
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var zeros = require( '@stdlib/ndarray/zeros' );
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var some = require( '@stdlib/ndarray/some' );
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var x = zeros( [ 2, 4, 5 ], {
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'dtype': 'float64'
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});
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x = fillBy( x, discreteUniform( 0, 10 ) );
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console.log( ndarray2array( x ) );
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var n = scalar2ndarray( 4, {
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'dtype': 'int8'
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});
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var y = some( x, n );
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console.log( y.get() );
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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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[@stdlib/ndarray/ctor]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/ctor
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[@stdlib/ndarray/dtypes]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/dtypes
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[@stdlib/ndarray/base/broadcast-shapes]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/base/broadcast-shapes
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</section>
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<!-- /.links -->

‎lib/node_modules/@stdlib/ndarray/some/benchmark/benchmark.1d.js‎

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/**
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* @license Apache-2.0
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*
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* Copyright (c) 2025 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 isndarrayLike = require( '@stdlib/assert/is-ndarray-like' );
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var pow = require( '@stdlib/math/base/special/pow' );
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var discreteUniform = require( '@stdlib/random/array/discrete-uniform' );
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var shape2strides = require( '@stdlib/ndarray/base/shape2strides' );
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var ndarray = require( '@stdlib/ndarray/ctor' );
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var pkg = require( './../package.json' ).name;
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var some = require( './../lib' );
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// VARIABLES //
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var types = [ 'float64' ];
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var orders = [ 'row-major', 'column-major' ];
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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 - ndarray length
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* @param {NonNegativeIntegerArray} shape - ndarray shape
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* @param {string} xtype - ndarray data type
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* @param {string} order - memory layout
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* @param {NonNegativeIntegerArray} dims - list of dimensions to reduce
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* @returns {Function} benchmark function
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*/
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function createBenchmark( len, shape, xtype, order, dims ) {
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var x;
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x = discreteUniform( len, 0, 10 );
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x = new ndarray( xtype, x, shape, shape2strides( shape, order ), 0, order );
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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 opts;
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var out;
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var i;
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opts = {
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'dims': dims
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};
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b.tic();
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for ( i = 0; i < b.iterations; i++ ) {
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out = some( x, len, opts );
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if ( typeof out !== '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 ( !isndarrayLike( out ) ) {
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b.fail( 'should return an ndarray' );
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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 dims;
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var len;
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var min;
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var max;
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var ord;
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var sh;
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var t1;
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var f;
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var i;
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var j;
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var k;
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var n;
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var d;
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min = 1; // 10^min
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max = 6; // 10^max
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d = [
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[ 0 ],
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[]
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];
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for ( n = 0; n < d.length; n++ ) {
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dims = d[ n ];
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for ( k = 0; k < orders.length; k++ ) {
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ord = orders[ k ];
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for ( j = 0; j < types.length; j++ ) {
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t1 = types[ j ];
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for ( i = min; i <= max; i++ ) {
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len = pow( 10, i );
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sh = [ len ];
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f = createBenchmark( len, sh, t1, ord, dims );
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bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+ord+',xtype='+t1+',dims=['+dims.join(',')+']', f );
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}
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}
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}
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}
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}
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main();

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