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feat: add ndarra/flatten
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‎lib/node_modules/@stdlib/ndarray/flatten/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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# flatten
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> Return a flattened copy of an input [`ndarray`][@stdlib/ndarray/ctor].
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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 flatten = require( '@stdlib/ndarray/flatten' );
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```
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#### flatten( x, depth )
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Returns a flattened copy of an input [`ndarray`][@stdlib/ndarray/ctor].
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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, 2.0 ] ], [ [ 3.0, 4.0 ] ], [ [ 5.0, 6.0 ] ] ] );
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// returns <ndarray>
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var y = flatten( x, 2 );
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// returns <ndarray>
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var arr = ndarray2array( y );
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// returns [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ]
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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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- **depth**: a non-negative integer specifying the number of input [`ndarray`][@stdlib/ndarray/ctor] dimensions to flatten.
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</section>
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<!-- /.usage -->
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<section class="notes">
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## Notes
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- The provided input [`ndarray`][@stdlib/ndarray/ctor] **must** have more than one-dimension.
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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/array/discrete-uniform' );
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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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var flatten = require( '@stdlib/ndarray/flatten' );
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var xbuf = discreteUniform( 12, -100, 100, {
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'dtype': 'generic'
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});
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// Create an input ndarray:
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var x = array( xbuf, {
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'shape': [ 2, 2, 3 ],
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'dtype': 'generic'
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});
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console.log( ndarray2array( x ) );
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// Flatten the input ndarray:
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var y = flatten( x, 2 );
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console.log( ndarray2array( y ) );
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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 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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<!-- <related-links> -->
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<!-- </related-links> -->
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</section>
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<!-- /.links -->

‎lib/node_modules/@stdlib/ndarray/flatten/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) 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 zeros = require( '@stdlib/ndarray/zeros' );
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var pkg = require( './../package.json' ).name;
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var flatten = require( './../lib' );
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// MAIN //
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bench( pkg+'::2d', function benchmark( b ) {
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var values;
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var y;
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var i;
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var j;
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values = [
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zeros( 'float64', [ 2, 2 ], 'row-major' ),
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zeros( 'float32', [ 2, 2 ], 'row-major' ),
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zeros( 'int32', [ 2, 2 ], 'row-major' ),
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zeros( 'complex128', [ 2, 2 ], 'row-major' ),
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zeros( 'generic', [ 2, 2 ], 'row-major' )
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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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j = i % values.length;
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y = flatten( values[ j ], 1 );
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if ( typeof y !== '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( y ) ) {
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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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bench( pkg+'::3d', function benchmark( b ) {
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var values;
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var y;
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var i;
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var j;
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values = [
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zeros( 'float64', [ 2, 2, 2 ], 'row-major' ),
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zeros( 'float32', [ 2, 2, 2 ], 'row-major' ),
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zeros( 'int32', [ 2, 2, 2 ], 'row-major' ),
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zeros( 'complex128', [ 2, 2, 2 ], 'row-major' ),
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zeros( 'generic', [ 2, 2, 2 ], 'row-major' )
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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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j = i % values.length;
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y = flatten( values[ j ], 2 );
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if ( typeof y !== '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( y ) ) {
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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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bench( pkg+'::4d', function benchmark( b ) {
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var values;
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var y;
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var i;
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var j;
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values = [
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zeros( 'float64', [ 2, 2, 2, 2 ], 'row-major' ),
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zeros( 'float32', [ 2, 2, 2, 2 ], 'row-major' ),
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zeros( 'int32', [ 2, 2, 2, 2 ], 'row-major' ),
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zeros( 'complex128', [ 2, 2, 2, 2 ], 'row-major' ),
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zeros( 'generic', [ 2, 2, 2, 2 ], 'row-major' )
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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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j = i % values.length;
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y = flatten( values[ j ], 3 );
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if ( typeof y !== '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( y ) ) {
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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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bench( pkg+'::5d', function benchmark( b ) {
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var values;
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var y;
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var i;
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var j;
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values = [
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zeros( 'float64', [ 2, 2, 2, 2, 2 ], 'row-major' ),
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zeros( 'float32', [ 2, 2, 2, 2, 2 ], 'row-major' ),
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zeros( 'int32', [ 2, 2, 2, 2, 2 ], 'row-major' ),
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zeros( 'complex128', [ 2, 2, 2, 2, 2 ], 'row-major' ),
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zeros( 'generic', [ 2, 2, 2, 2, 2 ], 'row-major' )
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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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j = i % values.length;
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y = flatten( values[ j ], 4 );
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if ( typeof y !== '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( y ) ) {
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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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});

‎lib/node_modules/@stdlib/ndarray/flatten/docs/repl.txt‎

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{{alias}}( x, depth )
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Returns a flattened copy of an input ndarray.
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The `depth` must be a valid non-negative integer.
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Parameters
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----------
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x: ndarray
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Input ndarray.
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depth: integer
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A non-negative integer specifying the number of input ndarray dimensions
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to flatten.
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Returns
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-------
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out: ndarray
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Output ndarray.
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Examples
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--------
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> var x = {{alias:@stdlib/ndarray/array}}( [ [ 1.0, 2.0 ], [ 3.0, 4.0 ] ] );
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> var y = {{alias}}( x, 1 );
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> var arr = {{alias:@stdlib/ndarray/to-array}}( y )
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[ 1.0, 2.0, 3.0, 4.0 ]
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See Also
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--------
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