feat: add ndarray/flatten

lib/node_modules/@stdlib/ndarray/flatten/README.md

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+<!--
+
+@license Apache-2.0
+
+Copyright (c) 2025 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.
+
+-->
+
+# flatten
+
+> Return a flattened copy of an input [`ndarray`][@stdlib/ndarray/ctor].
+
+<section class="intro">
+
+</section>
+
+<!-- /.intro -->
+
+<section class="usage">
+
+## Usage
+
+```javascript
+var flatten = require( '@stdlib/ndarray/flatten' );
+```
+
+#### flatten( x, depth )
+
+Returns a flattened copy of an input [`ndarray`][@stdlib/ndarray/ctor].
+
+```javascript
+var array = require( '@stdlib/ndarray/array' );
+var ndarray2array = require( '@stdlib/ndarray/to-array' );
+
+// Create an input ndarray:
+var x = array( [ [ [ 1.0, 2.0 ] ], [ [ 3.0, 4.0 ] ], [ [ 5.0, 6.0 ] ] ] );
+// returns <ndarray>
+
+var y = flatten( x, 2 );
+// returns <ndarray>
+
+var arr = ndarray2array( y );
+// returns [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0 ]
+```
+
+The function accepts the following arguments:
+
+-   **x**: input [`ndarray`][@stdlib/ndarray/ctor].
+-   **depth**: a non-negative integer specifying the number of input [`ndarray`][@stdlib/ndarray/ctor] dimensions to flatten.
+
+</section>
+
+<!-- /.usage -->
+
+<section class="notes">
+
+## Notes
+
+-   The provided input [`ndarray`][@stdlib/ndarray/ctor] **must** have more than one-dimension.
+
+</section>
+
+<!-- /.notes -->
+
+<section class="examples">
+
+## Examples
+
+<!-- eslint no-undef: "error" -->
+
+```javascript
+var discreteUniform = require( '@stdlib/random/array/discrete-uniform' );
+var array = require( '@stdlib/ndarray/array' );
+var ndarray2array = require( '@stdlib/ndarray/to-array' );
+var flatten = require( '@stdlib/ndarray/flatten' );
+
+var xbuf = discreteUniform( 12, -100, 100, {
+    'dtype': 'generic'
+});
+
+// Create an input ndarray:
+var x = array( xbuf, {
+    'shape': [ 2, 2, 3 ],
+    'dtype': 'generic'
+});
+console.log( ndarray2array( x ) );
+
+// Flatten the input ndarray:
+var y = flatten( x, 2 );
+console.log( ndarray2array( y ) );
+```
+
+</section>
+
+<!-- /.examples -->
+
+<!-- Section for related `stdlib` packages. Do not manually edit this section, as it is automatically populated. -->
+
+<section class="related">
+
+</section>
+
+<!-- /.related -->
+
+<section class="links">
+
+[@stdlib/ndarray/ctor]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/ctor
+
+<!-- <related-links> -->
+
+<!-- </related-links> -->
+
+</section>
+
+<!-- /.links -->

lib/node_modules/@stdlib/ndarray/flatten/benchmark/benchmark.js

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+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2025 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 isndarrayLike = require( '@stdlib/assert/is-ndarray-like' );
+var zeros = require( '@stdlib/ndarray/base/zeros' );
+var pkg = require( './../package.json' ).name;
+var flatten = require( './../lib' );
+
+
+// MAIN //
+
+bench( pkg+'::2d', function benchmark( b ) {
+	var values;
+	var y;
+	var i;
+	var j;
+
+	values = [
+		zeros( 'float64', [ 2, 2 ], 'row-major' ),
+		zeros( 'float32', [ 2, 2 ], 'row-major' ),
+		zeros( 'int32', [ 2, 2 ], 'row-major' ),
+		zeros( 'complex128', [ 2, 2 ], 'row-major' ),
+		zeros( 'generic', [ 2, 2 ], 'row-major' )
+	];
+
+	b.tic();
+	for ( i = 0; i < b.iterations; i++ ) {
+		j = i % values.length;
+		y = flatten( values[ j ], 1 );
+		if ( typeof y !== 'object' ) {
+			b.fail( 'should return an ndarray' );
+		}
+	}
+	b.toc();
+	if ( !isndarrayLike( y ) ) {
+		b.fail( 'should return an ndarray' );
+	}
+	b.pass( 'benchmark finished' );
+	b.end();
+});
+
+bench( pkg+'::3d', function benchmark( b ) {
+	var values;
+	var y;
+	var i;
+	var j;
+
+	values = [
+		zeros( 'float64', [ 2, 2, 2 ], 'row-major' ),
+		zeros( 'float32', [ 2, 2, 2 ], 'row-major' ),
+		zeros( 'int32', [ 2, 2, 2 ], 'row-major' ),
+		zeros( 'complex128', [ 2, 2, 2 ], 'row-major' ),
+		zeros( 'generic', [ 2, 2, 2 ], 'row-major' )
+	];
+
+	b.tic();
+	for ( i = 0; i < b.iterations; i++ ) {
+		j = i % values.length;
+		y = flatten( values[ j ], 2 );
+		if ( typeof y !== 'object' ) {
+			b.fail( 'should return an ndarray' );
+		}
+	}
+	b.toc();
+	if ( !isndarrayLike( y ) ) {
+		b.fail( 'should return an ndarray' );
+	}
+	b.pass( 'benchmark finished' );
+	b.end();
+});
+
+bench( pkg+'::4d', function benchmark( b ) {
+	var values;
+	var y;
+	var i;
+	var j;
+
+	values = [
+		zeros( 'float64', [ 2, 2, 2, 2 ], 'row-major' ),
+		zeros( 'float32', [ 2, 2, 2, 2 ], 'row-major' ),
+		zeros( 'int32', [ 2, 2, 2, 2 ], 'row-major' ),
+		zeros( 'complex128', [ 2, 2, 2, 2 ], 'row-major' ),
+		zeros( 'generic', [ 2, 2, 2, 2 ], 'row-major' )
+	];
+
+	b.tic();
+	for ( i = 0; i < b.iterations; i++ ) {
+		j = i % values.length;
+		y = flatten( values[ j ], 3 );
+		if ( typeof y !== 'object' ) {
+			b.fail( 'should return an ndarray' );
+		}
+	}
+	b.toc();
+	if ( !isndarrayLike( y ) ) {
+		b.fail( 'should return an ndarray' );
+	}
+	b.pass( 'benchmark finished' );
+	b.end();
+});
+
+bench( pkg+'::5d', function benchmark( b ) {
+	var values;
+	var y;
+	var i;
+	var j;
+
+	values = [
+		zeros( 'float64', [ 2, 2, 2, 2, 2 ], 'row-major' ),
+		zeros( 'float32', [ 2, 2, 2, 2, 2 ], 'row-major' ),
+		zeros( 'int32', [ 2, 2, 2, 2, 2 ], 'row-major' ),
+		zeros( 'complex128', [ 2, 2, 2, 2, 2 ], 'row-major' ),
+		zeros( 'generic', [ 2, 2, 2, 2, 2 ], 'row-major' )
+	];
+
+	b.tic();
+	for ( i = 0; i < b.iterations; i++ ) {
+		j = i % values.length;
+		y = flatten( values[ j ], 4 );
+		if ( typeof y !== 'object' ) {
+			b.fail( 'should return an ndarray' );
+		}
+	}
+	b.toc();
+	if ( !isndarrayLike( y ) ) {
+		b.fail( 'should return an ndarray' );
+	}
+	b.pass( 'benchmark finished' );
+	b.end();
+});

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

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