feat: add ndarray/map

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

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+<!--
+
+@license Apache-2.0
+
+Copyright (c) 2024 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.
+
+-->
+
+# map
+
+> Apply a callback function to elements in an input [ndarray][@stdlib/ndarray/ctor] and assign results to elements in a new output [ndarray][@stdlib/ndarray/ctor].
+
+<section class="intro">
+
+</section>
+
+<!-- /.intro -->
+
+<section class="usage">
+
+## Usage
+
+```javascript
+var map = require( '@stdlib/ndarray/map' );
+```
+
+#### map( x\[, options], fcn\[, thisArg] )
+
+Applies a callback function to elements in an input [ndarray][@stdlib/ndarray/ctor] and assigns results to elements in a new output [ndarray][@stdlib/ndarray/ctor].
+
+<!-- eslint-disable max-len -->
+
+```javascript
+var Float64Array = require( '@stdlib/array/float64' );
+var ndarray = require( '@stdlib/ndarray/ctor' );
+var ndarray2array = require( '@stdlib/ndarray/to-array' );
+
+function scale( z ) {
+    return z * 10.0;
+}
+
+var buffer = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );
+var shape = [ 2, 3 ];
+var strides = [ 6, 1 ];
+var offset = 1;
+
+var x = ndarray( 'float64', buffer, shape, strides, offset, 'row-major' );
+// returns <ndarray>
+
+var y = map( x, scale );
+// returns <ndarray>
+
+var arr = ndarray2array( y );
+// returns [ [ 20.0, 30.0, 40.0 ], [ 80.0, 90.0, 100.0 ] ]
+```
+
+The function accepts the following arguments:
+
+-   **x**: input [ndarray][@stdlib/ndarray/ctor].
+-   **options**: function options.
+-   **fcn**: callback to apply.
+-   **thisArg**: callback execution context.
+
+The function accepts the following options:
+
+-   **dtype**: output ndarray [data type][@stdlib/ndarray/dtypes]. If not specified, the output ndarray [data type][@stdlib/ndarray/dtypes] is inferred from the input [ndarray][@stdlib/ndarray/ctor].
+
+By default, the output ndarray [data type][@stdlib/ndarray/dtypes] is inferred from the input [ndarray][@stdlib/ndarray/ctor]. To return an ndarray with a different [data type][@stdlib/ndarray/dtypes], specify the `dtype` option.
+
+<!-- eslint-disable max-len -->
+
+```javascript
+var Float64Array = require( '@stdlib/array/float64' );
+var ndarray = require( '@stdlib/ndarray/ctor' );
+var dtype = require( '@stdlib/ndarray/dtype' );
+var ndarray2array = require( '@stdlib/ndarray/to-array' );
+
+function scale( z ) {
+    return z * 10.0;
+}
+
+var buffer = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );
+var shape = [ 2, 3 ];
+var strides = [ 6, 1 ];
+var offset = 1;
+
+var x = ndarray( 'float64', buffer, shape, strides, offset, 'row-major' );
+// returns <ndarray>
+
+var opts = {
+    'dtype': 'float32'
+};
+var y = map( x, opts, scale );
+// returns <ndarray>
+
+var dt = dtype( y );
+// returns 'float32'
+
+var arr = ndarray2array( y );
+// returns [ [ 20.0, 30.0, 40.0 ], [ 80.0, 90.0, 100.0 ] ]
+```
+
+The callback function is provided the following arguments:
+
+-   **values**: current array element.
+-   **indices**: current array element indices.
+-   **arr**: the input [ndarray][@stdlib/ndarray/ctor].
+
+</section>
+
+<!-- /.usage -->
+
+<section class="notes">
+
+## Notes
+
+-   The function does **not** perform explicit casting (e.g., from a real-valued floating-point number to a complex floating-point number). Any such casting should be performed by a provided callback function.
+
+    <!-- eslint-disable max-len -->
+
+    ```javascript
+    var Float64Array = require( '@stdlib/array/float64' );
+    var ndarray = require( '@stdlib/ndarray/ctor' );
+    var Complex128 = require( '@stdlib/complex/float64/ctor' );
+    var ndarray2array = require( '@stdlib/ndarray/to-array' );
+
+    function toComplex( z ) {
+        return new Complex128( z, 0.0 );
+    }
+
+    var buffer = new Float64Array( [ 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0, 12.0 ] );
+    var shape = [ 2, 3 ];
+    var strides = [ 6, 1 ];
+    var offset = 1;
+
+    var x = ndarray( 'float64', buffer, shape, strides, offset, 'row-major' );
+    // returns <ndarray>
+
+    var opts = {
+        'dtype': 'complex128'
+    };
+    var y = map( x, opts, toComplex );
+    // returns <ndarray>
+    ```
+
+-   For very high-dimensional ndarrays which are non-contiguous, one should consider copying the underlying data to contiguous memory before applying a callback function in order to achieve better performance.
+
+</section>
+
+<!-- /.notes -->
+
+<section class="examples">
+
+## Examples
+
+<!-- eslint no-undef: "error" -->
+
+```javascript
+var discreteUniform = require( '@stdlib/random/array/discrete-uniform' );
+var abs = require( '@stdlib/math/base/special/abs' );
+var ndarray2array = require( '@stdlib/ndarray/to-array' );
+var naryFunction = require( '@stdlib/utils/nary-function' );
+var ndarray = require( '@stdlib/ndarray/ctor' );
+var map = require( '@stdlib/ndarray/map' );
+
+var buffer = discreteUniform( 10, -100, 100, {
+    'dtype': 'generic'
+});
+var shape = [ 5, 2 ];
+var strides = [ 2, 1 ];
+var offset = 0;
+var x = ndarray( 'generic', buffer, shape, strides, offset, 'row-major' );
+console.log( ndarray2array( x ) );
+
+var y = map( x, naryFunction( abs, 1 ) );
+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
+
+[@stdlib/ndarray/dtypes]: https://github.com/stdlib-js/stdlib/tree/develop/lib/node_modules/%40stdlib/ndarray/dtypes
+
+<!-- <related-links> -->
+
+<!-- </related-links> -->
+
+</section>
+
+<!-- /.links -->

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

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+/**
+* @license Apache-2.0
+*
+* Copyright (c) 2024 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 isnan = require( '@stdlib/math/base/assert/is-nan' );
+var pow = require( '@stdlib/math/base/special/pow' );
+var isndarrayLike = require( '@stdlib/assert/is-ndarray-like' );
+var identity = require( '@stdlib/math/base/special/identity' );
+var discreteUniform = require( '@stdlib/random/array/discrete-uniform' );
+var shape2strides = require( '@stdlib/ndarray/base/shape2strides' );
+var ndarray = require( '@stdlib/ndarray/ctor' );
+var pkg = require( './../package.json' ).name;
+var map = require( './../lib' );
+
+
+// VARIABLES //
+
+var xtypes = [ 'generic' ];
+var ytypes = [ 'float64' ];
+var orders = [ 'row-major', 'column-major' ];
+
+
+// FUNCTIONS //
+
+/**
+* Creates a benchmark function.
+*
+* @private
+* @param {PositiveInteger} len - array length
+* @param {NonNegativeIntegerArray} shape - ndarray shape
+* @param {string} xtype - input ndarray data type
+* @param {string} ytype - output ndarray data type
+* @param {string} order - ndarray memory layout
+* @returns {Function} benchmark function
+*/
+function createBenchmark( len, shape, xtype, ytype, order ) {
+	var strides;
+	var opts;
+	var xbuf;
+	var x;
+
+	xbuf = discreteUniform( len, -100, 100, {
+		'dtype': xtype
+	});
+	strides = shape2strides( shape, order );
+	x = ndarray( xtype, xbuf, shape, strides, 0, order );
+	opts = {
+		'dtype': ytype
+	};
+
+	return benchmark;
+
+	/**
+	* Benchmark function.
+	*
+	* @private
+	* @param {Benchmark} b - benchmark instance
+	*/
+	function benchmark( b ) {
+		var y;
+		var i;
+
+		b.tic();
+		for ( i = 0; i < b.iterations; i++ ) {
+			y = map( x, opts, identity );
+			if ( isnan( y.data[ i%len ] ) ) {
+				b.fail( 'should not return NaN' );
+			}
+		}
+		b.toc();
+		if ( !isndarrayLike( y ) ) {
+			b.fail( 'should return an ndarray' );
+		}
+		b.pass( 'benchmark finished' );
+		b.end();
+	}
+}
+
+
+// MAIN //
+
+/**
+* Main execution sequence.
+*
+* @private
+*/
+function main() {
+	var len;
+	var min;
+	var max;
+	var ord;
+	var sh;
+	var t1;
+	var t2;
+	var f;
+	var i;
+	var j;
+	var k;
+
+	min = 1; // 10^min
+	max = 6; // 10^max
+
+	for ( k = 0; k < orders.length; k++ ) {
+		ord = orders[ k ];
+		for ( j = 0; j < xtypes.length; j++ ) {
+			t1 = xtypes[ j ];
+			t2 = ytypes[ j ];
+			for ( i = min; i <= max; i++ ) {
+				len = pow( 10, i );
+
+				sh = [ len ];
+				f = createBenchmark( len, sh, t1, t2, ord );
+				bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+ord+',yorder='+ord+',xtype='+t1+',ytype='+t2, f );
+			}
+		}
+	}
+}
+
+main();