feat: add ndarray/for-each

lib/node_modules/@stdlib/ndarray/for-each/README.md

@@ -0,0 +1,164 @@
+<!--
+
+@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.
+
+-->
+
+# forEach
+
+> Invoke a callback function once for each [ndarray][@stdlib/ndarray/ctor] element.
+
+<section class="intro">
+
+</section>
+
+<!-- /.intro -->
+
+<section class="usage">
+
+## Usage
+
+```javascript
+var forEach = require( '@stdlib/ndarray/for-each' );
+```
+
+#### forEach( x, fcn\[, thisArg] )
+
+Invokes a callback function once for each [ndarray][@stdlib/ndarray/ctor] element.
+
+<!-- eslint-disable max-len -->
+
+```javascript
+var Float64Array = require( '@stdlib/array/float64' );
+var ndarray = require( '@stdlib/ndarray/ctor' );
+var naryFunction = require( '@stdlib/utils/nary-function' );
+var log = require( '@stdlib/console/log' );
+
+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>
+
+forEach( x, naryFunction( log, 1 ) );
+```
+
+The function accepts the following arguments:
+
+-   **x**: input [ndarray][@stdlib/ndarray/ctor].
+-   **fcn**: callback to apply.
+-   **thisArg**: callback execution context _(optional)_.
+
+To set the callback function execution context, provide a `thisArg`.
+
+<!-- eslint-disable no-invalid-this, max-len -->
+
+```javascript
+var Float64Array = require( '@stdlib/array/float64' );
+var ndarray = require( '@stdlib/ndarray/ctor' );
+
+function accumulate( z ) {
+    this.sum += z;
+}
+
+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 ctx = {
+    'sum': 0
+};
+
+forEach( x, accumulate, ctx );
+var sum = ctx.sum;
+// returns 36
+```
+
+The callback function is provided the following arguments:
+
+-   **value**: current array element.
+-   **indices**: current array element indices.
+-   **arr**: the input [ndarray][@stdlib/ndarray/ctor].
+
+</section>
+
+<!-- /.usage -->
+
+<section class="notes">
+
+## Notes
+
+-   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 ndarray = require( '@stdlib/ndarray/ctor' );
+var ndarray2array = require( '@stdlib/ndarray/to-array' );
+var naryFunction = require( '@stdlib/utils/nary-function' );
+var log = require( '@stdlib/console/log' );
+var forEach = require( '@stdlib/ndarray/for-each' );
+
+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' );
+
+log( ndarray2array( x ) );
+forEach( x, naryFunction( log, 2 ) );
+```
+
+</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/for-each/benchmark/benchmark.1d.js

@@ -0,0 +1,140 @@
+/**
+* @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 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 forEach = require( './../lib' );
+
+
+// VARIABLES //
+
+var xtypes = [ 'generic' ];
+var orders = [ 'row-major', 'column-major' ];
+
+
+// FUNCTIONS //
+
+/**
+* Callback invoked for each ndarray element.
+*
+* @private
+* @param {number} value - array element
+* @throws {Error} unexpected error
+*/
+function fcn( value ) {
+	if ( isnan( value ) ) {
+		throw new Error( 'unexpected error' );
+	}
+}
+
+/**
+* Creates a benchmark function.
+*
+* @private
+* @param {PositiveInteger} len - array length
+* @param {NonNegativeIntegerArray} shape - ndarray shape
+* @param {string} xtype - input ndarray data type
+* @param {string} order - ndarray memory layout
+* @returns {Function} benchmark function
+*/
+function createBenchmark( len, shape, xtype, order ) {
+	var strides;
+	var xbuf;
+	var x;
+
+	xbuf = discreteUniform( len, -100, 100, {
+		'dtype': xtype
+	});
+	strides = shape2strides( shape, order );
+	x = ndarray( xtype, xbuf, shape, strides, 0, order );
+
+	return benchmark;
+
+	/**
+	* Benchmark function.
+	*
+	* @private
+	* @param {Benchmark} b - benchmark instance
+	*/
+	function benchmark( b ) {
+		var i;
+
+		b.tic();
+		for ( i = 0; i < b.iterations; i++ ) {
+			forEach( x, fcn );
+			if ( isnan( x.data[ i%len ] ) ) {
+				b.fail( 'should not return NaN' );
+			}
+		}
+		b.toc();
+		if ( isnan( x.data[ i%len ] ) ) {
+			b.fail( 'should not return NaN' );
+		}
+		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 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 ];
+			for ( i = min; i <= max; i++ ) {
+				len = pow( 10, i );
+
+				sh = [ len ];
+				f = createBenchmark( len, sh, t1, ord );
+				bench( pkg+':ndims='+sh.length+',len='+len+',shape=['+sh.join(',')+'],xorder='+ord+',xtype='+t1, f );
+			}
+		}
+	}
+}
+
+main();