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Invoke a callback function once for each ndarray element.
To use in Observable,
forEach = require( 'https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-for-each@umd/browser.js' )To vendor stdlib functionality and avoid installing dependency trees for Node.js, you can use the UMD server build:
var forEach = require( 'path/to/vendor/umd/ndarray-for-each/index.js' )To include the bundle in a webpage,
<script type="text/javascript" src="https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-for-each@umd/browser.js"></script>If no recognized module system is present, access bundle contents via the global scope:
<script type="text/javascript">
(function () {
window.forEach;
})();
</script>Invokes a callback function once for each ndarray element.
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.
- fcn: callback to apply.
- thisArg: callback execution context (optional).
To set the callback function execution context, provide a thisArg.
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 36The callback function is provided the following arguments:
- value: current array element.
- indices: current array element indices.
- arr: the input 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.
<!DOCTYPE html>
<html lang="en">
<body>
<script type="text/javascript" src="https://cdn.jsdelivr.net/gh/stdlib-js/random-array-discrete-uniform@umd/browser.js"></script>
<script type="text/javascript" src="https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-ctor@umd/browser.js"></script>
<script type="text/javascript" src="https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-to-array@umd/browser.js"></script>
<script type="text/javascript" src="https://cdn.jsdelivr.net/gh/stdlib-js/utils-nary-function@umd/browser.js"></script>
<script type="text/javascript" src="https://cdn.jsdelivr.net/gh/stdlib-js/console-log@umd/browser.js"></script>
<script type="text/javascript" src="https://cdn.jsdelivr.net/gh/stdlib-js/ndarray-for-each@umd/browser.js"></script>
<script type="text/javascript">
(function () {
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 ) );
})();
</script>
</body>
</html>@stdlib/ndarray-map: apply a callback to elements in an input ndarray and assign results to elements in a new output ndarray.
This package is part of stdlib, a standard library for JavaScript and Node.js, with an emphasis on numerical and scientific computing. The library provides a collection of robust, high performance libraries for mathematics, statistics, streams, utilities, and more.
For more information on the project, filing bug reports and feature requests, and guidance on how to develop stdlib, see the main project repository.
See LICENSE.
Copyright © 2016-2025. The Stdlib Authors.
