About stdlib...
We believe in a future in which the web is a preferred environment for numerical computation. To help realize this future, we've built stdlib. stdlib is a standard library, with an emphasis on numerical and scientific computation, written in JavaScript (and C) for execution in browsers and in Node.js.
The library is fully decomposable, being architected in such a way that you can swap out and mix and match APIs and functionality to cater to your exact preferences and use cases.
When you use stdlib, you can be absolutely certain that you are using the most thorough, rigorous, well-written, studied, documented, tested, measured, and high-quality code out there.
To join us in bringing numerical computing to the web, get started by checking us out on GitHub, and please consider financially supporting stdlib. We greatly appreciate your continued support!
Invoke a callback function once for each ndarray element.
npm install @stdlib/ndarray-base-for-each
Alternatively,
- To load the package in a website via a
script
tag without installation and bundlers, use the ES Module available on theesm
branch (see README). - If you are using Deno, visit the
deno
branch (see README for usage intructions). - For use in Observable, or in browser/node environments, use the Universal Module Definition (UMD) build available on the
umd
branch (see README).
The branches.md file summarizes the available branches and displays a diagram illustrating their relationships.
To view installation and usage instructions specific to each branch build, be sure to explicitly navigate to the respective README files on each branch, as linked to above.
var forEach = require( '@stdlib/ndarray-base-for-each' );
Invokes a callback function once for each ndarray element.
var Float64Array = require( '@stdlib/array-float64' );
var naryFunction = require( '@stdlib/utils-nary-function' );
var log = require( '@stdlib/console-log' );
// Create data buffers:
var xbuf = new Float64Array( 12 );
// Define the shape of the array:
var shape = [ 3, 1, 2 ];
// Define the array strides:
var sx = [ 4, 4, 1 ];
// Define the index offset:
var ox = 1;
// Create an ndarray-like object:
var x = {
'dtype': 'float64',
'data': xbuf,
'shape': shape,
'strides': sx,
'offset': ox,
'order': 'row-major'
};
// Apply the callback function:
forEach( [ x ], naryFunction( log, 1 ) );
The function accepts the following arguments:
- arrays: array-like object containing an ndarray.
- fcn: callback to apply.
- thisArg: callback execution context.
The callback function is provided the following arguments:
- value: current array element.
- indices: current array element indices.
- arr: the input ndarray.
-
The provided ndarray should be an
object
with the following properties:- dtype: data type.
- data: data buffer.
- shape: dimensions.
- strides: stride lengths.
- offset: index offset.
- order: specifies whether an ndarray is row-major (C-style) or column major (Fortran-style).
-
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.
var ndarray2array = require( '@stdlib/ndarray-base-to-array' );
var zeroTo = require( '@stdlib/array-base-zero-to' );
var naryFunction = require( '@stdlib/utils-nary-function' );
var log = require( '@stdlib/console-log' );
var forEach = require( '@stdlib/ndarray-base-for-each' );
var x = {
'dtype': 'generic',
'data': zeroTo( 10 ),
'shape': [ 5, 2 ],
'strides': [ -2, 1 ],
'offset': 8,
'order': 'row-major'
};
log( ndarray2array( x.data, x.shape, x.strides, x.offset, x.order ) );
forEach( [ x ], naryFunction( log, 2 ) );
x = {
'dtype': 'generic',
'data': zeroTo( 10 ),
'shape': [ 5, 2 ],
'strides': [ 1, -5 ],
'offset': 5,
'order': 'column-major'
};
log( ndarray2array( x.data, x.shape, x.strides, x.offset, x.order ) );
forEach( [ x ], naryFunction( log, 2 ) );
x = {
'dtype': 'generic',
'data': zeroTo( 18 ),
'shape': [ 2, 3, 3 ],
'strides': [ 9, 3, 1 ],
'offset': 0,
'order': 'row-major'
};
log( ndarray2array( x.data, x.shape, x.strides, x.offset, x.order ) );
forEach( [ x ], naryFunction( log, 2 ) );
x = {
'dtype': 'generic',
'data': zeroTo( 18 ),
'shape': [ 2, 3, 3 ],
'strides': [ -1, -2, -6 ],
'offset': 17,
'order': 'column-major'
};
log( ndarray2array( x.data, x.shape, x.strides, x.offset, x.order ) );
forEach( [ x ], naryFunction( log, 2 ) );
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 © 2016-2024. The Stdlib Authors.