Package Exports
- @stdlib/array-base-mskreject-map
- @stdlib/array-base-mskreject-map/dist
- @stdlib/array-base-mskreject-map/dist/index.js
- @stdlib/array-base-mskreject-map/lib/index.js
This package does not declare an exports field, so the exports above have been automatically detected and optimized by JSPM instead. If any package subpath is missing, it is recommended to post an issue to the original package (@stdlib/array-base-mskreject-map) to support the "exports" field. If that is not possible, create a JSPM override to customize the exports field for this package.
Readme
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!
mskrejectMap
Apply a mask to a provided input array and map the unmasked values according to a callback function.
Installation
npm install @stdlib/array-base-mskreject-mapUsage
var mskrejectMap = require( '@stdlib/array-base-mskreject-map' );mskrejectMap( x, mask, clbk[, thisArg ] )
Returns a new array by applying a mask and mapping the unmasked values according to a callback function.
var x = [ 1, 2, 3, 4 ];
function clbk( val ) {
return val * 2;
}
var y = mskrejectMap( x, [ 0, 1, 0, 1 ], clbk );
// returns [ 2, 6 ]The function supports the following parameters:
- x: input array.
- mask: mask array.
- clbk: function to apply.
- thisArg: applied function execution context (optional).
The clbk function is provided three arguments:
- value: current unmasked array element.
- index: current unmasked array element index.
- arr: input array.
To set the clbk function execution context, provide a thisArg.
var x = [ 1, 2, 3, 4 ];
var mask = [ 0, 1, 0, 1 ];
var increase = 3;
function clbk( value ) {
return value + this;
}
var out = mskrejectMap( x, mask, clbk, increase );
// returns [ 4, 6 ]The function always returns a new "generic" array.
mskrejectMap.assign( x, mask, out, stride, offset, clbk[, thisArg ] )
Applies a mask to a provided input array, maps the unmasked values according to a callback function, and assigns to elements in a provided output array.
var x = [ 1, 2, 3, 4 ];
var mask = [ 1, 0, 1, 0 ];
var out = [ 0, 0, 0, 0 ];
function clbk( val ) {
return val * 2;
}
var arr = mskrejectMap.assign( x, mask, out, -2, out.length-1, clbk );
// returns [ 0, 8, 0, 4 ]
var bool = ( arr === out );
// returns trueThe function supports the following parameters:
- x: input array.
- mask: mask array.
- out: output array.
- stride: output array stride.
- offset: output array offset.
- clbk: function to apply.
- thisArg: applied function execution context (optional).
Notes
- If a
maskarray element is falsy, the corresponding element inxis mapped in the output array; otherwise, the corresponding element inxis "masked" and thus excluded from the output array.
Examples
var zeroTo = require( '@stdlib/array-base-zero-to' );
var bernoulli = require( '@stdlib/random-array-bernoulli' );
var mskrejectMap = require( '@stdlib/array-base-mskreject-map' );
// Generate a linearly spaced array:
var x = zeroTo( 20 );
console.log( x );
// Generate a random mask:
var mask = bernoulli( x.length, 0.5, {
'dtype': 'generic'
});
console.log( mask );
function clbk( val ) {
return val * 2;
}
// Filter an array using the mask:
var y = mskrejectMap( x, mask, clbk );
console.log( y );Notice
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.
Community
License
See LICENSE.
Copyright
Copyright © 2016-2026. The Stdlib Authors.