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Replace elements of an array with provided values according to a provided mask array.

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stdlib-js/array-base-mskput

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mskput

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Replace elements of an array with provided values according to a provided mask array.

Installation

npm install @stdlib/array-base-mskput

Alternatively,

  • To load the package in a website via a script tag without installation and bundlers, use the ES Module available on the esm 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.

Usage

var mskput = require( '@stdlib/array-base-mskput' );

mskput( x, mask, values, mode )

Replaces elements of an array with provided values according to a provided mask array.

var x = [ 1, 2, 3, 4 ];

var out = mskput( x, [ 1, 0, 1, 0 ], [ 20, 40 ], 'strict' );
// returns [ 1, 20, 3, 40 ]

var bool = ( out === x );
// returns true

The function supports the following parameters:

  • x: input array.
  • mask: mask array.
  • values: values to set.
  • mode: string specifying behavior when the number of values does not equal the number of falsy mask values.

The function supports the following modes:

  • 'strict': specifies that the function must raise an exception when the number of values does not exactly equal the number of falsy mask values.
  • 'non_strict': specifies that the function must raise an exception when the function is provided insufficient values to satisfy the mask array.
  • 'strict_broadcast': specifies that the function must broadcast a single-element values array and otherwise raise an exception when the number of values does not exactly equal the number of falsy mask values.
  • 'broadcast': specifies that the function must broadcast a single-element values array and otherwise raise an exception when the function is provided insufficient values to satisfy the mask array.
  • 'repeat': specifies that the function must reuse provided values when replacing elements in x in order to satisfy the mask array.

In broadcasting modes, the function supports broadcasting a values array containing a single element against the number of falsy values in the mask array.

var x = [ 1, 2, 3, 4 ];

var out = mskput( x, [ 1, 0, 1, 0 ], [ 20 ], 'strict_broadcast' );
// returns [ 1, 20, 3, 20 ]

var bool = ( out === x );
// returns true

In repeat mode, the function supports recycling elements in a values array to satisfy the number of falsy values in the mask array.

var x = [ 1, 2, 3, 4 ];

var out = mskput( x, [ 0, 0, 1, 0 ], [ 20, 40 ], 'repeat' );
// returns [ 20, 40, 3, 20 ]

var bool = ( out === x );
// returns true

Notes

  • The function mutates the input array x.
  • If a mask array element is falsy, the corresponding element in x is replaced; otherwise, the corresponding element in x is "masked" and thus left unchanged.

Examples

var filledBy = require( '@stdlib/array-base-filled-by' );
var discreteUniform = require( '@stdlib/random-base-discrete-uniform' );
var bernoulli = require( '@stdlib/random-base-bernoulli' );
var linspace = require( '@stdlib/array-base-linspace' );
var mskput = require( '@stdlib/array-base-mskput' );

// Generate a linearly spaced array:
var x = linspace( 0, 100, 11 );
console.log( x );

// Generate a random mask array:
var N = discreteUniform( 5, 15 );
var mask = filledBy( N, bernoulli.factory( 0.3 ) );
console.log( mask );

// Generate an array of random values:
var values = filledBy( N, discreteUniform.factory( 1000, 2000 ) );
console.log( values );

// Update a random sample of elements in `x`:
var out = mskput( x, mask, values, 'non_strict' );
console.log( out );

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.

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License

See LICENSE.

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