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mskmax

Calculate the maximum value of a one-dimensional ndarray according to a mask.

Installation

npm install @stdlib/stats-base-ndarray-mskmax

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 mskmax = require( '@stdlib/stats-base-ndarray-mskmax' );

mskmax( arrays )

Computes the maximum value of a one-dimensional ndarray according to a mask.

var ndarray = require( '@stdlib/ndarray-base-ctor' );

var xbuf = [ 1.0, -2.0, 4.0, 2.0 ];
var x = new ndarray( 'generic', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );

var maskbuf = [ 0, 0, 1, 0 ];
var mask = new ndarray( 'generic', maskbuf, [ 4 ], [ 1 ], 0, 'row-major' );

var v = mskmax( [ x, mask ] );
// returns 2.0

The function has the following parameters:

• arrays: array-like object containing an input ndarray and a mask ndarray.

If a mask array element is 0, the corresponding element in the input ndarray is considered valid and included in computation. If a mask array element is 1, the corresponding element in the input ndarray is considered invalid/missing and excluded from computation.

Notes

• If provided an empty ndarray or a mask with all elements set to 1, the function returns NaN.

Examples

var uniform = require( '@stdlib/random-array-uniform' );
var bernoulli = require( '@stdlib/random-array-bernoulli' );
var ndarray = require( '@stdlib/ndarray-base-ctor' );
var ndarray2array = require( '@stdlib/ndarray-to-array' );
var mskmax = require( '@stdlib/stats-base-ndarray-mskmax' );

var xbuf = uniform( 10, -50.0, 50.0, {
    'dtype': 'float64'
});
var x = new ndarray( 'generic', xbuf, [ xbuf.length ], [ 1 ], 0, 'row-major' );
console.log( ndarray2array( x ) );

var maskbuf = bernoulli( xbuf.length, 0.2, {
    'dtype': 'uint8'
});
var mask = new ndarray( 'generic', maskbuf, [ maskbuf.length ], [ 1 ], 0, 'row-major' );
console.log( ndarray2array( mask ) );

var v = mskmax( [ x, mask ] );
console.log( v );

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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

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License

See LICENSE.

Copyright

Copyright © 2016-2025. The Stdlib Authors.