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dnanmskminabs

Compute the minimum absolute value of a double-precision floating-point ndarray according to a mask, ignoring NaN values.

Installation

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

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

dnanmskminabs( arrays )

Computes the minimum absolute value of a double-precision floating-point ndarray according to a mask, ignoring NaN values.

var Float64Vector = require( '@stdlib/ndarray-vector-float64' );
var Uint8Vector = require( '@stdlib/ndarray-vector-uint8' );

var x = new Float64Vector( [ 1.0, -2.0, NaN, 2.0 ] );
var mask = new Uint8Vector( [ 0, 0, 0, 0 ] );

var v = dnanmskminabs( [ x, mask ] );
// returns 1.0

The function has the following parameters:

• arrays: array-like object containing the following ndarrays:

  • a one-dimensional input ndarray.
  • a one-dimensional mask ndarray.

Notes

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

Examples

var uniform = require( '@stdlib/random-base-uniform' );
var bernoulli = require( '@stdlib/random-base-bernoulli' );
var fillBy = require( '@stdlib/ndarray-fill-by' );
var zeros = require( '@stdlib/ndarray-zeros' );
var ndarray2array = require( '@stdlib/ndarray-to-array' );
var dnanmskminabs = require( '@stdlib/stats-base-ndarray-dnanmskminabs' );

function rand() {
    if ( bernoulli( 0.8 ) < 1 ) {
        return NaN;
    }
    return uniform( -50.0, 50.0 );
}

function mrand() {
    return bernoulli( 0.2 );
}

var opts = {
    'dtype': 'float64'
};
var mopts = {
    'dtype': 'uint8'
};
var x = fillBy( zeros( [ 10 ], opts ), rand );
console.log( ndarray2array( x ) );

var mask = fillBy( zeros( [ 10 ], mopts ), mrand );
console.log( ndarray2array( mask ) );

var v = dnanmskminabs( [ 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 © 2016-2026. The Stdlib Authors.