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Compute the maximum absolute value along one or more ndarray dimensions.

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stdlib-js/stats-maxabs

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maxabs

NPM version Build Status Coverage Status

Compute the maximum absolute value along one or more ndarray dimensions.

Installation

npm install @stdlib/stats-maxabs

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 maxabs = require( '@stdlib/stats-maxabs' );

maxabs( x[, options] )

Computes the maximum absolute value along one or more ndarray dimensions.

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

var x = array( [ -1.0, 2.0, -3.0 ] );

var y = maxabs( x );
// returns <ndarray>

var v = y.get();
// returns 3.0

The function has the following parameters:

  • x: input ndarray. Must have a real-valued or "generic" data type.
  • options: function options (optional).

The function accepts the following options:

  • dims: list of dimensions over which to perform a reduction. If not provided, the function performs a reduction over all elements in a provided input ndarray.
  • dtype: output ndarray data type. Must be a real-valued or "generic" data type.
  • keepdims: boolean indicating whether the reduced dimensions should be included in the returned ndarray as singleton dimensions. Default: false.

By default, the function performs a reduction over all elements in a provided input ndarray. To perform a reduction over specific dimensions, provide a dims option.

var ndarray2array = require( '@stdlib/ndarray-to-array' );
var array = require( '@stdlib/ndarray-array' );

var x = array( [ -1.0, 2.0, -3.0, 4.0 ], {
    'shape': [ 2, 2 ],
    'order': 'row-major'
});
var v = ndarray2array( x );
// returns [ [ -1.0, 2.0 ], [ -3.0, 4.0 ] ]

var y = maxabs( x, {
    'dims': [ 0 ]
});
// returns <ndarray>

v = ndarray2array( y );
// returns [ 3.0, 4.0 ]

y = maxabs( x, {
    'dims': [ 1 ]
});
// returns <ndarray>

v = ndarray2array( y );
// returns [ 2.0, 4.0 ]

y = maxabs( x, {
    'dims': [ 0, 1 ]
});
// returns <ndarray>

v = y.get();
// returns 4.0

By default, the function excludes reduced dimensions from the output ndarray. To include the reduced dimensions as singleton dimensions, set the keepdims option to true.

var ndarray2array = require( '@stdlib/ndarray-to-array' );
var array = require( '@stdlib/ndarray-array' );

var x = array( [ -1.0, 2.0, -3.0, 4.0 ], {
    'shape': [ 2, 2 ],
    'order': 'row-major'
});

var v = ndarray2array( x );
// returns [ [ -1.0, 2.0 ], [ -3.0, 4.0 ] ]

var y = maxabs( x, {
    'dims': [ 0 ],
    'keepdims': true
});
// returns <ndarray>

v = ndarray2array( y );
// returns [ [ 3.0, 4.0 ] ]

y = maxabs( x, {
    'dims': [ 1 ],
    'keepdims': true
});
// returns <ndarray>

v = ndarray2array( y );
// returns [ [ 2.0 ], [ 4.0 ] ]

y = maxabs( x, {
    'dims': [ 0, 1 ],
    'keepdims': true
});
// returns <ndarray>

v = ndarray2array( y );
// returns [ [ 4.0 ] ]

By default, the function returns an ndarray having a data type determined by the function's output data type policy. To override the default behavior, set the dtype option.

var getDType = require( '@stdlib/ndarray-dtype' );
var array = require( '@stdlib/ndarray-array' );

var x = array( [ -1.0, 2.0, -3.0 ], {
    'dtype': 'generic'
});

var y = maxabs( x, {
    'dtype': 'float64'
});
// returns <ndarray>

var dt = getDType( y );
// returns 'float64'

maxabs.assign( x, out[, options] )

Computes the maximum absolute value along one or more ndarray dimensions and assigns results to a provided output ndarray.

var array = require( '@stdlib/ndarray-array' );
var zeros = require( '@stdlib/ndarray-zeros' );

var x = array( [ -1.0, 2.0, -3.0 ] );
var y = zeros( [] );

var out = maxabs.assign( x, y );
// returns <ndarray>

var v = out.get();
// returns 3.0

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

The method has the following parameters:

  • x: input ndarray. Must have a real-valued or generic data type.
  • out: output ndarray.
  • options: function options (optional).

The method accepts the following options:

  • dims: list of dimensions over which to perform a reduction. If not provided, the function performs a reduction over all elements in a provided input ndarray.

Notes

  • Setting the keepdims option to true can be useful when wanting to ensure that the output ndarray is broadcast-compatible with ndarrays having the same shape as the input ndarray.
  • The output data type policy only applies to the main function and specifies that, by default, the function must return an ndarray having the same data type as the input ndarray. For the assign method, the output ndarray is allowed to have any supported output data type.

Examples

var discreteUniform = require( '@stdlib/random-array-discrete-uniform' );
var getDType = require( '@stdlib/ndarray-dtype' );
var ndarray2array = require( '@stdlib/ndarray-to-array' );
var ndarray = require( '@stdlib/ndarray-ctor' );
var maxabs = require( '@stdlib/stats-maxabs' );

// Generate an array of random numbers:
var xbuf = discreteUniform( 25, -10, 10, {
    'dtype': 'generic'
});

// Wrap in an ndarray:
var x = new ndarray( 'generic', xbuf, [ 5, 5 ], [ 5, 1 ], 0, 'row-major' );
console.log( ndarray2array( x ) );

// Perform a reduction:
var y = maxabs( x, {
    'dims': [ 0 ]
});

// Resolve the output array data type:
var dt = getDType( y );
console.log( dt );

// Print the results:
console.log( ndarray2array( 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.

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License

See LICENSE.

Copyright

Copyright © 2016-2025. The Stdlib Authors.