Package Exports

@stdlib/stats-base-ndarray-scumax
@stdlib/stats-base-ndarray-scumax/lib/index.js

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scumax

Compute the cumulative maximum value of a one-dimensional single-precision floating-point ndarray.

Installation

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

Usage

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

scumax( arrays )

Computes the cumulative maximum value of a one-dimensional single-precision floating-point ndarray.

var Float32Array = require( '@stdlib/array-float32' );
var ndarray2array = require( '@stdlib/ndarray-to-array' );
var ndarray = require( '@stdlib/ndarray-base-ctor' );

var xbuf = new Float32Array( [ 1.0, 3.0, 4.0, 2.0 ] );
var x = new ndarray( 'float32', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );

var ybuf = new Float32Array( [ 0.0, 0.0, 0.0, 0.0 ] );
var y = new ndarray( 'float32', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );

var v = scumax( [ x, y ] );
// returns <ndarray>

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

var arr = ndarray2array( v );
// returns [ 1.0, 3.0, 4.0, 4.0 ]

The function has the following parameters:

arrays: array-like object containing a one-dimensional input ndarray and a one-dimensional output ndarray.

Notes

If provided an empty one-dimensional input ndarray, the function returns the output ndarray unchanged.

Examples

var discreteUniform = require( '@stdlib/random-array-discrete-uniform' );
var ndarray = require( '@stdlib/ndarray-base-ctor' );
var zerosLike = require( '@stdlib/ndarray-zeros-like' );
var ndarray2array = require( '@stdlib/ndarray-to-array' );
var scumax = require( '@stdlib/stats-base-ndarray-scumax' );

var xbuf = discreteUniform( 10, -50, 50, {
    'dtype': 'float32'
});
var x = new ndarray( 'float32', xbuf, [ xbuf.length ], [ 1 ], 0, 'row-major' );
console.log( ndarray2array( x ) );

var y = zerosLike( x );
console.log( ndarray2array( y ) );

var v = scumax( [ x, y ] );
console.log( ndarray2array( v ) );

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.

@stdlib/stats-base-ndarray-scumax