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cumin

Compute the cumulative minimum value along one or more ndarray dimensions.

Installation

npm install @stdlib/stats-cumin

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

cumin( x[, options] )

Computes the cumulative minimum value along one or more ndarray dimensions.

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

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

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

var arr = ndarray2array( y );
// returns [ -1.0, -1.0, -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 operation. If not provided, the function performs the operation over all elements in a provided input ndarray.
• dtype: output ndarray data type. Must be a real-valued or "generic" data type.

By default, the function performs the operation over all elements in a provided input ndarray. To perform the operation 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 = cumin( x, {
    'dims': [ 0 ]
});
// returns <ndarray>

v = ndarray2array( y );
// returns [ [ -1.0, 2.0 ], [ -3.0, 2.0 ] ]

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

v = ndarray2array( y );
// returns [ [ -1.0, -1.0 ], [ -3.0, -3.0 ] ]

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

v = ndarray2array( y );
// returns [ [ -1.0, -1.0 ], [ -3.0, -3.0 ] ]

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 ndarray2array = require( '@stdlib/ndarray-to-array' );
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 = cumin( x, {
    'dtype': 'float64'
});
// returns <ndarray>

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

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

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

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

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

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

var v = ndarray2array( out );
// returns [ -1.0, -1.0, -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 operation. If not provided, the function performs the operation over all elements in a provided input ndarray.

Notes

• Both functions iterate over ndarray elements according to the memory layout of 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 cumin = require( '@stdlib/stats-cumin' );

// Generate an array of random numbers:
var xbuf = discreteUniform( 25, 0, 20, {
    'dtype': 'generic'
});

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

// Perform operation:
var y = cumin( x, {
    'dims': [ 0 ]
});

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

// Print the results:
console.log( ndarray2array( y ) );

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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.