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cusum

Compute the cumulative sum along one or more ndarray dimensions.

Installation

npm install @stdlib/blas-ext-cusum

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 cusum = require( '@stdlib/blas-ext-cusum' );

cusum( x[, initial][, options] )

Computes the cumulative sum 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 = cusum( x );
// returns <ndarray>

var arr = ndarray2array( y );
// returns [ -1.0, 1.0, -2.0 ]

The function has the following parameters:

• x: input ndarray. Must have a numeric or "generic" data type.
• initial: initial value for the cumulative sum (optional). May be either a scalar value or an ndarray having a data type which promotes to the data type of the input ndarray. If provided a scalar value, the value is cast to the data type of the input ndarray. If provided an ndarray, the value must have a shape which is broadcast-compatible with the complement of the shape defined by options.dims. For example, given the input shape [2, 3, 4] and options.dims=[0], an ndarray initial value must have a shape which is broadcast-compatible with the shape [3, 4]. Similarly, when performing the operation over all elements in a provided input ndarray, an ndarray initial value must be a zero-dimensional ndarray. By default, the initial value is the additive identity (i.e., zero).
• 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 numeric or "generic" data type.

By default, the function uses the additive identity when computing the cumulative sum. To begin summing from a different value, provide an initial argument.

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

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

var y = cusum( x, 10.0 );
// returns <ndarray>

var arr = ndarray2array( y );
// returns [ 9.0, 11.0, 8.0 ]

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

v = ndarray2array( y );
// returns [ [ -1.0, 2.0 ], [ -4.0, 6.0 ] ]

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

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

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

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

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

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

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

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

cusum.assign( x[, initial], out[, options] )

Computes the cumulative sum 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 = cusum.assign( x, y );
// returns <ndarray>

var v = ndarray2array( out );
// returns [ -1.0, 1.0, -2.0 ]

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

The method has the following parameters:

• x: input ndarray. Must have a numeric or generic data type.
• initial: initial value for the cumulative sum (optional). May be either a scalar value or an ndarray having a data type which promotes to the data type of the input ndarray. If provided a scalar value, the value is cast to the data type of the input ndarray. If provided an ndarray, the value must have a shape which is broadcast-compatible with the complement of the shape defined by options.dims. For example, given the input shape [2, 3, 4] and options.dims=[0], an ndarray initial value must have a shape which is broadcast-compatible with the shape [3, 4]. Similarly, when performing the operation over all elements in a provided input ndarray, an ndarray initial value must be a zero-dimensional ndarray. By default, the initial value is the additive identity (i.e., zero).
• 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. Accordingly, performance degradation is possible when operating over multiple dimensions of a large non-contiguous multi-dimensional input ndarray. In such scenarios, one may want to copy an input ndarray to contiguous memory before computing the cumulative sum.
• The output data type policy only applies to the main function and specifies that, by default, in order to avoid issues arising from integer overflow, the function must return an ndarray having a data type amenable to accumulation. This means that, for integer data types having small value ranges (e.g., int8, uint8, etc), the main function returns an ndarray having at least a 32-bit integer data type. By default, if an input ndarray has a floating-point data type, the main function returns an ndarray having the same data type. 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 cusum = require( '@stdlib/blas-ext-cusum' );

// 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 = cusum( x, 100.0, {
    '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.