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Compute the sum along one or more ndarray dimensions.
npm install @stdlib/blas-ext-sumAlternatively,
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var sum = require( '@stdlib/blas-ext-sum' );Computes the sum along one or more ndarray dimensions.
var array = require( '@stdlib/ndarray-array' );
var x = array( [ -1.0, 2.0, -3.0 ] );
var y = sum( x );
// returns <ndarray>
var v = y.get();
// returns -2.0The function has the following parameters:
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 numeric 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 = sum( x, {
'dims': [ 0 ]
});
// returns <ndarray>
v = ndarray2array( y );
// returns [ -4.0, 6.0 ]
y = sum( x, {
'dims': [ 1 ]
});
// returns <ndarray>
v = ndarray2array( y );
// returns [ 1.0, 1.0 ]
y = sum( x, {
'dims': [ 0, 1 ]
});
// returns <ndarray>
v = y.get();
// returns 2.0By 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 = sum( x, {
'dims': [ 0 ],
'keepdims': true
});
// returns <ndarray>
v = ndarray2array( y );
// returns [ [ -4.0, 6.0 ] ]
y = sum( x, {
'dims': [ 1 ],
'keepdims': true
});
// returns <ndarray>
v = ndarray2array( y );
// returns [ [ 1.0 ], [ 1.0 ] ]
y = sum( x, {
'dims': [ 0, 1 ],
'keepdims': true
});
// returns <ndarray>
v = ndarray2array( y );
// returns [ [ 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 getDType = require( '@stdlib/ndarray-dtype' );
var array = require( '@stdlib/ndarray-array' );
var x = array( [ -1.0, 2.0, -3.0 ], {
'dtype': 'generic'
});
var y = sum( x, {
'dtype': 'float64'
});
// returns <ndarray>
var dt = getDType( y );
// returns 'float64'Computes the sum 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 = sum.assign( x, y );
// returns <ndarray>
var v = out.get();
// returns -2.0
var bool = ( out === y );
// returns trueThe method has the following parameters:
- x: input ndarray. Must have a numeric 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.
- Setting the
keepdimsoption totruecan 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, 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 theassignmethod, the output ndarray is allowed to have any supported output data type. - When summing a large number of lower precision floating-point numbers (e.g., as found in an ndarray having a
'float32'data type), the accumulated numerical error can become significant. In such cases, casting the input ndarray to a higher precision floating-point data type, such as'float64', prior to computation is advisable.
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 sum = require( '@stdlib/blas-ext-sum' );
// 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 a reduction:
var y = sum( x, {
'dims': [ 0 ]
});
// Resolve the output array data type:
var dt = getDType( y );
console.log( dt );
// Print the results:
console.log( ndarray2array( y ) );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, se 902D e the main project repository.
See LICENSE.
Copyright © 2016-2025. The Stdlib Authors.
