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@stdlib/blas-ext-base-gsumpw
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Calculate the sum of strided array elements using pairwise summation.
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Calculate the sum of strided array elements using pairwise summation.
npm install @stdlib/blas-ext-base-gsumpw
var gsumpw = require( '@stdlib/blas-ext-base-gsumpw' );
Computes the sum of strided array elements using pairwise summation.
var x = [ 1.0, -2.0, 2.0 ];
var N = x.length;
var v = gsumpw( N, x, 1 );
// returns 1.0
The function has the following parameters:
Array
or typed array
.x
.The N
and stride
parameters determine which elements in x
are accessed at runtime. For example, to compute the gsumpw of every other element in x
,
var floor = require( '@stdlib/math-base-special-floor' );
var x = [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0 ];
var N = floor( x.length / 2 );
var v = gsumpw( N, x, 2 );
// returns 5.0
Note that indexing is relative to the first index. To introduce an offset, use typed array
views.
var Float64Array = require( '@stdlib/array-float64' );
var floor = require( '@stdlib/math-base-special-floor' );
var x0 = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] );
var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
var N = floor( x0.length / 2 );
var v = gsumpw( N, x1, 2 );
// returns 5.0
Computes the sum of strided array elements using pairwise summation and alternative indexing semantics.
var x = [ 1.0, -2.0, 2.0 ];
var N = x.length;
var v = gsumpw.ndarray( N, x, 1, 0 );
// returns 1.0
The function has the following additional parameters:
x
.While typed array
views mandate a view offset based on the underlying buffer
, the offset
parameter supports indexing semantics based on a starting index. For example, to calculate the sum of every other value in x
starting from the second value
var floor = require( '@stdlib/math-base-special-floor' );
var x = [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ];
var N = floor( x.length / 2 );
var v = gsumpw.ndarray( N, x, 2, 1 );
// returns 5.0
N <= 0
, both functions return 0.0
.dsumpw
, ssumpw
, etc.) are likely to be significantly more performant.var randu = require( '@stdlib/random-base-randu' );
var round = require( '@stdlib/math-base-special-round' );
var Float64Array = require( '@stdlib/array-float64' );
var gsumpw = require( '@stdlib/blas-ext-base-gsumpw' );
var x;
var i;
x = new Float64Array( 10 );
for ( i = 0; i < x.length; i++ ) {
x[ i ] = round( randu()*100.0 );
}
console.log( x );
var v = gsumpw( x.length, x, 1 );
console.log( v );
@stdlib/blas-ext/base/dsumpw
: calculate the sum of double-precision floating-point strided array elements using pairwise summation.@stdlib/blas-ext/base/gnansumpw
: calculate the sum of strided array elements, ignoring NaN values and using pairwise summation.@stdlib/blas-ext/base/gsum
: calculate the sum of strided array elements.@stdlib/blas-ext/base/gsumkbn2
: calculate the sum of strided array elements using a second-order iterative Kahan–Babuška algorithm.@stdlib/blas-ext/base/gsumors
: calculate the sum of strided array elements using ordinary recursive summation.@stdlib/blas-ext/base/ssumpw
: calculate the sum of single-precision floating-point strided array elements using pairwise summation.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.
See LICENSE.
Copyright © 2016-2024. The Stdlib Authors.
0.2.2 (2024-07-28)
No changes reported for this release.
</section> <!-- /.release --> <section class="release" id="v0.2.1">FAQs
Calculate the sum of strided array elements using pairwise summation.
The npm package @stdlib/blas-ext-base-gsumpw receives a total of 17,669 weekly downloads. As such, @stdlib/blas-ext-base-gsumpw popularity was classified as popular.
We found that @stdlib/blas-ext-base-gsumpw demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 0 open source maintainers collaborating on the project.
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