@stdlib/blas-ext-base-sdsapxsumpw
v0.2.2
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Adds a constant to each single-precision floating-point strided array element and computes the sum using pairwise summation with extended accumulation.
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sdsapxsumpw
Add a constant to each single-precision floating-point strided array element and compute the sum using pairwise summation with extended accumulation.
Installation
npm install @stdlib/blas-ext-base-sdsapxsumpw
Usage
var sdsapxsumpw = require( '@stdlib/blas-ext-base-sdsapxsumpw' );
sdsapxsumpw( N, alpha, x, stride )
Adds a constant to each single-precision floating-point strided array element and computes the sum using pairwise summation with extended accumulation.
var Float32Array = require( '@stdlib/array-float32' );
var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );
var v = sdsapxsumpw( 3, 5.0, x, 1 );
// returns 16.0
The function has the following parameters:
- N: number of indexed elements.
- alpha: scalar constant.
- x: input
Float32Array
. - stride: index increment for
x
.
The N
and stride parameters determine which elements in the strided array are accessed at runtime. For example, to compute the sum of every other element in the strided array,
var Float32Array = require( '@stdlib/array-float32' );
var x = new Float32Array( [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0 ] );
var v = sdsapxsumpw( 4, 5.0, x, 2 );
// returns 25.0
Note that indexing is relative to the first index. To introduce an offset, use typed array
views.
var Float32Array = require( '@stdlib/array-float32' );
var x0 = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] );
var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
var v = sdsapxsumpw( 4, 5.0, x1, 2 );
// returns 25.0
sdsapxsumpw.ndarray( N, alpha, x, stride, offset )
Adds a constant to each single-precision floating-point strided array element and computes the sum using pairwise summation with extended accumulation and alternative indexing semantics.
var Float32Array = require( '@stdlib/array-float32' );
var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );
var v = sdsapxsumpw.ndarray( 3, 5.0, x, 1, 0 );
// returns 16.0
The function has the following additional parameters:
- offset: starting index for
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 access every other value in the strided array starting from the second value
var Float32Array = require( '@stdlib/array-float32' );
var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] );
var v = sdsapxsumpw.ndarray( 4, 5.0, x, 2, 1 );
// returns 25.0
Notes
- If
N <= 0
, both functions return0.0
. - Accumulated intermediate values are stored as double-precision floating-point numbers.
Examples
var discreteUniform = require( '@stdlib/random-base-discrete-uniform' ).factory;
var filledarrayBy = require( '@stdlib/array-filled-by' );
var sdsapxsumpw = require( '@stdlib/blas-ext-base-sdsapxsumpw' );
var x = filledarrayBy( 10, 'float32', discreteUniform( 0, 100 ) );
console.log( x );
var v = sdsapxsumpw( x.length, 5.0, x, 1 );
console.log( v );
References
- Higham, Nicholas J. 1993. "The Accuracy of Floating Point Summation." SIAM Journal on Scientific Computing 14 (4): 783–99. doi:10.1137/0914050.
See Also
@stdlib/blas-ext/base/dsapxsumpw
: adds a constant to each single-precision floating-point strided array element and computes the sum using pairwise summation with extended accumulation and returning an extended precision result.@stdlib/blas-ext/base/sapxsumpw
: adds a constant to each single-precision floating-point strided array element and computes the sum using pairwise summation.@stdlib/blas-ext/base/sdsapxsum
: adds a constant to each single-precision floating-point strided array element and computes the sum using extended accumulation.@stdlib/blas-ext/base/sdssumpw
: calculate the sum of single-precision floating-point strided array elements using pairwise summation with extended accumulation.
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.
Copyright
Copyright © 2016-2024. The Stdlib Authors.