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Calculate the sum of single-precision floating-point strided array elements, ignoring NaN values and using pairwise summation with extended accumulation.

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sdsnansumpw

Calculate the sum of single-precision floating-point strided array elements, ignoringNaN values and using pairwise summation with extended accumulation.

Installation

npm install @stdlib/blas-ext-base-sdsnansumpw

Alternatively,

To load the package in a website via ascript tag without installation and bundlers, use theES Module available on theesm branch (seeREADME).
If you are using Deno, visit thedeno branch (seeREADME for usage intructions).
For use in Observable, or in browser/node environments, use theUniversal Module Definition (UMD) build available on theumd branch (seeREADME).

Thebranches.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

varsdsnansumpw=require('@stdlib/blas-ext-base-sdsnansumpw');

sdsnansumpw( N, x, strideX )

Computes the sum of single-precision floating-point strided array elements, ignoringNaN values and using pairwise summation with extended accumulation.

varFloat32Array=require('@stdlib/array-float32');varx=newFloat32Array([1.0,-2.0,NaN,2.0]);varv=sdsnansumpw(x.length,x,1);// returns 1.0

The function has the following parameters:

N: number of indexed elements.
x: inputFloat32Array.
strideX: stride length.

TheN and stride parameters determine which elements in the strided array are accessed at runtime. For example, to compute the sum of every other element:

varFloat32Array=require('@stdlib/array-float32');varx=newFloat32Array([1.0,2.0,NaN,-7.0,NaN,3.0,4.0,2.0]);varv=sdsnansumpw(4,x,2);// returns 5.0

Note that indexing is relative to the first index. To introduce an offset, usetyped array views.

varFloat32Array=require('@stdlib/array-float32');varx0=newFloat32Array([2.0,1.0,NaN,-2.0,-2.0,2.0,3.0,4.0]);varx1=newFloat32Array(x0.buffer,x0.BYTES_PER_ELEMENT*1);// start at 2nd elementvarv=sdsnansumpw(4,x1,2);// returns 5.0

sdsnansumpw.ndarray( N, x, strideX, offsetX )

Computes the sum of single-precision floating-point strided array elements, ignoringNaN values and using pairwise summation with extended accumulation and alternative indexing semantics.

varFloat32Array=require('@stdlib/array-float32');varx=newFloat32Array([1.0,-2.0,NaN,2.0]);varv=sdsnansumpw.ndarray(x.length,x,1,0);// returns 1.0

The function has the following additional parameters:

offsetX: starting index.

Whiletyped 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 element starting from the second element:

varFloat32Array=require('@stdlib/array-float32');varx=newFloat32Array([2.0,1.0,NaN,-2.0,-2.0,2.0,3.0,4.0]);varv=sdsnansumpw.ndarray(4,x,2,1);// returns 5.0

Notes

IfN <= 0, both functions return0.0.
Accumulated intermediate values are stored as double-precision floating-point numbers.

Examples

vardiscreteUniform=require('@stdlib/random-base-discrete-uniform');varbernoulli=require('@stdlib/random-base-bernoulli');varfilledarrayBy=require('@stdlib/array-filled-by');varsdsnansumpw=require('@stdlib/blas-ext-base-sdsnansumpw');functionrand(){if(bernoulli(0.5)<1){returnNaN;}returndiscreteUniform(0,100);}varx=filledarrayBy(10,'float32',rand);console.log(x);varv=sdsnansumpw(x.length,x,1);console.log(v);

C APIs

Usage

#include"stdlib/blas/ext/base/sdsnansumpw.h"

stdlib_strided_sdsnansumpw( N, *X, strideX )

Computes the sum of single-precision floating-point strided array elements, ignoringNaN values and using pairwise summation with extended accumulation.

constfloatx[]= {1.0f,-2.0f,0.0f/0.0f,2.0f };floatv=stdlib_strided_sdsnansumpw(4,x,1 );// returns 1.0f

The function accepts the following arguments:

N:[in] CBLAS_INT number of indexed elements.
X:[in] float* input array.
strideX:[in] CBLAS_INT stride length.

floatstdlib_strided_sdsnansumpw(constCBLAS_INTN,constfloat*X,constCBLAS_INTstrideX );

stdlib_strided_sdsnansumpw_ndarray( N, *X, strideX, offsetX )

Computes the sum of single-precision floating-point strided array elements, ignoringNaN values and using pairwise summation with extended accumulation and alternative indexing semantics.

constfloatx[]= {1.0f,-2.0f,0.0f/0.0f,2.0f };floatv=stdlib_strided_sdsnansumpw_ndarray(4,x,1,0 );// returns 1.0f

The function accepts the following arguments:

N:[in] CBLAS_INT number of indexed elements.
X:[in] float* input array.
strideX:[in] CBLAS_INT stride length.
offsetX:[in] CBLAS_INT starting index.

floatstdlib_strided_sdsnansumpw_ndarray(constCBLAS_INTN,constfloat*X,constCBLAS_INTstrideX,constCBLAS_INToffsetX );

Examples

#include"stdlib/blas/ext/base/sdsnansumpw.h"#include<stdio.h>intmain(void ) {// Create a strided array:constfloatx[]= {1.0f,2.0f,3.0f,4.0f,5.0f,6.0f,7.0f,8.0f,0.0f/0.0f,0.0f/0.0f };// Specify the number of elements:constintN=5;// Specify the stride length:constintstrideX=2;// Compute the sum:floatv=stdlib_strided_sdsnansumpw(N,x,strideX );// Print the result:printf("Sum: %f\n",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.

Notice

This package is part ofstdlib, 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 developstdlib, see the main projectrepository.

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License

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Calculate the sum of single-precision floating-point strided array elements, ignoring NaN values and using pairwise summation with extended accumulation.

github.com/stdlib-js/stdlib