Calculate the sum of single-precision floating-point strided array elements using ordinary recursive summation.
npm install @stdlib/blas-ext-base-ssumorsWe believe in a future in which the web is a preferred environment for numerical computation. To help realize this future, we've built stdlib. stdlib is a standard library, with an emphasis on numerical and scientific computation, written in JavaScript (and C) for execution in browsers and in Node.js. The library is fully decomposable, being architected in such a way that you can swap out and mix and match APIs and functionality to cater to your exact preferences and use cases. When you use stdlib, you can be absolutely certain that you are using the most thorough, rigorous, well-written, studied, documented, tested, measured, and high-quality code out there. To join us in bringing numerical computing to the web, get started by checking us out on GitHub, and please consider financially supporting stdlib. We greatly appreciate your continued support!
About stdlib...
[![NPM version][npm-image]][npm-url] [![Build Status][test-image]][test-url] [![Coverage Status][coverage-image]][coverage-url]
> Calculate the sum of single-precision floating-point strided array elements using ordinary recursive summation.
``bash`
npm install @stdlib/blas-ext-base-ssumors
`javascript`
var ssumors = require( '@stdlib/blas-ext-base-ssumors' );
#### ssumors( N, x, strideX )
Computes the sum of single-precision floating-point strided array elements using ordinary recursive summation.
`javascript
var Float32Array = require( '@stdlib/array-float32' );
var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );
var v = ssumors( x.length, x, 1 );
// returns 1.0
`
The function has the following parameters:
- N: number of indexed elements.
- x: input [Float32Array][@stdlib/array/float32].x
- strideX: stride length for .
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:
`javascript
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 = ssumors( 4, x, 2 );
// returns 5.0
`
Note that indexing is relative to the first index. To introduce an offset, use [typed array][mdn-typed-array] views.
`javascript
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 = ssumors( 4, x1, 2 );
// returns 5.0
`
#### ssumors.ndarray( N, x, strideX, offsetX )
Computes the sum of single-precision floating-point strided array elements using ordinary recursive summation and alternative indexing semantics.
`javascript
var Float32Array = require( '@stdlib/array-float32' );
var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );
var v = ssumors.ndarray( x.length, x, 1, 0 );
// returns 1.0
`
The function has the following additional parameters:
- offsetX: starting index for x.
While [typed array][mdn-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 element starting from the second element:
`javascript
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 = ssumors.ndarray( 4, x, 2, 1 );
// returns 5.0
`
- If N <= 0, both functions return 0.0.
- Ordinary recursive summation (i.e., a "simple" sum) is performant, but can incur significant numerical error. If performance is paramount and error tolerated, using ordinary recursive summation is acceptable; in all other cases, exercise due caution.
`javascript
var discreteUniform = require( '@stdlib/random-base-discrete-uniform' ).factory;
var filledarrayBy = require( '@stdlib/array-filled-by' );
var ssumors = require( '@stdlib/blas-ext-base-ssumors' );
var x = filledarrayBy( 10, 'float32', discreteUniform( -100.0, 100.0 ) );
console.log( x );
var v = ssumors( x.length, x, 1 );
console.log( v );
`
*
`c`
#include "stdlib/blas/ext/base/ssumors.h"
#### stdlib_strided_ssumors( N, \*X, strideX )
Computes the sum of single-precision floating-point strided array elements using ordinary recursive summation.
`c
const float x[] = { 1.0f, -2.0f, 2.0f };
float v = stdlib_strided_ssumors( 3, x, 1 );
// returns 1.0f
`
The function accepts the following arguments:
- N: [in] CBLAS_INT number of indexed elements.[in] float*
- X: input array.[in] CBLAS_INT
- strideX: stride length for X.
`c`
float stdlib_strided_ssumors( const CBLAS_INT N, const float *X, const CBLAS_INT strideX );
#### stdlib_strided_ssumors_ndarray( N, \*X, strideX, offsetX )
Computes the sum of single-precision floating-point strided array elements using ordinary recursive summation and alternative indexing semantics.
`c
const float x[] = { 1.0f, -2.0f, 2.0f };
float v = stdlib_strided_ssumors_ndarray( 3, x, 1, 0 );
// returns 1.0f
`
The function accepts the following arguments:
- N: [in] CBLAS_INT number of indexed elements.[in] float*
- X: input array.[in] CBLAS_INT
- strideX: stride length for X.[in] CBLAS_INT
- offsetX: starting index for X.
`c`
float stdlib_strided_ssumors_ndarray( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX );
`c
#include "stdlib/blas/ext/base/ssumors.h"
#include
int main( void ) {
// Create a strided array:
const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f };
// Specify the number of elements:
const int N = 4;
// Specify the stride length:
const int strideX = 2;
// Compute the sum:
float v = stdlib_strided_ssumors( N, x, strideX );
// Print the result:
printf( "sum: %f\n", v );
}
`
*
- [@stdlib/blas-ext/base/dsumors][@stdlib/blas/ext/base/dsumors]: calculate the sum of double-precision floating-point strided array elements using ordinary recursive summation.
- [@stdlib/blas-ext/base/gsumors][@stdlib/blas/ext/base/gsumors]: calculate the sum of strided array elements using ordinary recursive summation.
- [@stdlib/blas-ext/base/snansumors][@stdlib/blas/ext/base/snansumors]: calculate the sum of single-precision floating-point strided array elements, ignoring NaN values and using ordinary recursive summation.
- [@stdlib/blas-ext/base/ssum][@stdlib/blas/ext/base/ssum]: calculate the sum of single-precision floating-point strided array elements.
- [@stdlib/blas-ext/base/ssumkbn2][@stdlib/blas/ext/base/ssumkbn2]: calculate the sum of single-precision floating-point strided array elements using a second-order iterative Kahan–Babuška algorithm.
- [@stdlib/blas-ext/base/ssumpw][@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][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][stdlib], see the main project [repository][stdlib].
#### Community
[![Chat][chat-image]][chat-url]
---
See [LICENSE][stdlib-license].
Copyright © 2016-2026. The Stdlib [Authors][stdlib-authors].
[npm-image]: http://img.shields.io/npm/v/@stdlib/blas-ext-base-ssumors.svg
[npm-url]: https://npmjs.org/package/@stdlib/blas-ext-base-ssumors
[test-image]: https://github.com/stdlib-js/blas-ext-base-ssumors/actions/workflows/test.yml/badge.svg?branch=v0.3.1
[test-url]: https://github.com/stdlib-js/blas-ext-base-ssumors/actions/workflows/test.yml?query=branch:v0.3.1
[coverage-image]: https://img.shields.io/codecov/c/github/stdlib-js/blas-ext-base-ssumors/main.svg
[coverage-url]: https://codecov.io/github/stdlib-js/blas-ext-base-ssumors?branch=main
[chat-image]: https://img.shields.io/badge/zulip-join_chat-brightgreen.svg
[chat-url]: https://stdlib.zulipchat.com
[stdlib]: https://github.com/stdlib-js/stdlib
[stdlib-authors]: https://github.com/stdlib-js/stdlib/graphs/contributors
[umd]: https://github.com/umdjs/umd
[es-module]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Guide/Modules
[deno-url]: https://github.com/stdlib-js/blas-ext-base-ssumors/tree/deno
[deno-readme]: https://github.com/stdlib-js/blas-ext-base-ssumors/blob/deno/README.md
[umd-url]: https://github.com/stdlib-js/blas-ext-base-ssumors/tree/umd
[umd-readme]: https://github.com/stdlib-js/blas-ext-base-ssumors/blob/umd/README.md
[esm-url]: https://github.com/stdlib-js/blas-ext-base-ssumors/tree/esm
[esm-readme]: https://github.com/stdlib-js/blas-ext-base-ssumors/blob/esm/README.md
[branches-url]: https://github.com/stdlib-js/blas-ext-base-ssumors/blob/main/branches.md
[stdlib-license]: https://raw.githubusercontent.com/stdlib-js/blas-ext-base-ssumors/main/LICENSE
[@stdlib/array/float32]: https://www.npmjs.com/package/@stdlib/array-float32
[mdn-typed-array]: https://developer.mozilla.org/en-US/docs/Web/JavaScript/Reference/Global_Objects/TypedArray
[@stdlib/blas/ext/base/dsumors]: https://www.npmjs.com/package/@stdlib/blas-ext-base-dsumors
[@stdlib/blas/ext/base/gsumors]: https://www.npmjs.com/package/@stdlib/blas-ext-base-gsumors
[@stdlib/blas/ext/base/snansumors]: https://www.npmjs.com/package/@stdlib/blas-ext-base-snansumors
[@stdlib/blas/ext/base/ssum]: https://www.npmjs.com/package/@stdlib/blas-ext-base-ssum
[@stdlib/blas/ext/base/ssumkbn2]: https://www.npmjs.com/package/@stdlib/blas-ext-base-ssumkbn2
[@stdlib/blas/ext/base/ssumpw]: https://www.npmjs.com/package/@stdlib/blas-ext-base-ssumpw