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About stdlib...

We 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!

sdssum

NPM version Build Status Coverage Status

Calculate the sum of single-precision floating-point strided array elements using extended accumulation.

Usage

import sdssum from 'https://cdn.jsdelivr.net/gh/stdlib-js/blas-ext-base-sdssum@esm/index.mjs';

sdssum( N, x, stride )

Computes the sum of single-precision floating-point strided array elements using extended accumulation.

import Float32Array from 'https://cdn.jsdelivr.net/gh/stdlib-js/array-float32@esm/index.mjs';

var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );
var N = x.length;

var v = sdssum( N, x, 1 );
// returns 1.0

The function has the following parameters:

  • N: number of indexed elements.
  • x: input Float32Array.
  • stride: index increment.

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,

import Float32Array from 'https://cdn.jsdelivr.net/gh/stdlib-js/array-float32@esm/index.mjs';

var x = new Float32Array( [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0 ] );

var v = sdssum( 4, x, 2 );
// returns 5.0

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

import Float32Array from 'https://cdn.jsdelivr.net/gh/stdlib-js/array-float32@esm/index.mjs';

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 = sdssum( 4, x1, 2 );
// returns 5.0

sdssum.ndarray( N, x, stride, offset )

Computes the sum of single-precision floating-point strided array elements using extended accumulation and alternative indexing semantics.

import Float32Array from 'https://cdn.jsdelivr.net/gh/stdlib-js/array-float32@esm/index.mjs';

var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );
var N = x.length;

var v = sdssum.ndarray( N, x, 1, 0 );
// returns 1.0

The function has the following additional parameters:

  • offset: starting index for the strided array.

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 the strided array starting from the second value

import Float32Array from 'https://cdn.jsdelivr.net/gh/stdlib-js/array-float32@esm/index.mjs';

var x = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] );

var v = sdssum.ndarray( 4, x, 2, 1 );
// returns 5.0

Notes

  • If N <= 0, both functions return 0.0.
  • Accumulated intermediate values are stored as double-precision floating-point numbers.

Examples

<!DOCTYPE html>
<html lang="en">
<body>
<script type="module">

var discreteUniform = require( 'https://cdn.jsdelivr.net/gh/stdlib-js/random-base-discrete-uniform' ).factory;
import filledarrayBy from 'https://cdn.jsdelivr.net/gh/stdlib-js/array-filled-by@esm/index.mjs';
import sdssum from 'https://cdn.jsdelivr.net/gh/stdlib-js/blas-ext-base-sdssum@esm/index.mjs';

var x = filledarrayBy( 10, 'float32', discreteUniform( 0, 100 ) );

console.log( x );

var v = sdssum( x.length, x, 1 );
console.log( v );

</script>
</body>
</html>

See Also

Notice

This package is part of stdlib, a standard library 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.

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License

See LICENSE.

Copyright

Copyright © 2016-2024. The Stdlib Authors.