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!
Calculate the sum of single-precision floating-point strided array elements, ignoring
NaN
values and using extended accumulation.
To use in Observable,
sdsnansum = require( 'https://cdn.jsdelivr.net/gh/stdlib-js/blas-ext-base-sdsnansum@umd/browser.js' )
To vendor stdlib functionality and avoid installing dependency trees for Node.js, you can use the UMD server build:
var sdsnansum = require( 'path/to/vendor/umd/blas-ext-base-sdsnansum/index.js' )
To include the bundle in a webpage,
<script type="text/javascript" src="https://cdn.jsdelivr.net/gh/stdlib-js/blas-ext-base-sdsnansum@umd/browser.js"></script>
If no recognized module system is present, access bundle contents via the global scope:
<script type="text/javascript">
(function () {
window.sdsnansum;
})();
</script>
Computes the sum of single-precision floating-point strided array elements, ignoring NaN
values and using extended accumulation.
var Float32Array = require( '@stdlib/array-float32' );
var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );
var v = sdsnansum( 4, x, 1 );
// returns 1.0
The function has the following parameters:
- N: number of indexed elements.
- x: input
Float32Array
. - stride: index increment for the strided array.
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, NaN, -7.0, NaN, 3.0, 4.0, 2.0 ] );
var v = sdsnansum( 4, x, 2 );
// returns 5.0
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, NaN, -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 = sdsnansum( 4, x1, 2 );
// returns 5.0
Computes the sum of single-precision floating-point strided array elements, ignoring NaN
values and using extended accumulation and alternative indexing semantics.
var Float32Array = require( '@stdlib/array-float32' );
var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );
var N = x.length;
var v = sdsnansum.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
var Float32Array = require( '@stdlib/array-float32' );
var x = new Float32Array( [ 2.0, 1.0, NaN, -2.0, -2.0, 2.0, 3.0, 4.0 ] );
var v = sdsnansum.ndarray( 4, x, 2, 1 );
// returns 5.0
- If
N <= 0
, both functions return0.0
. - Accumulated intermediate values are stored as double-precision floating-point numbers.
<!DOCTYPE html>
<html lang="en">
<body>
<script type="text/javascript" src="https://cdn.jsdelivr.net/gh/stdlib-js/random-base-discrete-uniform@umd/browser.js"></script>
<script type="text/javascript" src="https://cdn.jsdelivr.net/gh/stdlib-js/random-base-bernoulli@umd/browser.js"></script>
<script type="text/javascript" src="https://cdn.jsdelivr.net/gh/stdlib-js/array-filled-by@umd/browser.js"></script>
<script type="text/javascript" src="https://cdn.jsdelivr.net/gh/stdlib-js/blas-ext-base-sdsnansum@umd/browser.js"></script>
<script type="text/javascript">
(function () {
function randOrNan() {
if ( bernoulli() < 0.2 ) {
return NaN;
}
return discreteUniform( 0, 100 );
}
var x = filledarrayBy( 10, 'float32', randOrNan );
console.log( x );
var v = sdsnansum( x.length, x, 1 );
console.log( v );
})();
</script>
</body>
</html>
@stdlib/blas-ext/base/dsnansum
: calculate the sum of single-precision floating-point strided array elements, ignoring NaN values, using extended accumulation, and returning an extended precision result.@stdlib/blas-ext/base/dnansum
: calculate the sum of double-precision floating-point strided array elements, ignoring NaN values.@stdlib/blas-ext/base/gnansum
: calculate the sum of strided array elements, ignoring NaN values.@stdlib/blas-ext/base/sdssum
: calculate the sum of single-precision floating-point strided array elements using extended accumulation.@stdlib/blas-ext/base/snansum
: calculate the sum of single-precision floating-point strided array elements, ignoring NaN values.
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.