@stdlib/blas-ext-base-ndarray-snansumkbn
v0.1.1
Published
Compute the sum of a one-dimensional single-precision floating-point ndarray, ignoring `NaN` values and using an improved Kahan–Babuška algorithm.
Readme
snansumkbn
Compute the sum of a one-dimensional single-precision floating-point ndarray, ignoring
NaNvalues and using an improved Kahan–Babuška algorithm.
Installation
npm install @stdlib/blas-ext-base-ndarray-snansumkbnUsage
var snansumkbn = require( '@stdlib/blas-ext-base-ndarray-snansumkbn' );snansumkbn( arrays )
Computes the sum of a one-dimensional single-precision floating-point ndarray, ignoring NaN values and using an improved Kahan–Babuška algorithm.
var Float32Array = require( '@stdlib/array-float32' );
var ndarray = require( '@stdlib/ndarray-base-ctor' );
var xbuf = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );
var x = new ndarray( 'float32', xbuf, [ 4 ], [ 1 ], 0, 'row-major' );
var v = snansumkbn( [ x ] );
// returns 1.0The function has the following parameters:
- arrays: array-like object containing a one-dimensional input ndarray.
Notes
- If provided an empty one-dimensional ndarray, the function returns
0.0.
Examples
var bernoulli = require( '@stdlib/random-base-bernoulli' );
var discreteUniform = require( '@stdlib/random-base-discrete-uniform' );
var filledarrayBy = require( '@stdlib/array-filled-by' );
var ndarray = require( '@stdlib/ndarray-base-ctor' );
var ndarray2array = require( '@stdlib/ndarray-to-array' );
var snansumkbn = require( '@stdlib/blas-ext-base-ndarray-snansumkbn' );
function clbk() {
if ( bernoulli( 0.7 ) > 0 ) {
return discreteUniform( 0, 100 );
}
return NaN;
}
var xbuf = filledarrayBy( 10, 'float32', clbk );
var x = new ndarray( 'float32', xbuf, [ xbuf.length ], [ 1 ], 0, 'row-major' );
console.log( ndarray2array( x ) );
var v = snansumkbn( [ x ] );
console.log( v );References
- Neumaier, Arnold. 1974. "Rounding Error Analysis of Some Methods for Summing Finite Sums." Zeitschrift Für Angewandte Mathematik Und Mechanik 54 (1): 39–51. doi:10.1002/zamm.19740540106.
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 © 2016-2026. The Stdlib Authors.
