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Calculate the sum of single-precision floating-point strided array elements, ignoring
NaN
values and using an improved Kahan–Babuška algorithm.
npm install @stdlib/blas-ext-base-snansumkbn
Alternatively,
- To load the package in a website via a
script
tag without installation and bundlers, use the ES Module available on theesm
branch (see README). - If you are using Deno, visit the
deno
branch (see README for usage intructions). - For use in Observable, or in browser/node environments, use the Universal Module Definition (UMD) build available on the
umd
branch (see README).
The branches.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.
var snansumkbn = require( '@stdlib/blas-ext-base-snansumkbn' );
Computes the sum of single-precision floating-point strided array elements, ignoring NaN
values and using an improved Kahan–Babuška algorithm.
var Float32Array = require( '@stdlib/array-float32' );
var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );
var N = x.length;
var v = snansumkbn( N, x, 1 );
// returns 1.0
The function has the following parameters:
- N: number of indexed elements.
- x: input
Float32Array
. - stride: index increment for
x
.
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 x
,
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 = snansumkbn( 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 = snansumkbn( 4, x1, 2 );
// returns 5.0
Computes the sum of single-precision floating-point strided array elements, ignoring NaN
values and using an improved Kahan–Babuška algorithm and alternative indexing semantics.
var Float32Array = require( '@stdlib/array-float32' );
var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );
var v = snansumkbn.ndarray( 4, x, 1, 0 );
// returns 1.0
The function has the following additional parameters:
- offset: starting index for
x
.
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 x
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 = snansumkbn.ndarray( 4, x, 2, 1 );
// returns 5.0
- If
N <= 0
, both functions return0.0
.
var discreteUniform = require( '@stdlib/random-base-discrete-uniform' );
var bernoulli = require( '@stdlib/random-base-bernoulli' );
var filledarrayBy = require( '@stdlib/array-filled-by' );
var snansumkbn = require( '@stdlib/blas-ext-base-snansumkbn' );
function rand() {
if ( bernoulli( 0.8 ) > 0 ) {
return discreteUniform( 0, 100 );
}
return NaN;
}
var x = filledarrayBy( 10, 'float32', rand );
console.log( x );
var v = snansumkbn( x.length, x, 1 );
console.log( v );
- 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.
@stdlib/blas-ext/base/dnansumkbn
: calculate the sum of double-precision floating-point strided array elements, ignoring NaN values and using an improved Kahan–Babuška algorithm.@stdlib/blas-ext/base/gnansumkbn
: calculate the sum of strided array elements, ignoring NaN values and using an improved Kahan–Babuška algorithm.@stdlib/blas-ext/base/snansum
: calculate the sum of single-precision floating-point strided array elements, ignoring NaN values.@stdlib/blas-ext/base/snansumkbn2
: calculate the sum of single-precision floating-point strided array elements, ignoring NaN values and using a second-order iterative Kahan–Babuška algorithm.@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/snansumpw
: calculate the sum of single-precision floating-point strided array elements, ignoring NaN values and using pairwise summation.@stdlib/blas-ext/base/ssumkbn
: calculate the sum of single-precision floating-point strided array elements using an improved Kahan–Babuška algorithm.
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.
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See LICENSE.
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