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Add a constant to each single-precision floating-point strided array element and compute the sum using a second-order iterative Kahan–Babuška algorithm.
To use in Observable,
sapxsumkbn2 = require( 'https://cdn.jsdelivr.net/gh/stdlib-js/blas-ext-base-sapxsumkbn2@umd/browser.js' )
To vendor stdlib functionality and avoid installing dependency trees for Node.js, you can use the UMD server build:
var sapxsumkbn2 = require( 'path/to/vendor/umd/blas-ext-base-sapxsumkbn2/index.js' )
To include the bundle in a webpage,
<script type="text/javascript" src="https://cdn.jsdelivr.net/gh/stdlib-js/blas-ext-base-sapxsumkbn2@umd/browser.js"></script>
If no recognized module system is present, access bundle contents via the global scope:
<script type="text/javascript">
(function () {
window.sapxsumkbn2;
})();
</script>
Adds a constant to each single-precision floating-point strided array element and computes the sum using a second-order iterative Kahan–Babuška algorithm.
var Float32Array = require( '@stdlib/array-float32' );
var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );
var N = x.length;
var v = sapxsumkbn2( N, 5.0, x, 1 );
// returns 16.0
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 access every other element in x
,
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 = sapxsumkbn2( 4, 5.0, x, 2 );
// returns 25.0
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, 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 = sapxsumkbn2( 4, 5.0, x1, 2 );
// returns 25.0
Adds a constant to each single-precision floating-point strided array element and computes the sum using a second-order iterative Kahan–Babuška algorithm and alternative indexing semantics.
var Float32Array = require( '@stdlib/array-float32' );
var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );
var N = x.length;
var v = sapxsumkbn2.ndarray( N, 5.0, x, 1, 0 );
// returns 16.0
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 access every other value in x
starting from the second value
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 = sapxsumkbn2.ndarray( 4, 5.0, x, 2, 1 );
// returns 25.0
- If
N <= 0
, both functions return0.0
.
<!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">
(function () {.factory;
var filledarrayBy = require( '@stdlib/array-filled-by');
var sapxsumkbn2 = require( '@stdlib/blas-ext-base-sapxsumkbn2' );
var x = filledarrayBy( 10, 'float32', discreteUniform( 0, 100 ));
console.log( x );
var v = sapxsumkbn2( x.length, 5.0, x, 1 );
console.log( v );
})();
</script>
</body>
</html>
- Klein, Andreas. 2005. "A Generalized Kahan-Babuška-Summation-Algorithm." Computing 76 (3): 279–93. doi:10.1007/s00607-005-0139-x.
@stdlib/blas-ext/base/dapxsumkbn2
: adds a constant to each double-precision floating-point strided array element and computes the sum using a second-order iterative Kahan–Babuška algorithm.@stdlib/blas-ext/base/gapxsumkbn2
: adds a constant to each strided array element and computes the sum using a second-order iterative Kahan–Babuška algorithm.@stdlib/blas-ext/base/sapxsum
: adds a constant to each single-precision floating-point strided array element and computes the sum.@stdlib/blas-ext/base/ssumkbn2
: calculate the sum of single-precision floating-point strided array elements using a second-order iterative 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.
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.
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