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Calculate the sum of single-precision floating-point strided array elements, ignoring
NaN
values, using pairwise summation with extended accumulation, and returning an extended precision result.
npm install @stdlib/blas-ext-base-dsnansumpw
var dsnansumpw = require( '@stdlib/blas-ext-base-dsnansumpw' );
Computes the sum of single-precision floating-point strided array elements, ignoring NaN
values, using pairwise summation with extended accumulation, and returning an extended precision result.
var Float32Array = require( '@stdlib/array-float32' );
var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );
var N = x.length;
var v = dsnansumpw( 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 x
are accessed at runtime. For example, to compute the sum of every other element in x
,
var Float32Array = require( '@stdlib/array-float32' );
var floor = require( '@stdlib/math-base-special-floor' );
var x = new Float32Array( [ 1.0, 2.0, NaN, -7.0, NaN, 3.0, 4.0, 2.0 ] );
var N = floor( x.length / 2 );
var v = dsnansumpw( N, 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 floor = require( '@stdlib/math-base-special-floor' );
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 N = floor( x0.length / 2 );
var v = dsnansumpw( N, x1, 2 );
// returns 5.0
Computes the sum of single-precision floating-point strided array elements, ignoring NaN
values and using pairwise summation with 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 = dsnansumpw.ndarray( N, 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 floor = require( '@stdlib/math-base-special-floor' );
var x = new Float32Array( [ 2.0, 1.0, NaN, -2.0, -2.0, 2.0, 3.0, 4.0 ] );
var N = floor( x.length / 2 );
var v = dsnansumpw.ndarray( N, x, 2, 1 );
// returns 5.0
- If
N <= 0
, both functions return0.0
. - Accumulated intermediate values are stored as double-precision floating-point numbers.
var randu = require( '@stdlib/random-base-randu' );
var round = require( '@stdlib/math-base-special-round' );
var Float32Array = require( '@stdlib/array-float32' );
var dsnansumpw = require( '@stdlib/blas-ext-base-dsnansumpw' );
var x;
var i;
x = new Float32Array( 10 );
for ( i = 0; i < x.length; i++ ) {
if ( randu() < 0.2 ) {
x[ i ] = NaN;
} else {
x[ i ] = round( randu()*100.0 );
}
}
console.log( x );
var v = dsnansumpw( x.length, x, 1 );
console.log( v );
- Higham, Nicholas J. 1993. "The Accuracy of Floating Point Summation." SIAM Journal on Scientific Computing 14 (4): 783–99. doi:10.1137/0914050.
-
@stdlib/blas-ext/base/dnansumpw
: calculate the sum of double-precision floating-point strided array elements, ignoring NaN values and using pairwise summation. -
@stdlib/blas-ext/base/dssum
: calculate the sum of single-precision floating-point strided array elements using extended accumulation and returning an extended precision result. -
@stdlib/blas-ext/base/dssumpw
: calculate the sum of single-precision floating-point strided array elements using pairwise summation with extended accumulation and returning an extended precision result. -
@stdlib/blas-ext/base/snansumpw
: calculate the sum of single-precision floating-point strided array elements, ignoring NaN values and using pairwise summation.
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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