dsnansumpw

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.

Usage

var dsnansumpw = require( '@stdlib/blas/ext/base/dsnansumpw' );

dsnansumpw( N, x, strideX )

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 v = dsnansumpw( x.length, x, 1 );
// returns 1.0

The function has the following parameters:

  • N: number of indexed elements.
  • x: input Float32Array.
  • stride: stride length 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:

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 = dsnansumpw( 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 = dsnansumpw( 4, x1, 2 );
// returns 5.0

dsnansumpw.ndarray( N, x, strideX, offsetX )

Computes the sum of single-precision floating-point strided array elements, ignoring NaN values, using pairwise summation with extended accumulation and alternative indexing semantics, and returning an extended precision result.

var Float32Array = require( '@stdlib/array/float32' );

var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );

var v = dsnansumpw.ndarray( x.length, x, 1, 0 );
// returns 1.0

The function has the following additional parameters:

  • offsetX: 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 element starting from the second element:

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 = dsnansumpw.ndarray( 4, x, 2, 1 );
// returns 5.0

Notes

  • If N <= 0, both functions return 0.0.
  • Accumulated intermediate values are stored as double-precision floating-point numbers.

Examples

var discreteUniform = require( '@stdlib/random/base/discrete-uniform' );
var bernoulli = require( '@stdlib/random/base/bernoulli' );
var filledarrayBy = require( '@stdlib/array/filled-by' );
var dsnansumpw = require( '@stdlib/blas/ext/base/dsnansumpw' );

function rand() {
    if ( bernoulli( 0.8 ) > 0 ) {
        return NaN;
    }
    return discreteUniform( 0, 100 );
}

var x = filledarrayBy( 10, 'float32', rand );
console.log( x );

var v = dsnansumpw( x.length, x, 1 );
console.log( v );

C APIs

Usage

#include "stdlib/blas/ext/base/dsnansumpw.h"

stdlib_strided_dsnansumpw( N, *X, strideX )

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.

const float x[] = { 1.0f, -2.0f, 0.0f/0.0f, 2.0f };

double v = stdlib_strided_dsnansumpw( 4, x, 1 );
// returns 1.0

The function accepts the following arguments:

  • N: [in] CBLAS_INT number of indexed elements.
  • X: [in] float* input array.
  • strideX: [in] CBLAS_INT stride length for X.
double stdlib_strided_dsnansumpw( const CBLAS_INT N, const float *X, const CBLAS_INT strideX );

stdlib_strided_dsnansumpw_ndarray( N, *X, strideX, offsetX )

Computes the sum of single-precision floating-point strided array elements, ignoring NaN values, using pairwise summation with extended accumulation and alternative indexing semantics, and returning an extended precision result.

const float x[] = { 1.0f, -2.0f, 0.0f/0.0f, 2.0f };

double v = stdlib_strided_dsnansumpw_ndarray( 4, x, 1, 0 );
// returns 1.0

The function accepts the following arguments:

  • N: [in] CBLAS_INT number of indexed elements.
  • X: [in] float* input array.
  • strideX: [in] CBLAS_INT stride length for X.
  • offsetX: [in] CBLAS_INT starting index for X.
double stdlib_strided_dsnansumpw_ndarray( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX );

Examples

#include "stdlib/blas/ext/base/dsnansumpw.h"
#include <stdio.h>

int main( void ) {
    // Create a strided array:
    const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f, 0.0f/0.0f, 0.0f/0.0f };

    // Specify the number of elements:
    const int N = 5;

    // Specify the stride length:
    const int strideX = 2;

    // Compute the sum:
    double v = stdlib_strided_dsnansumpw( N, x, strideX );

    // Print the result:
    printf( "sum: %lf\n", v );
}

References

  • Higham, Nicholas J. 1993. "The Accuracy of Floating Point Summation." SIAM Journal on Scientific Computing 14 (4): 783–99. doi:10.1137/0914050.

See Also

  • @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.
Did you find this page helpful?