dsnannsumors
Calculate the sum of single-precision floating-point strided array elements, ignoring
NaN
values, using ordinary recursive summation with extended accumulation, and returning an extended precision result.
Usage
var dsnannsumors = require( '@stdlib/blas/ext/base/dsnannsumors' );
dsnannsumors( N, x, strideX, out, strideOut )
Computes the sum of single-precision floating-point strided array elements, ignoring NaN
values, using ordinary recursive summation with extended accumulation, and returning an extended precision result.
var Float32Array = require( '@stdlib/array/float32' );
var Float64Array = require( '@stdlib/array/float64' );
var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );
var out = new Float64Array( 2 );
var v = dsnannsumors( x.length, x, 1, out, 1 );
// returns <Float64Array>[ 1.0, 3 ]
The function has the following parameters:
- N: number of indexed elements.
- x: input
Float32Array
. - strideX: stride length for
x
. - out: output
Float64Array
whose first element is the sum and whose second element is the number of non-NaN elements. - strideOut: stride length for
out
.
The N
and stride parameters determine which elements are accessed at runtime. For example, to compute the sum of every other element:
var Float32Array = require( '@stdlib/array/float32' );
var Float64Array = require( '@stdlib/array/float64' );
var x = new Float32Array( [ 1.0, 2.0, NaN, -7.0, NaN, 3.0, 4.0, 2.0 ] );
var out = new Float64Array( 2 );
var v = dsnannsumors( 4, x, 2, out, 1 );
// returns <Float64Array>[ 5.0, 2 ]
Note that indexing is relative to the first index. To introduce an offset, use typed array
views.
var Float32Array = require( '@stdlib/array/float32' );
var Float64Array = require( '@stdlib/array/float64' );
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 out0 = new Float64Array( 4 );
var out1 = new Float64Array( out0.buffer, out0.BYTES_PER_ELEMENT*2 ); // start at 3rd element
var v = dsnannsumors( 4, x1, 2, out1, 1 );
// returns <Float64Array>[ 5.0, 4 ]
dsnannsumors.ndarray( N, x, strideX, offsetX, out, strideOut, offsetOut )
Computes the sum of single-precision floating-point strided array elements, ignoring NaN
values, using ordinary recursive summation with extended accumulation and alternative indexing semantics, and returning an extended precision result.
var Float32Array = require( '@stdlib/array/float32' );
var Float64Array = require( '@stdlib/array/float64' );
var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );
var out = new Float64Array( 2 );
var v = dsnannsumors.ndarray( x.length, x, 1, 0, out, 1, 0 );
// returns <Float64Array>[ 1.0, 3 ]
The function has the following additional parameters:
- offsetX: starting index for
x
. - offsetOut: starting index for
out
.
While typed array
views mandate a view offset based on the underlying buffer, the offset parameters support indexing semantics based on starting indices. For example, to calculate the sum of every other element starting from the second element:
var Float32Array = require( '@stdlib/array/float32' );
var Float64Array = require( '@stdlib/array/float64' );
var x = new Float32Array( [ 2.0, 1.0, NaN, -2.0, -2.0, 2.0, 3.0, 4.0 ] );
var out = new Float64Array( 4 );
var v = dsnannsumors.ndarray( 4, x, 2, 1, out, 2, 1 );
// returns <Float64Array>[ 0.0, 5.0, 0.0, 4 ]
Notes
- If
N <= 0
, both functions return a sum equal to0.0
. - 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 Float32Array = require( '@stdlib/array/float32' );
var Float64Array = require( '@stdlib/array/float64' );
var dsnannsumors = require( '@stdlib/blas/ext/base/dsnannsumors' );
function rand() {
if ( bernoulli( 0.5 ) < 0.2 ) {
return NaN;
}
return discreteUniform( 0, 100 );
}
var x = filledarrayBy( 10, 'float32', rand );
console.log( x );
var out = new Float64Array( 2 );
dsnannsumors( x.length, x, 1, out, 1 );
console.log( out );
C APIs
Usage
#include "stdlib/blas/ext/base/dsnannsumors.h"
stdlib_strided_dsnannsumors( N, *X, strideX, *n )
Computes the sum of single-precision floating-point strided array elements, ignoring NaN
values, using ordinary recursive summation with extended accumulation, and returning an extended precision result.
const float x[] = { 1.0f, -2.0f, 0.0f/0.0f, 2.0f };
CBLAS_INT n = 0;
double v = stdlib_strided_dsnannsumors( 4, x, 1, &n );
// 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 forX
. - n:
[out] CBLAS_INT*
pointer for storing the number of non-NaN elements.
double stdlib_strided_dsnannsumors( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, CBLAS_INT *n );
stdlib_strided_dsnannsumors_ndarray( N, *X, strideX, offsetX, *n )
Computes the sum of single-precision floating-point strided array elements, ignoring NaN
values, using ordinary recursive 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 };
CBLAS_INT n = 0;
double v = stdlib_strided_dsnannsumors_ndarray( 4, x, 1, 0, &n );
// 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 forX
. - offsetX:
[in] CBLAS_INT
starting index forX
. - n:
[out] CBLAS_INT*
pointer for storing the number of non-NaN elements.
double stdlib_strided_dsnannsumors_ndarray( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX, CBLAS_INT *n );
Examples
#include "stdlib/blas/ext/base/dsnannsumors.h"
#include "stdlib/blas/base/shared.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;
// Initialize a variable for storing the number of non-NaN elements:
CBLAS_INT n = 0;
// Compute the sum:
double v = stdlib_strided_dsnannsumors( N, x, strideX, &n );
// Print the result:
printf( "sum: %lf\n", v );
printf( "n: %"CBLAS_IFMT"\n", n );
}