dnansum
Calculate the sum of double-precision floating-point strided array elements, ignoring
NaN
values.
Usage
var dnansum = require( '@stdlib/blas/ext/base/dnansum' );
dnansum( N, x, strideX )
Computes the sum of double-precision floating-point strided array elements, ignoring NaN
values.
var Float64Array = require( '@stdlib/array/float64' );
var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );
var v = dnansum( x.length, x, 1 );
// returns 1.0
The function has the following parameters:
- N: number of indexed elements.
- x: input
Float64Array
. - strideX: 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 in the strided array,
var Float64Array = require( '@stdlib/array/float64' );
var x = new Float64Array( [ 1.0, 2.0, NaN, -7.0, NaN, 3.0, 4.0, 2.0 ] );
var v = dnansum( 4, x, 2 );
// returns 5.0
Note that indexing is relative to the first index. To introduce an offset, use typed array
views.
var Float64Array = require( '@stdlib/array/float64' );
var x0 = new Float64Array( [ 2.0, 1.0, NaN, -2.0, -2.0, 2.0, 3.0, 4.0 ] );
var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
var v = dnansum( 4, x1, 2 );
// returns 5.0
dnansum.ndarray( N, x, strideX, offsetX )
Computes the sum of double-precision floating-point strided array elements, ignoring NaN
values and using alternative indexing semantics.
var Float64Array = require( '@stdlib/array/float64' );
var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );
var v = dnansum.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 Float64Array = require( '@stdlib/array/float64' );
var x = new Float64Array( [ 2.0, 1.0, NaN, -2.0, -2.0, 2.0, 3.0, 4.0 ] );
var v = dnansum.ndarray( 4, x, 2, 1 );
// returns 5.0
Notes
- If
N <= 0
, both functions return0.0
.
Examples
var bernoulli = require( '@stdlib/random/base/bernoulli' );
var discreteUniform = require( '@stdlib/random/base/discrete-uniform' );
var filledarrayBy = require( '@stdlib/array/filled-by' );
var Float64Array = require( '@stdlib/array/float64' );
var dnansum = require( '@stdlib/blas/ext/base/dnansum' );
function clbk() {
if ( bernoulli( 0.7 ) > 0 ) {
return discreteUniform( 0, 100 );
}
return NaN;
}
var x = filledarrayBy( 10, 'float64', clbk );
console.log( x );
var v = dnansum( x.length, x, 1 );
console.log( v );
C APIs
Usage
#include "stdlib/blas/ext/base/dnansum.h"
stdlib_strided_dnansum( N, *X, strideX )
Computes the sum of double-precision floating-point strided array elements, ignoring NaN
values.
const double x[] = { 1.0, 2.0, 0.0/0.0, 4.0 };
double v = stdlib_strided_dnansum( 4, x, 1 );
// returns 7.0
The function accepts the following arguments:
- N:
[in] CBLAS_INT
number of indexed elements. - X:
[in] double*
input array. - strideX:
[in] CBLAS_INT
stride length forX
.
double stdlib_strided_dnansum( const CBLAS_INT N, const double *X, const CBLAS_INT strideX );
stdlib_strided_dnansum_ndarray( N, *X, strideX, offsetX )
Computes the sum of double-precision floating-point strided array elements, ignoring NaN
values and using alternative indexing semantics.
const double x[] = { 1.0, 2.0, 0.0/0.0, 4.0 };
double v = stdlib_strided_dnansum_ndarray( 4, x, 1, 0 );
// returns 7.0
The function accepts the following arguments:
- N:
[in] CBLAS_INT
number of indexed elements. - X:
[in] double*
input array. - strideX:
[in] CBLAS_INT
stride length forX
. - offsetX:
[in] CBLAS_INT
starting index forX
.
double stdlib_strided_dnansum_ndarray( const CBLAS_INT N, const double *X, const CBLAS_INT strideX, const CBLAS_INT offsetX );
Examples
#include "stdlib/blas/ext/base/dnansum.h"
#include <stdio.h>
int main( void ) {
// Create a strided array:
const double x[] = { 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 0.0/0.0, 0.0/0.0 };
// Specify the number of elements:
const int N = 5;
// Specify the stride length:
const int strideX = 2;
// Compute the sum:
double v = stdlib_strided_dnansum( N, x, strideX );
// Print the result:
printf( "sum: %lf\n", v );
}