Calculate the sum of single-precision floating-point strided array elements.
var ssum = require( '@stdlib/blas/ext/base/ssum' );
Computes the sum of single-precision floating-point strided array elements.
var Float32Array = require( '@stdlib/array/float32' );
var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );
var v = ssum( x.length, x, 1 );
// returns 1.0
The function has the following parameters:
- N: number of indexed elements.
- x: input
Float32Array
. - strideX: stride length.
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, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0 ] );
var v = ssum( 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, 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 = ssum( 4, x1, 2 );
// returns 5.0
Computes the sum of single-precision floating-point strided array elements using alternative indexing semantics.
var Float32Array = require( '@stdlib/array/float32' );
var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );
var v = ssum.ndarray( x.length, x, 1, 0 );
// returns 1.0
The function has the following additional parameters:
- offsetX: starting index.
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, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] );
var v = ssum.ndarray( 4, x, 2, 1 );
// returns 5.0
- If
N <= 0
, both functions return0.0
.
var discreteUniform = require( '@stdlib/random/array/discrete-uniform' );
var ssum = require( '@stdlib/blas/ext/base/ssum' );
var x = discreteUniform( 10, -100, 100, {
'dtype': 'float32'
});
console.log( x );
var v = ssum( x.length, x, 1 );
console.log( v );
#include "stdlib/blas/ext/base/ssum.h"
Computes the sum of single-precision floating-point strided array elements.
const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f };
float v = stdlib_strided_ssum( 4, x, 1 );
// returns 10.0f
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.
float stdlib_strided_ssum( const CBLAS_INT N, const float *X, const CBLAS_INT strideX );
Computes the sum of single-precision floating-point strided array elements using alternative indexing semantics.
const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f };
float v = stdlib_strided_ssum_ndarray( 4, x, 1, 0 );
// returns 10.0f
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. - offsetX:
[in] CBLAS_INT
starting index.
float stdlib_strided_ssum_ndarray( const CBLAS_INT N, const float *X, const CBLAS_INT strideX, const CBLAS_INT offsetX );
#include "stdlib/blas/ext/base/ssum.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 };
// Specify the number of elements:
const int N = 4;
// Specify the stride length:
const int strideX = 2;
// Compute the sum:
float v = stdlib_strided_ssum( N, x, strideX );
// Print the result:
printf( "Sum: %f\n", v );
}
@stdlib/blas/ext/base/dsum
: calculate the sum of double-precision floating-point strided array elements.@stdlib/stats/base/smean
: calculate the arithmetic mean of a single-precision floating-point strided array.@stdlib/blas/ext/base/snansum
: calculate the sum of single-precision floating-point strided array elements, ignoring NaN values.@stdlib/blas/ext/base/gsum
: calculate the sum of strided array elements.