Calculate the cumulative sum of single-precision floating-point strided array elements using ordinary recursive summation.
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> Calculate the cumulative sum of single-precision floating-point strided array elements using ordinary recursive summation.
``bash`
npm install @stdlib/blas-ext-base-scusumors
`javascript`
var scusumors = require( '@stdlib/blas-ext-base-scusumors' );
#### scusumors( N, sum, x, strideX, y, strideY )
Computes the cumulative sum of single-precision floating-point strided array elements using ordinary recursive summation.
`javascript
var Float32Array = require( '@stdlib/array-float32' );
var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );
var y = new Float32Array( x.length );
scusumors( x.length, 0.0, x, 1, y, 1 );
// y =>
x = new Float32Array( [ 1.0, -2.0, 2.0 ] );
y = new Float32Array( x.length );
scusumors( x.length, 10.0, x, 1, y, 1 );
// y =>
`
The function has the following parameters:
- N: number of indexed elements.
- sum: initial sum.
- x: input [Float32Array][@stdlib/array/float32].x
- strideX: stride length for .Float32Array
- y: output [][@stdlib/array/float32].y
- strideY: stride length for .
The N and stride parameters determine which elements in the strided arrays are accessed at runtime. For example, to compute the cumulative sum of every other element:
`javascript
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 y = new Float32Array( x.length );
var v = scusumors( 4, 0.0, x, 2, y, 1 );
// y =>
`
Note that indexing is relative to the first index. To introduce an offset, use [typed array][mdn-typed-array] views.
`javascript
var Float32Array = require( '@stdlib/array-float32' );
// Initial arrays...
var x0 = new Float32Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] );
var y0 = new Float32Array( x0.length );
// Create offset views...
var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
var y1 = new Float32Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 ); // start at 4th element
scusumors( 4, 0.0, x1, -2, y1, 1 );
// y0 =>
`
#### scusumors.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY )
Computes the cumulative sum of single-precision floating-point strided array elements using ordinary recursive summation and alternative indexing semantics.
`javascript
var Float32Array = require( '@stdlib/array-float32' );
var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );
var y = new Float32Array( x.length );
scusumors.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 );
// y =>
`
The function has the following additional parameters:
- offsetX: starting index for x.y
- offsetY: starting index for .
While [typed array][mdn-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 cumulative sum of every other element starting from the second element and to store in the last N elements of y starting from the last element:
`javascript
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 y = new Float32Array( x.length );
scusumors.ndarray( 4, 0.0, x, 2, 1, y, -1, y.length-1 );
// y =>
`
- If N <= 0, both functions return the output array unchanged.
- Ordinary recursive summation (i.e., a "simple" sum) is performant, but can incur significant numerical error. If performance is paramount and error tolerated, using ordinary recursive summation is acceptable; in all other cases, exercise due caution.
`javascript
var discreteUniform = require( '@stdlib/random-array-discrete-uniform' );
var scusumors = require( '@stdlib/blas-ext-base-scusumors' );
var x = discreteUniform( 10, -100, 100, {
'dtype': 'float32'
});
console.log( x );
var y = discreteUniform( 10, -100, 100, {
'dtype': 'float32'
});
console.log( y );
scusumors( x.length, 0.0, x, 1, y, -1 );
console.log( y );
`
*
`c`
#include "stdlib/blas/ext/base/scusumors.h"
#### stdlib_strided_scusumors( N, sum, \X, strideX, \Y, strideY )
Computes the cumulative sum of single-precision floating-point strided array elements using ordinary recursive summation.
`c
const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f };
float y[] = { 0.0f, 0.0f, 0.0f, 0.0f };
stdlib_strided_scusumors( 4, 0.0f, x, 1, y, 1 );
`
The function accepts the following arguments:
- N: [in] CBLAS_INT number of indexed elements.[in] float
- sum: initial sum.[in] float*
- X: input array.[in] CBLAS_INT
- strideX: stride length for X.[out] float*
- Y: output array.[in] CBLAS_INT
- strideY: stride length for Y.
`c`
void stdlib_strided_scusumors( const CBLAS_INT N, const float sum, const float X, const CBLAS_INT strideX, float Y, const CBLAS_INT strideY );
#### stdlib_strided_scusumors_ndarray( N, sum, \X, strideX, offsetX, \Y, strideY, offsetY )
Computes the cumulative sum of single-precision floating-point strided array elements using ordinary recursive summation and alternative indexing semantics.
`c
const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f };
float y[] = { 0.0f, 0.0f, 0.0f, 0.0f };
stdlib_strided_scusumors_ndarray( 4, 0.0f, x, 1, 0, y, 1, 0 );
`
The function accepts the following arguments:
- N: [in] CBLAS_INT number of indexed elements.[in] float
- sum: initial sum.[in] float*
- X: input array.[in] CBLAS_INT
- strideX: stride length for X.[in] CBLAS_INT
- offsetX: starting index for X.[out] float*
- Y: output array.[in] CBLAS_INT
- strideY: stride length for Y.[in] CBLAS_INT
- offsetY: starting index for Y.
`c`
void stdlib_strided_scusumors_ndarray( const CBLAS_INT N, const float sum, const float X, const CBLAS_INT strideX, const CBLAS_INT offsetX, float Y, const CBLAS_INT strideY, const CBLAS_INT offsetY );
`c
#include "stdlib/blas/ext/base/scusumors.h"
#include
int main( void ) {
// Create strided arrays:
const float x[] = { 1.0f, 2.0f, 3.0f, 4.0f, 5.0f, 6.0f, 7.0f, 8.0f };
float y[] = { 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f, 0.0f };
// Specify the number of elements:
const int N = 4;
// Specify stride lengths:
const int strideX = 2;
const int strideY = -2;
// Compute the cumulative sum:
stdlib_strided_scusumors( N, 0.0f, x, strideX, y, strideY );
// Print the result:
for ( int i = 0; i < 8; i++ ) {
printf( "y[ %d ] = %f\n", i, y[ i ] );
}
}
`
*
- [@stdlib/blas-ext/base/dcusumors][@stdlib/blas/ext/base/dcusumors]: calculate the cumulative sum of double-precision floating-point strided array elements using ordinary recursive summation.
- [@stdlib/blas-ext/base/gcusumors][@stdlib/blas/ext/base/gcusumors]: calculate the cumulative sum of strided array elements using ordinary recursive summation.
- [@stdlib/blas-ext/base/scusum][@stdlib/blas/ext/base/scusum]: calculate the cumulative sum of single-precision floating-point strided array elements.
*
This package is part of [stdlib][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][stdlib], see the main project [repository][stdlib].
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---
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[@stdlib/array/float32]: https://www.npmjs.com/package/@stdlib/array-float32
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[@stdlib/blas/ext/base/dcusumors]: https://www.npmjs.com/package/@stdlib/blas-ext-base-dcusumors
[@stdlib/blas/ext/base/gcusumors]: https://www.npmjs.com/package/@stdlib/blas-ext-base-gcusumors
[@stdlib/blas/ext/base/scusum]: https://www.npmjs.com/package/@stdlib/blas-ext-base-scusum