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Calculate the cumulative sum of single-precision floating-point strided array elements.
npm install @stdlib/blas-ext-base-scusum
Alternatively,
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tag without installation and bundlers, use the ES Module available on theesm
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branch (see README).
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To view installation and usage instructions specific to each branch build, be sure to explicitly navigate to the respective README files on each branch, as linked to above.
var scusum = require( '@stdlib/blas-ext-base-scusum' );
Computes the cumulative 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 y = new Float32Array( x.length );
scusum( x.length, 0.0, x, 1, y, 1 );
// y => <Float32Array>[ 1.0, -1.0, 1.0 ]
x = new Float32Array( [ 1.0, -2.0, 2.0 ] );
y = new Float32Array( x.length );
scusum( x.length, 10.0, x, 1, y, 1 );
// y => <Float32Array>[ 11.0, 9.0, 11.0 ]
The function has the following parameters:
- N: number of indexed elements.
- sum: initial sum.
- x: input
Float32Array
. - strideX: index increment for
x
. - y: output
Float32Array
. - strideY: index increment for
y
.
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 in the strided input array,
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 = scusum( 4, 0.0, x, 2, y, 1 );
// y => <Float32Array>[ 1.0, 3.0, 1.0, 5.0, 0.0, 0.0, 0.0, 0.0 ]
Note that indexing is relative to the first index. To introduce an offset, use typed array
views.
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
scusum( 4, 0.0, x1, -2, y1, 1 );
// y0 => <Float32Array>[ 0.0, 0.0, 0.0, 4.0, 6.0, 4.0, 5.0, 0.0 ]
Computes the cumulative 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 y = new Float32Array( x.length );
scusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 );
// y => <Float32Array>[ 1.0, -1.0, 1.0 ]
The function has the following additional parameters:
- offsetX: starting index for
x
. - offsetY: starting index for
y
.
While typed array
views mandate a view offset based on the underlying buffer
, offsetX and offsetY parameters support indexing semantics based on a starting indices. For example, to calculate the cumulative sum of every other value in the strided input array starting from the second value and to store in the last N
elements of the strided output array starting from the last 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 y = new Float32Array( x.length );
scusum.ndarray( 4, 0.0, x, 2, 1, y, -1, y.length-1 );
// y => <Float32Array>[ 0.0, 0.0, 0.0, 0.0, 5.0, 1.0, -1.0, 1.0 ]
- If
N <= 0
, both functions returny
unchanged.
var discreteUniform = require( '@stdlib/random-base-discrete-uniform' ).factory;
var filledarrayBy = require( '@stdlib/array-filled-by' );
var Float32Array = require( '@stdlib/array-float32' );
var scusum = require( '@stdlib/blas-ext-base-scusum' );
var x = filledarrayBy( 10, 'float32', discreteUniform( 0, 100 ) );
var y = new Float32Array( x.length );
console.log( x );
console.log( y );
scusum( x.length, 0.0, x, 1, y, -1 );
console.log( y );
@stdlib/blas-ext/base/dcusum
: calculate the cumulative sum of double-precision floating-point strided array elements.@stdlib/blas-ext/base/gcusum
: calculate the cumulative sum of strided array elements.@stdlib/blas-ext/base/scusumpw
: calculate the cumulative sum of single-precision floating-point strided array elements using pairwise summation.
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For more information on the project, filing bug reports and feature requests, and guidance on how to develop stdlib, see the main project repository.
See LICENSE.
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