# scusum > Calculate the cumulative sum of single-precision floating-point strided array elements.
## Usage ```javascript var scusum = require( '@stdlib/blas/ext/base/scusum' ); ``` #### scusum( N, sum, x, strideX, y, strideY ) Computes the cumulative sum of single-precision floating-point strided array elements. ```javascript 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 => [ 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 => [ 11.0, 9.0, 11.0 ] ``` The function has the following parameters: - **N**: number of indexed elements. - **sum**: initial sum. - **x**: input [`Float32Array`][@stdlib/array/float32]. - **strideX**: index increment for `x`. - **y**: output [`Float32Array`][@stdlib/array/float32]. - **strideY**: index increment for `y`. The `N` and `stride` parameters determine which elements in `x` and `y` are accessed at runtime. For example, to compute the cumulative sum of every other element in `x`, ```javascript var Float32Array = require( '@stdlib/array/float32' ); var floor = require( '@stdlib/math/base/special/floor' ); 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 N = floor( x.length / 2 ); var v = scusum( N, 0.0, x, 2, y, 1 ); // y => [ 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`][mdn-typed-array] views. ```javascript var Float32Array = require( '@stdlib/array/float32' ); var floor = require( '@stdlib/math/base/special/floor' ); // 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 var N = floor( x0.length / 2 ); scusum( N, 0.0, x1, -2, y1, 1 ); // y0 => [ 0.0, 0.0, 0.0, 4.0, 6.0, 4.0, 5.0, 0.0 ] ``` #### scusum.ndarray( N, sum, x, strideX, offsetX, y, strideY, offsetY ) Computes the cumulative sum of single-precision floating-point strided array elements using 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 ); scusum.ndarray( x.length, 0.0, x, 1, 0, y, 1, 0 ); // y => [ 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`][mdn-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 `x` starting from the second value and to store in the last `N` elements of `y` starting from the last element ```javascript var Float32Array = require( '@stdlib/array/float32' ); var floor = require( '@stdlib/math/base/special/floor' ); 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 ); var N = floor( x.length / 2 ); scusum.ndarray( N, 0.0, x, 2, 1, y, -1, y.length-1 ); // y => [ 0.0, 0.0, 0.0, 0.0, 5.0, 1.0, -1.0, 1.0 ] ```
## Notes - If `N <= 0`, both functions return `y` unchanged.
## Examples ```javascript var randu = require( '@stdlib/random/base/randu' ); var round = require( '@stdlib/math/base/special/round' ); var Float32Array = require( '@stdlib/array/float32' ); var scusum = require( '@stdlib/blas/ext/base/scusum' ); var y; var x; var i; x = new Float32Array( 10 ); y = new Float32Array( x.length ); for ( i = 0; i < x.length; i++ ) { x[ i ] = round( randu()*100.0 ); } console.log( x ); console.log( y ); scusum( x.length, 0.0, x, 1, y, -1 ); console.log( y ); ```