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Calculate the cumulative maximum absolute value of single-precision floating-point strided array elements.
import scumaxabs from 'https://cdn.jsdelivr.net/gh/stdlib-js/stats-base-scumaxabs@deno/mod.js';
Computes the cumulative maximum absolute value of single-precision floating-point strided array elements.
import Float32Array from 'https://cdn.jsdelivr.net/gh/stdlib-js/array-float32@deno/mod.js';
var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );
var y = new Float32Array( x.length );
scumaxabs( x.length, x, 1, y, 1 );
// y => <Float32Array>[ 1.0, 2.0, 2.0 ]
The function has the following parameters:
- N: number of indexed elements.
- 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 x
and y
are accessed at runtime. For example, to compute the cumulative maximum absolute value of every other element in x
,
import Float32Array from 'https://cdn.jsdelivr.net/gh/stdlib-js/array-float32@deno/mod.js';
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 = scumaxabs( 4, x, 2, y, 1 );
// y => <Float32Array>[ 1.0, 2.0, 2.0, 4.0, 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.
import Float32Array from 'https://cdn.jsdelivr.net/gh/stdlib-js/array-float32@deno/mod.js';
// 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
scumaxabs( 4, x1, -2, y1, 1 );
// y0 => <Float32Array>[ 0.0, 0.0, 0.0, 4.0, 4.0, 4.0, 4.0, 0.0 ]
Computes the cumulative maximum absolute value of single-precision floating-point strided array elements using alternative indexing semantics.
import Float32Array from 'https://cdn.jsdelivr.net/gh/stdlib-js/array-float32@deno/mod.js';
var x = new Float32Array( [ 1.0, -2.0, 2.0 ] );
var y = new Float32Array( x.length );
scumaxabs.ndarray( x.length, x, 1, 0, y, 1, 0 );
// y => <Float32Array>[ 1.0, 2.0, 2.0 ]
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 maximum absolute value 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
import Float32Array from 'https://cdn.jsdelivr.net/gh/stdlib-js/array-float32@deno/mod.js';
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 );
scumaxabs.ndarray( 4, x, 2, 1, y, -1, y.length-1 );
// y => <Float32Array>[ 0.0, 0.0, 0.0, 0.0, 4.0, 2.0, 2.0, 1.0 ]
- If
N <= 0
, both functions returny
unchanged.
import randu from 'https://cdn.jsdelivr.net/gh/stdlib-js/random-base-randu@deno/mod.js';
import round from 'https://cdn.jsdelivr.net/gh/stdlib-js/math-base-special-round@deno/mod.js';
import Float32Array from 'https://cdn.jsdelivr.net/gh/stdlib-js/array-float32@deno/mod.js';
import scumaxabs from 'https://cdn.jsdelivr.net/gh/stdlib-js/stats-base-scumaxabs@deno/mod.js';
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) - 50.0 );
}
console.log( x );
console.log( y );
scumaxabs( x.length, x, 1, y, -1 );
console.log( y );
@stdlib/stats-base/cumaxabs
: calculate the cumulative maximum absolute value of a strided array.@stdlib/stats-base/dcumaxabs
: calculate the cumulative maximum absolute value of double-precision floating-point strided array elements.@stdlib/stats-base/scumax
: calculate the cumulative maximum of single-precision floating-point strided array elements.@stdlib/stats-base/scuminabs
: calculate the cumulative minimum absolute value of single-precision floating-point strided array elements.
This package is part of stdlib, a standard library 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, see the main project repository.
See LICENSE.
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