@stdlib/stats-base-scumin
v0.2.2
Published
Calculate the cumulative minimum of single-precision floating-point strided array elements.
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scumin
Calculate the cumulative minimum of single-precision floating-point strided array elements.
Installation
npm install @stdlib/stats-base-scumin
Usage
var scumin = require( '@stdlib/stats-base-scumin' );
scumin( N, x, strideX, y, strideY )
Computes the cumulative minimum 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 );
scumin( 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 minimum of every other element in x
,
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 = scumin( 4, x, 2, y, 1 );
// y => <Float32Array>[ 1.0, 1.0, -2.0, -2.0, 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
scumin( 4, x1, -2, y1, 1 );
// y0 => <Float32Array>[ 0.0, 0.0, 0.0, 4.0, 2.0, -2.0, -2.0, 0.0 ]
scumin.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )
Computes the cumulative minimum 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 );
scumin.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 minimum 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
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 );
scumin.ndarray( 4, x, 2, 1, y, -1, y.length-1 );
// y => <Float32Array>[ 0.0, 0.0, 0.0, 0.0, -2.0, -2.0, -2.0, 1.0 ]
Notes
- If
N <= 0
, both functions returny
unchanged.
Examples
var randu = require( '@stdlib/random-base-randu' );
var round = require( '@stdlib/math-base-special-round' );
var Float32Array = require( '@stdlib/array-float32' );
var scumin = require( '@stdlib/stats-base-scumin' );
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 );
scumin( x.length, x, 1, y, -1 );
console.log( y );
See Also
@stdlib/stats-base/cumin
: calculate the cumulative minimum of a strided array.@stdlib/stats-base/dcumin
: calculate the cumulative minimum of double-precision floating-point strided array elements.@stdlib/stats-base/scumax
: calculate the cumulative maximum of single-precision floating-point strided array elements.
Notice
This package is part of 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, see the main project repository.
Community
License
See LICENSE.
Copyright
Copyright © 2016-2024. The Stdlib Authors.