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Calculate the cumulative minimum of a strided array.
npm install @stdlib/stats-base-cumin
var cumin = require( '@stdlib/stats-base-cumin' );
Computes the cumulative minimum of a strided array.
var x = [ 1.0, -2.0, 2.0 ];
var y = [ 0.0, 0.0, 0.0 ];
cumin( x.length, x, 1, y, 1 );
// y => [ 1.0, -2.0, -2.0 ]
The function has the following parameters:
- N: number of indexed elements.
-
x: input
Array
ortyped array
. -
strideX: index increment for
x
. -
y: output
Array
ortyped array
. -
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 x = [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0 ];
var y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];
var v = cumin( 4, x, 2, y, 1 );
// y => [ 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 Float64Array = require( '@stdlib/array-float64' );
// Initial arrays...
var x0 = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] );
var y0 = new Float64Array( x0.length );
// Create offset views...
var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
var y1 = new Float64Array( y0.buffer, y0.BYTES_PER_ELEMENT*3 ); // start at 4th element
cumin( 4, x1, -2, y1, 1 );
// y0 => <Float64Array>[ 0.0, 0.0, 0.0, 4.0, 2.0, -2.0, -2.0, 0.0 ]
Computes the cumulative minimum of a strided array using alternative indexing semantics.
var x = [ 1.0, -2.0, 2.0 ];
var y = [ 0.0, 0.0, 0.0 ];
cumin.ndarray( x.length, x, 1, 0, y, 1, 0 );
// y => [ 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 x = [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ];
var y = [ 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0 ];
cumin.ndarray( 4, x, 2, 1, y, -1, y.length-1 );
// y => [ 0.0, 0.0, 0.0, 0.0, -2.0, -2.0, -2.0, 1.0 ]
var randu = require( '@stdlib/random-base-randu' );
var round = require( '@stdlib/math-base-special-round' );
var Float64Array = require( '@stdlib/array-float64' );
var cumin = require( '@stdlib/stats-base-cumin' );
var y;
var x;
var i;
x = new Float64Array( 10 );
y = new Float64Array( x.length );
for ( i = 0; i < x.length; i++ ) {
x[ i ] = round( randu()*100.0 );
}
console.log( x );
console.log( y );
cumin( x.length, x, 1, y, -1 );
console.log( y );
-
@stdlib/stats-base/cumax
: calculate the cumulative maximum of a strided array. -
@stdlib/stats-base/dcumin
: calculate the cumulative minimum of double-precision floating-point strided array elements. -
@stdlib/stats-base/scumin
: calculate the cumulative minimum of single-precision floating-point strided array elements.
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.
See LICENSE.
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