dcuminabs

Calculate the cumulative minimum absolute value of double-precision floating-point strided array elements.

Usage

var dcuminabs = require( '@stdlib/stats/base/dcuminabs' );

dcuminabs( N, x, strideX, y, strideY )

Computes the cumulative minimum absolute value of double-precision floating-point strided array elements.

var Float64Array = require( '@stdlib/array/float64' );

var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );
var y = new Float64Array( x.length );

dcuminabs( x.length, x, 1, y, 1 );
// y => <Float64Array>[ 1.0, 1.0, 1.0 ]

The function has the following parameters:

  • N: number of indexed elements.
  • x: input Float64Array.
  • strideX: index increment for x.
  • y: output Float64Array.
  • 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 absolute value of every other element in x,

var Float64Array = require( '@stdlib/array/float64' );

var x = new Float64Array( [ 1.0, 2.0, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0 ] );
var y = new Float64Array( x.length );

var v = dcuminabs( 4, x, 2, y, 1 );
// y => <Float64Array>[ 1.0, 1.0, 1.0, 1.0, 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

dcuminabs( 4, x1, -2, y1, 1 );
// y0 => <Float64Array>[ 0.0, 0.0, 0.0, 4.0, 2.0, 2.0, 1.0, 0.0 ]

dcuminabs.ndarray( N, x, strideX, offsetX, y, strideY, offsetY )

Computes the cumulative minimum absolute value of double-precision floating-point strided array elements using alternative indexing semantics.

var Float64Array = require( '@stdlib/array/float64' );

var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );
var y = new Float64Array( x.length );

dcuminabs.ndarray( x.length, x, 1, 0, y, 1, 0 );
// y => <Float64Array>[ 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 minimum 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

var Float64Array = require( '@stdlib/array/float64' );

var x = new Float64Array( [ 2.0, 1.0, 2.0, -2.0, -2.0, 2.0, 3.0, 4.0 ] );
var y = new Float64Array( x.length );

dcuminabs.ndarray( 4, x, 2, 1, y, -1, y.length-1 );
// y => <Float64Array>[ 0.0, 0.0, 0.0, 0.0, 1.0, 1.0, 1.0, 1.0 ]

Notes

  • If N <= 0, both functions return y unchanged.

Examples

var randu = require( '@stdlib/random/base/randu' );
var round = require( '@stdlib/math/base/special/round' );
var Float64Array = require( '@stdlib/array/float64' );
var dcuminabs = require( '@stdlib/stats/base/dcuminabs' );

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) - 50.0 );
}
console.log( x );
console.log( y );

dcuminabs( x.length, x, 1, y, -1 );
console.log( y );