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Calculate the maximum absolute value of a double-precision floating-point strided array, ignoring
NaN
values.
npm install @stdlib/stats-base-dnanmaxabs
var dnanmaxabs = require( '@stdlib/stats-base-dnanmaxabs' );
Computes the maximum absolute value of a double-precision floating-point strided array x
, ignoring NaN
values.
var Float64Array = require( '@stdlib/array-float64' );
var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );
var N = x.length;
var v = dnanmaxabs( N, x, 1 );
// returns 2.0
The function has the following parameters:
- N: number of indexed elements.
-
x: input
Float64Array
. -
stride: index increment for
x
.
The N
and stride
parameters determine which elements in x
are accessed at runtime. For example, to compute the maximum absolute value of every other element in x
,
var Float64Array = require( '@stdlib/array-float64' );
var floor = require( '@stdlib/math-base-special-floor' );
var x = new Float64Array( [ 1.0, 2.0, -7.0, -2.0, 4.0, 3.0, NaN, NaN ] );
var N = floor( x.length / 2 );
var v = dnanmaxabs( N, x, 2 );
// returns 7.0
Note that indexing is relative to the first index. To introduce an offset, use typed array
views.
var Float64Array = require( '@stdlib/array-float64' );
var floor = require( '@stdlib/math-base-special-floor' );
var x0 = new Float64Array( [ 2.0, 1.0, -2.0, -2.0, 3.0, 4.0, NaN, NaN ] );
var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
var N = floor( x0.length / 2 );
var v = dnanmaxabs( N, x1, 2 );
// returns 4.0
Computes the maximum absolute value of a double-precision floating-point strided array, ignoring NaN
values and using alternative indexing semantics.
var Float64Array = require( '@stdlib/array-float64' );
var x = new Float64Array( [ 1.0, -2.0, NaN, 2.0 ] );
var N = x.length;
var v = dnanmaxabs.ndarray( N, x, 1, 0 );
// returns 2.0
The function has the following additional parameters:
-
offset: starting index for
x
.
While typed array
views mandate a view offset based on the underlying buffer
, the offset
parameter supports indexing semantics based on a starting index. For example, to calculate the maximum absolute value for every other value in x
starting from the second value
var Float64Array = require( '@stdlib/array-float64' );
var floor = require( '@stdlib/math-base-special-floor' );
var x = new Float64Array( [ 2.0, 1.0, -2.0, -2.0, 3.0, 4.0, NaN, NaN ] );
var N = floor( x.length / 2 );
var v = dnanmaxabs.ndarray( N, x, 2, 1 );
// returns 4.0
- If
N <= 0
, both functions returnNaN
.
var randu = require( '@stdlib/random-base-randu' );
var round = require( '@stdlib/math-base-special-round' );
var Float64Array = require( '@stdlib/array-float64' );
var dnanmaxabs = require( '@stdlib/stats-base-dnanmaxabs' );
var x;
var i;
x = new Float64Array( 10 );
for ( i = 0; i < x.length; i++ ) {
if ( randu() < 0.2 ) {
x[ i ] = NaN;
} else {
x[ i ] = round( (randu()*100.0) - 50.0 );
}
}
console.log( x );
var v = dnanmaxabs( x.length, x, 1 );
console.log( v );
-
@stdlib/stats-base/dmaxabs
: calculate the maximum absolute value of a double-precision floating-point strided array. -
@stdlib/stats-base/dnanmax
: calculate the maximum value of a double-precision floating-point strided array, ignoring NaN values. -
@stdlib/stats-base/dnanminabs
: calculate the minimum absolute value of a double-precision floating-point strided array, ignoring NaN values. -
@stdlib/stats-base/nanmaxabs
: calculate the maximum absolute value of a strided array, ignoring NaN values. -
@stdlib/stats-base/snanmaxabs
: calculate the maximum absolute value of a single-precision floating-point strided array, ignoring NaN values.
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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