@stdlib/stats-base-snanmax
v0.2.2
Published
Calculate the maximum value of a single-precision floating-point strided array, ignoring NaN values.
Downloads
198
Readme
snanmax
Calculate the maximum value of a single-precision floating-point strided array, ignoring
NaN
values.
Installation
npm install @stdlib/stats-base-snanmax
Usage
var snanmax = require( '@stdlib/stats-base-snanmax' );
snanmax( N, x, stride )
Computes the maximum value of a single-precision floating-point strided array x
, ignoring NaN
values.
var Float32Array = require( '@stdlib/array-float32' );
var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );
var N = x.length;
var v = snanmax( N, x, 1 );
// returns 2.0
The function has the following parameters:
- N: number of indexed elements.
- x: input
Float32Array
. - 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 value of every other element in x
,
var Float32Array = require( '@stdlib/array-float32' );
var floor = require( '@stdlib/math-base-special-floor' );
var x = new Float32Array( [ 1.0, 2.0, -7.0, -2.0, 4.0, 3.0, NaN, NaN ] );
var N = floor( x.length / 2 );
var v = snanmax( N, x, 2 );
// returns 4.0
Note that indexing is relative to the first index. To introduce an offset, use typed array
views.
var Float32Array = require( '@stdlib/array-float32' );
var floor = require( '@stdlib/math-base-special-floor' );
var x0 = new Float32Array( [ 2.0, 1.0, -2.0, -2.0, 3.0, 4.0, NaN, NaN ] );
var x1 = new Float32Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element
var N = floor( x0.length / 2 );
var v = snanmax( N, x1, 2 );
// returns 4.0
snanmax.ndarray( N, x, stride, offset )
Computes the maximum value of a single-precision floating-point strided array, ignoring NaN
values and using alternative indexing semantics.
var Float32Array = require( '@stdlib/array-float32' );
var x = new Float32Array( [ 1.0, -2.0, NaN, 2.0 ] );
var N = x.length;
var v = snanmax.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 value for every other value in x
starting from the second value
var Float32Array = require( '@stdlib/array-float32' );
var floor = require( '@stdlib/math-base-special-floor' );
var x = new Float32Array( [ 2.0, 1.0, -2.0, -2.0, 3.0, 4.0, NaN, NaN ] );
var N = floor( x.length / 2 );
var v = snanmax.ndarray( N, x, 2, 1 );
// returns 4.0
Notes
- If
N <= 0
, both functions returnNaN
.
Examples
var randu = require( '@stdlib/random-base-randu' );
var round = require( '@stdlib/math-base-special-round' );
var Float32Array = require( '@stdlib/array-float32' );
var snanmax = require( '@stdlib/stats-base-snanmax' );
var x;
var i;
x = new Float32Array( 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 = snanmax( x.length, x, 1 );
console.log( v );
See Also
@stdlib/stats-base/dnanmax
: calculate the maximum value of a double-precision floating-point strided array, ignoring NaN values.@stdlib/stats-base/nanmax
: calculate the maximum value of a strided array, ignoring NaN values.@stdlib/stats-base/smax
: calculate the maximum value of a single-precision floating-point strided array.@stdlib/stats-base/snanmin
: calculate the minimum value of a single-precision floating-point strided array, ignoring NaN values.
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.