Package Exports

@stdlib/stats-base-dnanmskrange

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Readme

dnanmskrange

Calculate the range of a double-precision floating-point strided array according to a mask, ignoring NaN values.

The range is defined as the difference between the maximum and minimum values.

Installation

npm install @stdlib/stats-base-dnanmskrange

Usage

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

dnanmskrange( N, x, strideX, mask, strideMask )

Computes the range of a double-precision floating-point strided array x according to a mask, ignoring NaN values.

var Float64Array = require( '@stdlib/array-float64' );
var Uint8Array = require( '@stdlib/array-uint8' );

var x = new Float64Array( [ 1.0, -2.0, 4.0, 2.0, NaN ] );
var mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );

var v = dnanmskrange( x.length, x, 1, mask, 1 );
// returns 4.0

The function has the following parameters:

N: number of indexed elements.
x: input Float64Array.
strideX: index increment for x.
mask: mask Uint8Array. If a mask array element is 0, the corresponding element in x is considered valid and included in computation. If a mask array element is 1, the corresponding element in x is considered invalid/missing and excluded from computation.
strideMask: index increment for mask.

The N and stride parameters determine which elements are accessed at runtime. For example, to compute the range of every other element in x,

var Float64Array = require( '@stdlib/array-float64' );
var Uint8Array = require( '@stdlib/array-uint8' );
var floor = require( '@stdlib/math-base-special-floor' );

var x = new Float64Array( [ 1.0, 2.0, -7.0, -2.0, 4.0, 3.0, 5.0, 6.0 ] );
var mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1, 1 ] );
var N = floor( x.length / 2 );

var v = dnanmskrange( N, x, 2, mask, 2 );
// returns 11.0

Note that indexing is relative to the first index. To introduce offsets, use typed array views.

var Float64Array = require( '@stdlib/array-float64' );
var Uint8Array = require( '@stdlib/array-uint8' );
var floor = require( '@stdlib/math-base-special-floor' );

var x0 = new Float64Array( [ 2.0, 1.0, -2.0, -2.0, 3.0, 4.0, 5.0, 6.0 ] );
var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element

var mask0 = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1, 1 ] );
var mask1 = new Uint8Array( mask0.buffer, mask0.BYTES_PER_ELEMENT*1 ); // start at 2nd element

var N = floor( x0.length / 2 );

var v = dnanmskrange( N, x1, 2, mask1, 2 );
// returns 6.0

dnanmskrange.ndarray( N, x, strideX, offsetX, mask, strideMask, offsetMask )

Computes the range of a double-precision floating-point strided array according to a mask, ignoring NaN values and using alternative indexing semantics.

var Float64Array = require( '@stdlib/array-float64' );
var Uint8Array = require( '@stdlib/array-uint8' );

var x = new Float64Array( [ 1.0, -2.0, 4.0, 2.0, NaN ] );
var mask = new Uint8Array( [ 0, 0, 1, 0, 0 ] );

var v = dnanmskrange.ndarray( x.length, x, 1, 0, mask, 1, 0 );
// returns 4.0

The function has the following additional parameters:

offsetX: starting index for x.
offsetMask: starting index for mask.

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 range for every other value in x starting from the second value

var Float64Array = require( '@stdlib/array-float64' );
var Uint8Array = require( '@stdlib/array-uint8' );
var floor = require( '@stdlib/math-base-special-floor' );

var x = new Float64Array( [ 2.0, 1.0, -2.0, -2.0, 3.0, 4.0, 5.0, 6.0 ] );
var mask = new Uint8Array( [ 0, 0, 0, 0, 0, 0, 1, 1 ] );
var N = floor( x.length / 2 );

var v = dnanmskrange.ndarray( N, x, 2, 1, mask, 2, 1 );
// returns 6.0

Notes

If N <= 0, both functions return NaN.

Examples

var randu = require( '@stdlib/random-base-randu' );
var round = require( '@stdlib/math-base-special-round' );
var Float64Array = require( '@stdlib/array-float64' );
var Uint8Array = require( '@stdlib/array-uint8' );
var dnanmskrange = require( '@stdlib/stats-base-dnanmskrange' );

var mask;
var x;
var i;

x = new Float64Array( 10 );
mask = new Uint8Array( x.length );
for ( i = 0; i < x.length; i++ ) {
    if ( randu() < 0.2 ) {
        mask[ i ] = 1;
    } else {
        mask[ i ] = 0;
    }
    if ( randu() < 0.1 ) {
        x[ i ] = NaN;
    } else {
        x[ i ] = round( (randu()*100.0) - 50.0 );
    }
}
console.log( x );
console.log( mask );

var v = dnanmskrange( x.length, x, 1, mask, 1 );
console.log( v );

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.

License

See LICENSE.

@stdlib/stats-base-dnanmskrange