mskmidrange

Calculate the mid-range of a strided array according to a mask.

The mid-range, or mid-extreme, is the arithmetic mean of the maximum and minimum values in a data set. The measure is the midpoint of the range and a measure of central tendency.

Installation

npm install @stdlib/stats-strided-mskmidrange

Usage

var mskmidrange = require( '@stdlib/stats-strided-mskmidrange' );

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

Computes the mid-range of a strided array according to a mask.

var x = [ 1.0, -2.0, 4.0, 2.0 ];
var mask = [ 0, 0, 1, 0 ];

var v = mskmidrange( x.length, x, 1, mask, 1 );
// returns 0.0

The function has the following parameters:

• N: number of indexed elements.
• x: input Array or typed array.
• strideX: stride length for x.
• mask: mask Array or typed array. 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: stride length for mask.

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

var x = [ 1.0, 2.0, -7.0, -2.0, 4.0, 3.0, 5.0, 6.0 ];
var mask = [ 0, 0, 0, 0, 0, 0, 1, 1 ];

var v = mskmidrange( 4, x, 2, mask, 2 );
// returns -1.5

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 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 v = mskmidrange( 4, x1, 2, mask1, 2 );
// returns 1.0

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

Computes the mid-range of a strided array according to a mask and using alternative indexing semantics.

var x = [ 1.0, -2.0, 4.0, 2.0 ];
var mask = [ 0, 0, 1, 0 ];

var v = mskmidrange.ndarray( x.length, x, 1, 0, mask, 1, 0 );
// returns 0.0

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 parameters support indexing semantics based on starting indices. For example, to calculate the mid-range of every other value in x starting from the second value

var x = [ 2.0, 1.0, -2.0, -2.0, 3.0, 4.0, 5.0, 6.0 ];
var mask = [ 0, 0, 0, 0, 0, 0, 1, 1 ];

var v = mskmidrange.ndarray( 4, x, 2, 1, mask, 2, 1 );
// returns 1.0

Notes

• If N <= 0, both functions return NaN.
• Depending on the environment, the typed versions (dmskmidrange, smskmidrange, etc.) are likely to be significantly more performant.
• Both functions support array-like objects having getter and setter accessors for array element access (e.g., @stdlib/array-base/accessor).

Examples

var uniform = require( '@stdlib/random-array-uniform' );
var bernoulli = require( '@stdlib/random-array-bernoulli' );
var mskmidrange = require( '@stdlib/stats-strided-mskmidrange' );

var x = uniform( 10, -50.0, 50.0, {
    'dtype': 'float64'
});
console.log( x );

var mask = bernoulli( x.length, 0.2, {
    'dtype': 'uint8'
});
console.log( mask );

var v = mskmidrange( 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.

Community

License

See LICENSE.

Copyright

Copyright © 2016-2026. The Stdlib Authors.