nanmidrangeBy

Calculate the mid-range of a strided array via a callback function, ignoring NaN values.

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-nanmidrange-by

Usage

var nanmidrangeBy = require( '@stdlib/stats-strided-nanmidrange-by' );

nanmidrangeBy( N, x, strideX, clbk[, thisArg] )

Computes the mid-range of a strided array via a callback function, ignoring NaN values.

function accessor( v ) {
    return v * 2.0;
}

var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0, NaN ];

var v = nanmidrangeBy( x.length, x, 1, accessor );
// returns -1.0

The function has the following parameters:

• N: number of indexed elements.
• x: input Array, typed array, or an array-like object (excluding strings and functions).
• strideX: stride length.
• clbk: callback function.
• thisArg: execution context (optional).

The invoked callback is provided four arguments:

• value: array element.
• aidx: array index.
• sidx: strided index (offset + aidx*stride).
• array: input array/collection.

To set the callback execution context, provide a thisArg.

function accessor( v ) {
    this.count += 1;
    return v * 2.0;
}

var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];

var context = {
    'count': 0
};

var v = nanmidrangeBy( x.length, x, 1, accessor, context );
// returns -1.0

var cnt = context.count;
// returns 8

The N and stride parameters determine which elements in the strided array are accessed at runtime. For example, to access every other element

function accessor( v ) {
    return v * 2.0;
}

var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0 ];

var v = nanmidrangeBy( 4, x, 2, accessor );
// returns 2.0

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

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

function accessor( v ) {
    return v * 2.0;
}

// Initial array...
var x0 = new Float64Array( [ 1.0, -2.0, 3.0, -4.0, 5.0, -6.0 ] );

// Create an offset view...
var x1 = new Float64Array( x0.buffer, x0.BYTES_PER_ELEMENT*1 ); // start at 2nd element

// Access every other element...
var v = nanmidrangeBy( 3, x1, 2, accessor );
// returns -8.0

nanmidrangeBy.ndarray( N, x, strideX, offsetX, clbk[, thisArg] )

Computes the mid-range of a strided array via a callback function, ignoring NaN values and using alternative indexing semantics.

function accessor( v ) {
    return v * 2.0;
}

var x = [ -2.0, 1.0, 3.0, -5.0, 4.0, 0.0, -1.0, -3.0, NaN ];

var v = nanmidrangeBy.ndarray( x.length, x, 1, 0, accessor );
// returns -1.0

The function has the following additional parameters:

• offsetX: starting index.

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 access only the last three elements of x

function accessor( v ) {
    return v * 2.0;
}

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

var v = nanmidrangeBy.ndarray( 3, x, 1, x.length-3, accessor );
// returns -1.0

Notes

• If N <= 0, both functions return NaN.
• A provided callback function should return a numeric value.
• If a provided callback function does not return any value (or equivalently, explicitly returns undefined), the value is ignored.
• Both functions support array-like objects having getter and setter accessors for array element access (e.g., @stdlib/array-base/accessor).
• When possible, prefer using dnanmidrange, snanmidrange, and/or nanmidrange, as, depending on the environment, these interfaces are likely to be significantly more performant.

Examples

var discreteUniform = require( '@stdlib/random-array-discrete-uniform' );
var nanmidrangeBy = require( '@stdlib/stats-strided-nanmidrange-by' );

function accessor( v ) {
    return v * 2.0;
}

var x = discreteUniform( 10, -50, 50, {
    'dtype': 'float64'
});
console.log( x );

var v = nanmidrangeBy( x.length, x, 1, accessor );
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.