dmidrange

Calculate the mid-range of a double-precision floating-point strided array.

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-base-dmidrange

Usage

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

dmidrange( N, x, stride )

Computes the mid-range of a double-precision floating-point strided array x.

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

var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );

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

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 mid-range 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, 2.0, -7.0, -2.0, 3.0, 4.0, 2.0 ] );
var N = floor( x.length / 2 );

var v = dmidrange( N, x, 2 );
// returns 1.0

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

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

var v = dmidrange( N, x1, 2 );
// returns 1.0

dmidrange.ndarray( N, x, stride, offset )

Computes the mid-range of a double-precision floating-point strided array using alternative indexing semantics.

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

var x = new Float64Array( [ 1.0, -2.0, 2.0 ] );

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

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 mid-range 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, -2.0, 2.0, 3.0, 4.0 ] );
var N = floor( x.length / 2 );

var v = dmidrange.ndarray( N, x, 2, 1 );
// returns 1.0

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

var x;
var i;

x = new Float64Array( 10 );
for ( i = 0; i < x.length; i++ ) {
    x[ i ] = round( (randu()*100.0) - 50.0 );
}
console.log( x );

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

See Also

• @stdlib/stats-base/dmax: calculate the maximum value of a double-precision floating-point strided array.
• @stdlib/stats-base/dmean: calculate the arithmetic mean of a double-precision floating-point strided array.
• @stdlib/stats-base/dmin: calculate the minimum value of a double-precision floating-point strided array.
• @stdlib/stats-base/drange: calculate the range of a double-precision floating-point strided array.
• @stdlib/stats-base/smidrange: calculate the mid-range of a single-precision floating-point strided array.

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.