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mediansorted

Calculate the median value of a sorted strided array.

Installation

npm install @stdlib/stats-base-mediansorted

Alternatively,

• To load the package in a website via a script tag without installation and bundlers, use the ES Module available on the esm branch (see README).
• If you are using Deno, visit the deno branch (see README for usage intructions).
• For use in Observable, or in browser/node environments, use the Universal Module Definition (UMD) build available on the umd branch (see README).

The branches.md file summarizes the available branches and displays a diagram illustrating their relationships.

To view installation and usage instructions specific to each branch build, be sure to explicitly navigate to the respective README files on each branch, as linked to above.

Usage

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

mediansorted( N, x, stride )

Computes the median value of a sorted strided array x.

var x = [ 1.0, 2.0, 3.0 ];
var v = mediansorted( x.length, x, 1 );
// returns 2.0

x = [ 3.0, 2.0, 1.0 ];
v = mediansorted( x.length, x, 1 );
// returns 2.0

The function has the following parameters:

• N: number of indexed elements.
• x: input Array or typed array.
• stride: index increment for x.

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

var floor = require( '@stdlib/math-base-special-floor' );

var x = [ 1.0, 2.0, 2.0, -7.0, 3.0, 3.0, 4.0, 2.0 ];
var N = floor( x.length / 2 );

var v = mediansorted( N, x, 2 );
// returns 2.5

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 = mediansorted( N, x1, 2 );
// returns 2.0

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

Computes the median value of a sorted strided array using alternative indexing semantics.

var x = [ 1.0, 2.0, 3.0 ];

var v = mediansorted.ndarray( x.length, 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 median value for every other value in x starting from the second value

var floor = require( '@stdlib/math-base-special-floor' );

var x = [ 2.0, 1.0, 2.0, 2.0, -2.0, 2.0, 3.0, 4.0 ];
var N = floor( x.length / 2 );

var v = mediansorted.ndarray( N, x, 2, 1 );
// returns 2.0

Notes

• If N <= 0, both functions return NaN.
• The input strided array must be sorted in either strictly ascending or descending order.

Examples

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

var x;
var i;

x = new Float64Array( 10 );
for ( i = 0; i < x.length; i++ ) {
    x[ i ] = i - 5.0;
}
console.log( x );

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

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See Also

• @stdlib/stats-base/dmediansorted: calculate the median value of a sorted double-precision floating-point strided array.
• @stdlib/stats-base/mean: calculate the arithmetic mean of a strided array.
• @stdlib/stats-base/smediansorted: calculate the median value of a sorted single-precision floating-point strided array.

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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

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License

See LICENSE.

Copyright

Copyright © 2016-2024. The Stdlib Authors.