@stdlib/stats-incr-mmax NPM

incrmmax

Compute a moving maximum value incrementally.

Installation

npm install @stdlib/stats-incr-mmax

Usage

var incrmmax = require( '@stdlib/stats-incr-mmax' );

incrmmax( window )

Returns an accumulator function which incrementally computes a moving maximum value. The window parameter defines the number of values over which to compute the moving maximum.

var accumulator = incrmmax( 3 );

accumulator( [x] )

If provided an input value x, the accumulator function returns an updated maximum value. If not provided an input value x, the accumulator function returns the current maximum value.

var accumulator = incrmmax( 3 );

var m = accumulator();
// returns null

// Fill the window...
m = accumulator( 2.0 ); // [2.0]
// returns 2.0

m = accumulator( 1.0 ); // [2.0, 1.0]
// returns 2.0

m = accumulator( 3.0 ); // [2.0, 1.0, 3.0]
// returns 3.0

// Window begins sliding...
m = accumulator( -7.0 ); // [1.0, 3.0, -7.0]
// returns 3.0

m = accumulator( -5.0 ); // [3.0, -7.0, -5.0]
// returns 3.0

m = accumulator();
// returns 3.0

Notes

Input values are not type checked. If provided NaN, the accumulated value is NaN for at least W-1 future invocations. If non-numeric inputs are possible, you are advised to type check and handle accordingly before passing the value to the accumulator function.
As W values are needed to fill the window buffer, the first W-1 returned values are calculated from smaller sample sizes. Until the window is full, each returned value is calculated from all provided values.

Examples

var randu = require( '@stdlib/random-base-randu' );
var incrmmax = require( '@stdlib/stats-incr-mmax' );

var accumulator;
var v;
var i;

// Initialize an accumulator:
accumulator = incrmmax( 5 );

// For each simulated datum, update the moving maximum...
for ( i = 0; i < 100; i++ ) {
    v = randu() * 100.0;
    accumulator( v );
}
console.log( accumulator() );

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.