compute-mvariance

Computes a moving sample variance over a numeric array.

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Moving Sample Variance
!NPM versionnpm-imagenpm-url !Build Statustravis-imagetravis-url !Coverage Statuscoveralls-imagecoveralls-url !Dependenciesdependencies-imagedependencies-url
Computes a moving (sliding window) sample variance over a numeric array.

Installation

$ npm install compute-mvariance

For use in the browser, use browserify.

Usage

To use the module,
var mvariance = require( 'compute-mvariance' );

mvariance( arr, window )

Slides a window over a numeric array to compute a moving sample variance.
var data = [ 1, 5, 0, 10, 2 ];

var arr = mvariance( data, 3 );
// returns [ 7, 25, 28 ]

Note: the returned array has length L - W + 1, where L is the length of the input array and W is the window size.

Examples

var mvariance = require( 'compute-mvariance' );

// Simulate some data...
var data = new Array( 50 );

for ( var i = 0; i < data.length; i++ ) {
	data[ i ] = Math.random() * 100;
}

// Compute the moving sample variance:
var arr = mvariance( data, 7 );

console.log( arr.join( '\n' ) );

To run the example code from the top-level application directory,
$ node ./examples/index.js

Tests

Unit

Unit tests use the Mocha test framework with Chai assertions. To run the tests, execute the following command in the top-level application directory:
$ make test

All new feature development should have corresponding unit tests to validate correct functionality.

Test Coverage

This repository uses Istanbul as its code coverage tool. To generate a test coverage report, execute the following command in the top-level application directory:
$ make test-cov

Istanbul creates a ./reports/coverage directory. To access an HTML version of the report,
$ make view-cov

License

MIT license.

Copyright

Copyright © 2014. Athan Reines.