Moving Sample Variance
!NPM versionnpm-imagenpm-url !Build Statustravis-imagetravis-url !Coverage Statuscoveralls-imagecoveralls-url !Dependenciesdependencies-imagedependencies-urlComputes 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 awindow
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