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    compute-minkowski-distance

    1.0.0 • Public • Published

    Minkowski Distance

    NPM version Build Status Coverage Status Dependencies

    Computes the Minkowski distance between two arrays.

    The Minkowski distance defines a distance between two points in a normed vector space.

    Minkowski distance formula

    Special cases:

    Installation

    $ npm install compute-minkowski-distance

    For use in the browser, use browserify.

    Usage

    var minkowski = require( 'compute-minkowski-distance' );

    minkowski( x, y, [opts] )

    Computes the Minkowski distance between two arrays.

    var x = [ 2, 4, 5, 3, 8, 2 ],
        y = [ 3, 1, 5, -3, 7, 2 ];
     
    var d = minkowski( x, y );
    // returns ~6.86

    The function accepts the following options:

    • p: norm order (p > 0).
    • accessor: accessor function for accessing array values.

    By default, the norm order is 2 (Euclidean distance). To specify a different order, set the p option.

    var x = [ 2, 4, 5, 3, 8, 2 ],
        y = [ 3, 1, 5, 3, 7, 2 ];
     
    var d = minkowski( x, y, {
        'p': 1
    });
    // returns 5

    For object arrays, provide an accessor function for accessing numeric values.

    var x = [
        {'x':2},
        {'x':4},
        {'x':5}
    ];
     
    var y = [
        [1,1],
        [2,2],
        [3,7]
    ];
     
    function getValue( d, i, j ) {
        if ( j === 0 ) {
            return d.x;
        }
        return d[ 1 ];
    }
     
    var dist = minkowski( x, y, {
        'accessor': getValue
    });
    // returns 3

    The accessor function is provided three arguments:

    • d: current datum.
    • i: current datum index.
    • j: array index; e.g., array x has index 0, and array y has index 1.

    If provided empty arrays, the function returns null.

    Notes

    Warning: only specific p values allow for proper consideration of overflow and underflow; i.e., Euclidean, Manhattan, and Chebyshev distances. In the general case, you may overflow for large p values.

    Examples

    var minkowski = require( 'compute-minkowski-distance' );
     
    var x = new Array( 100 ),
        y = new Array( 100 );
     
    for ( var i = 0; i < x.length; i++ ) {
        x[ i ] = Math.round( Math.random()*100 );
        y[ i ] = Math.round( Math.random()*100 );
    }
     
    // Euclidean distance (default):
    console.log( minkowski( x, y ) );
     
    // Manhattan (city block) distance:
    console.log( minkowski( x, y, {
        'p': 1
    }));
     
    // Chebyshev distance:
    console.log( minkowski( x, y, {
        'p': Number.POSITIVE_INFINITY
    }));
     
    // Some other distance:
    console.log( minkowski( x, y, {
        'p': 3
    }));

    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 © 2015. Philipp Burckhardt.

    Install

    npm i compute-minkowski-distance

    DownloadsWeekly Downloads

    11

    Version

    1.0.0

    License

    none

    Last publish

    Collaborators

    • kgryte
    • planeshifter