https://github.com/titsuki/raku-algorithm-kdtree

A Raku binding for C implementation of the Kd-Tree Algorithm (https://github.com/jtsiomb/kdtree)
https://github.com/titsuki/raku-algorithm-kdtree

Last synced: 2 months ago
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A Raku binding for C implementation of the Kd-Tree Algorithm (https://github.com/jtsiomb/kdtree)

• Host: GitHub
• URL: https://github.com/titsuki/raku-algorithm-kdtree
• Owner: titsuki
• License: bsd-3-clause
• Created: 2016-03-06T05:06:11.000Z (almost 9 years ago)
• Default Branch: master
• Last Pushed: 2024-08-08T12:51:03.000Z (5 months ago)
• Last Synced: 2024-10-11T20:54:38.433Z (3 months ago)
• Language: C
• Homepage:
• Size: 46.9 KB
• Stars: 3
• Watchers: 2
• Forks: 2
• Open Issues: 1
• Metadata Files:
  • Readme: README.md
  • Changelog: Changes
  • License: LICENSE

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README

        
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NAME

====

Algorithm::KdTree - a Raku binding for C implementation of the Kd-Tree Algorithm (https://github.com/jtsiomb/kdtree)

SYNOPSIS

========

    use Algorithm::KdTree;

    my $kdtree = Algorithm::KdTree.new(3);

    $kdtree.insert: [0e0,0e0,0e0];

    $kdtree.insert: [10e0,10e0,10e0];

    my $nearest-response = $kdtree.nearest: [1e0,1e0,1e0];

    unless $nearest-response.is-end {

       $nearest-response.get-position.say; # [0e0, 0e0, 0e0]

    }

    my $range-response = $kdtree.nearest-range([9e0,9e0,9e0], sqrt(5));

    my @array;

    until $range-response.is-end {

       @array.push: $range-response.get-position;

       $range-response.next();

    }

    @array.perl.say; # [[10e0, 10e0, 10e0], ]

DESCRIPTION

===========

Algorithm::KdTree is a Raku binding for C implementation of the Kd-Tree Algorithm (https://github.com/jtsiomb/kdtree). Kd-Tree is the efficient algorithm for searching nearest neighbors in the k-dimensional space.

CONSTRUCTOR

-----------

### new(Int $dimension)

    my $kdtree = Algorithm::KdTree.new(3);

    my $kdtree = Algorithm::KdTree.new(256); # it could handle a huge dimensional space

Sets dimension `$dimension` for constructing `$dimension`-dimensional Kd-Tree.

METHODS

-------

### insert(@array)

    $kdtree.insert([1e0, 2e0, 3e0]);

Inserts a k-dimensional array.

### nearest(@array)

    my $response = $kdtree.nearest([1e0, 2e0, 3e0]);

    if (not $response.is-end()) {

	      my $position = $response.get-position();

    # YOUR CODE IS HERE

    # ...

    }

Returns a response which includes the nearest neighbor position of the query `@array` in the Kd-Tree. If the Kd-Tree has no elements, it returns a response which does not include any positions.

### nearest-range(@array, Num $radius)

    my $response = $kdtree.nearest-range([1e0, 2e0, 3e0], 10e0);

    while (not $response.is-end()) {

	      my $position = $response.get-position();

    # YOUR CODE IS HERE

    # ...

    $response.next();

    }

Returns a response which includes positions in the hypersphere. The center of this hypersphere is `@array` and the radius of this is `$radius`. If the Kd-Tree has no elements or no elements are found in the hypersphere, it returns a response which does not include any positions.

AUTHOR

======

titsuki 

COPYRIGHT AND LICENSE

=====================

Copyright 2016 titsuki

Copyright 2007-2011 John Tsiombikas 

This library is free software; you can redistribute it and/or modify it under the terms of the BSD 3-Clause License.

SEE ALSO

========

  * kdtree [https://github.com/jtsiomb/kdtree](https://github.com/jtsiomb/kdtree)