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Math::Vector::Real::kdTree(3pm) User Contributed Perl Documentation Math::Vector::Real::kdTree(3pm)

NAME

Math::Vector::Real::kdTree - kd-Tree implementation on top of Math::Vector::Real

SYNOPSIS

  use Math::Vector::Real::kdTree;
  use Math::Vector::Real;
  use Math::Vector::Real::Random;
  my @v = map Math::Vector::Real->random_normal(4), 1..1000;
  my $tree = Math::Vector::Real::kdTree->new(@v);
  my $ix = $tree->find_nearest_neighbor(V(0, 0, 0, 0));
  say "nearest neighbor is $ix, $v[$ix]";

DESCRIPTION

This module implements a kd-Tree data structure in Perl and some related algorithms.
The following methods are provided:
$t = Math::Vector::Real::kdTree->new(@points)
Creates a new kdTree containing the gived points.
$t->insert($p)
Inserts the given point into the kdTree.
$s = $t->size
Returns the number of points inside the tree.
$p = $t->at($ix)
Returns the point at the given index inside the tree.
$t->move($ix, $p)
Moves the point at index $ix to the new given position readjusting the tree structure accordingly.
($ix, $d) = $t->find_nearest_neighbor($p, $max_d, $but_ix)
Find the nearest neighbor for the given point $p and returns its index and the distance between the two points (in scalar context the index is returned).
 
If $max_d is defined, the search is limited to the points within that distance
 
If $but_ix is defined, the point with the given index is not considered.
@ix = $t->find_nearest_neighbor_all_internal
Returns the index of the nearest neighbor for every point inside the tree.
 
It is equivalent to (though, internally, it uses a better algorithm):
 
  @ix = map {
            scalar $t->nearest_neighbor($t->at($_), undef, $_)
        } 0..($t->size - 1);
@ix = $t->find_in_ball($z, $d, $but)
$n = $t->find_in_ball($z, $d, $but)
Finds the points inside the tree contained in the hypersphere with center $z and radius $d.
 
In scalar context returns the number of points found. In list context returns the indexes of the points.
 
If the extra argument $but is provided. The point with that index is ignored.
@ix = $t->ordered_by_proximity
Returns the indexes of the points in an ordered where is likely that the indexes of near vectors are also in near positions in the list.

SEE ALSO

http://en.wikipedia.org/wiki/K-d_tree <http://en.wikipedia.org/wiki/K-d_tree>
Math::Vector::Real

COPYRIGHT AND LICENSE

Copyright (C) 2011, 2012 by Salvador FandiA~Xo <sfandino@yahoo.com>
This library is free software; you can redistribute it and/or modify it under the same terms as Perl itself, either Perl version 5.12.3 or, at your option, any later version of Perl 5 you may have available.
2012-06-18 perl v5.14.2