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Revision: 1.2
Committed: Sun May 6 17:28:23 2001 UTC (23 years, 5 months ago) by root
Branch: MAIN
Changes since 1.1: +76 -11 lines
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# Content
1 package Tree::M;
2
3 use Carp;
4 use DynaLoader;
5
6 BEGIN {
7 $VERSION = 0.01;
8 @ISA = qw(DynaLoader);
9 bootstrap Tree::M, $VERSION;
10 }
11
12 =head1 NAME
13
14 Tree::M - implement M-trees for efficient "multimedia-searched"
15
16 =head1 SYNOPSIS
17
18 use Tree::M;
19
20 $M = new Tree::M
21
22 =head1 DESCRIPTION
23
24 (not yet)
25
26 Ever had the problem of managing multi-dimensional (spatial) data but your
27 database only had one-dimensional indices (b-tree etc.)? Queries like
28
29 select data from table where latitude > 40 and latitude < 50
30 and longitude> 50 and longitude< 60;
31
32 are quite inefficient, unless longitude and latitude are part of the same
33 spatial index (e.g. an R-tree).
34
35 An M-tree is an index tree that does not directly look at the stored keys
36 but rather requires a I<distance> (a metric, e.g. a vector norm) function
37 to be defined that sorts keys according to their distance. In the example
38 above the distance function could be the maximum norm (C<max(x1-x2,
39 y1-y2)>). The lookup above would then be something like this:
40
41 my $res = $M->range([45,55], 5);
42
43 This module implements an M-tree. Although the data structure and the
44 distance function is arbitrary, the current version only implements
45 n-dimensional discrete vectors and hardwires the distance function to the
46 suared euclidean metric (i.e. C<(x1-x2)**2 + (y1-y2)**2 + (z1-z2)**2 +
47 ...>). Evolution towards more freedom is expected ;)
48
49 =head2 THE Tree::M CLASS
50
51 =over 4
52
53 =item $M = new Tree::M ndims, min, max, steps
54
55 Creates a new M-Tree. Before it can be used you have to call one of the
56 C<create> or C<open> methods.
57
58 ndims the number of dimensions each vector has
59 min the lowest allowable scalar value in each dimension
60 max the maximum allowable number
61 steps the number of discrete steps (used when stored externally)
62
63 Example: create an M-Tree that stores 8-bit rgb-values:
64
65 $M = new Tree::M 3, 0, 255, 256;
66
67 Example: create an M-Tree that stores coordinates from -1..1 with 100 different steps:
68
69 $M = new Tree::M 2, -1, 1, 100;
70
71 =item $M->open(path)
72
73 =item $M->create($path)
74
75 Open or create the external storage file C<$path> and associate it with the tree.
76
77 [this braindamaged API will go away ;)]
78
79 =item $M->insert(\@v, $data)
80
81 Insert a vector (given by an array reference) into the index and associate
82 it with the value C<$data> (a 32-bit integer).
83
84 =item $res = $M->range(\@v, $radius)
85
86 Search all entries not farther away from C<@v> then C<$radius> and return
87 an arrayref containing the searchresults.
88
89 Each result is again anarrayref composed like this:
90
91 [\@v, $data]
92
93 e.g. the same as given to the C<insert> method.
94
95 =item $res = $M->top(\@v, $n)
96
97 Return the C<$n> "nearest neighbours". The results arrayref (see C<range>)
98 contains the C<$n> index values nearest to C<@v>, sorted for distance.
99
100 =item $distance = $M->distance(\@v1, \@v2)
101
102 Calculcate the distance between two vectors, just as they databse engine
103 would do it.
104
105 =item $depth = $M->maxlevel
106
107 Return the maximum height of the tree (usually a small integer specifying
108 the length of the path from the root to the farthest leaf)
109
110 =cut
111
112 =back
113
114 =head1 BUGS
115
116 Inserting too many duplicate keys into the tree cause the C++ library to
117 die, so don't do that.
118
119 =head1 AUTHOR
120
121 Marc Lehmann <pcg@goof.com>.
122
123 =head1 SEE ALSO
124
125 perl(1), L<DBIx::SpatialKeys>.
126
127 =cut
128
129 1;
130