1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
|
.. Copyright (C) 2004-2009 The Trustees of Indiana University.
Use, modification and distribution is subject to the Boost Software
License, Version 1.0. (See accompanying file LICENSE_1_0.txt or copy at
http://www.boost.org/LICENSE_1_0.txt)
===================================
|Logo| R-MAT generator
===================================
::
template<typename RandomGenerator, typename Graph>
class rmat_iterator
{
public:
typedef std::input_iterator_tag iterator_category;
typedef std::pair<vertices_size_type, vertices_size_type> value_type;
typedef const value_type& reference;
typedef const value_type* pointer;
typedef void difference_type;
rmat_iterator();
rmat_iterator(RandomGenerator& gen, vertices_size_type n,
edges_size_type m, double a, double b, double c,
double d, bool permute_vertices = true);
// Iterator operations
reference operator*() const;
pointer operator->() const;
rmat_iterator& operator++();
rmat_iterator operator++(int);
bool operator==(const rmat_iterator& other) const;
bool operator!=(const rmat_iterator& other) const;
};
This class template implements a generator for R-MAT graphs [CZF04]_,
suitable for initializing an adjacency_list or other graph structure
with iterator-based initialization. An R-MAT graph has a scale-free
distribution w.r.t. vertex degree and is implemented using
Recursive-MATrix partitioning.
Where Defined
-------------
<``boost/graph/rmat_graph_generator.hpp``>
Constructors
------------
::
rmat_iterator();
Constructs a past-the-end iterator.
::
rmat_iterator(RandomGenerator& gen, vertices_size_type n,
edges_size_type m, double a, double b, double c,
double d, bool permute_vertices = true);
Constructs an R-MAT generator iterator that creates a graph with ``n``
vertices and ``m`` edges. ``a``, ``b``, ``c``, and ``d`` represent
the probability that a generated edge is placed of each of the 4
quadrants of the partitioned adjacency matrix. Probabilities are
drawn from the random number generator gen. Vertex indices are
permuted to eliminate locality when ``permute_vertices`` is true.
Example
-------
::
#include <boost/graph/adjacency_list.hpp>
#include <boost/graph/rmat_graph_generator.hpp>
#include <boost/random/linear_congruential.hpp>
typedef boost::adjacency_list<> Graph;
typedef boost::rmat_iterator<boost::minstd_rand, Graph> RMATGen;
int main()
{
boost::minstd_rand gen;
// Create graph with 100 nodes and 400 edges
Graph g(RMATGen(gen, 100, 400, 0.57, 0.19, 0.19, 0.05), RMATGen(), 100);
return 0;
}
Bibliography
------------
.. [CZF04] D Chakrabarti, Y Zhan, and C Faloutsos. R-MAT: A Recursive
Model for Graph Mining. In Proceedings of 4th International Conference
on Data Mining, pages 442--446, 2004.
-----------------------------------------------------------------------------
Copyright (C) 2009 The Trustees of Indiana University.
Authors: Nick Edmonds and Andrew Lumsdaine
.. |Logo| image:: pbgl-logo.png
:align: middle
:alt: Parallel BGL
:target: http://www.osl.iu.edu/research/pbgl
|
