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- <Head>
- <Title>Boost Graph Library: Power Law Out Degree (PLOD) Generator</Title>
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- <tt>plod_iterator</tt>
- <br>
- <PRE>
- template<typename RandomGenerator, typename Graph>
- class plod_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;
- plod_iterator();
- plod_iterator(RandomGenerator& gen, vertices_size_type n,
- double alpha, double beta, bool allow_self_loops = false);
- // Iterator operations
- reference operator*() const;
- pointer operator->() const;
- plod_iterator& operator++();
- plod_iterator operator++(int);
- bool operator==(const plod_iterator& other) const;
- bool operator!=(const plod_iterator& other) const;
- };
- </PRE>
- <p> This class template implements a generator for scale-free graphs
- using the Power Law Out Degree (PLOD) algorithm
- [<a href="bibliography.html#palmer2000">63</a>], suitable for
- initializing an <a
- href="adjacency_list.html"><tt>adjacency_list</tt></a> or other graph
- structure with iterator-based initialization. A scale-free graph
- typically has a very skewed degree distribution, where few vertices
- have a very high degree and a large number of vertices have a very
- small degree. Many naturally evolving networks, such as the World
- Wide Web, are scale-free graphs, making these graphs a good model for
- certain networking problems.</p>
- <p>The Power Law Out Degree (PLOD) algorithm generates a scale-free
- graph from three parameters, <em>n</em>, <em>alpha</em>, and
- <em>beta</em>, by allocating a certain number of degree "credits" to
- each vertex, drawn from a power-law distribution. It then creates
- edges between vertices, deducting a credit from each involved vertex
- (in the undirected case) or the source vertex (in the directed
- case). The number of credits assigned to a vertex is:
- <em>beta*x<sup>-alpha</sup></em>, where <em>x</em> is a random value
- between 0 and <em>n-1</em>. The value of <em>beta</em> controls the
- y-intercept of the curve, so that increasing <em>beta</em> increases
- the average degree of vertices. The value of <em>alpha</em> controls
- how steeply the curve drops off, with larger values indicating a
- steeper curve. The web graph, for instance, has <em>alpha ~
- 2.72</em>.</p>
- <h3>Where Defined</h3>
- <a href="../../../boost/graph/plod_generator.hpp"><tt>boost/graph/plod_generator.hpp</tt></a>
- <h3>Constructors</h3>
- <a name="default-constructor"/>
- <pre>plod_iterator();</pre>
- <blockquote>
- Constructs a past-the-end iterator.
- </blockquote>
- <pre>
- plod_iterator(RandomGenerator& gen, vertices_size_type n,
- double alpha, double beta, bool allow_self_loops = false);
- </pre>
- <blockquote>
- Constructs a PLOD generator iterator that creates a
- graph with <tt>n</tt> vertices. Probabilities are drawn from the
- random number generator <tt>gen</tt>. Self-loops are permitted only
- when <tt>allow_self_loops</tt> is <tt>true</tt>.
- </blockquote>
- <H3>Example</H3>
- <pre>
- #include <boost/graph/adjacency_list.hpp>
- #include <boost/graph/plod_generator.hpp>
- #include <boost/random/linear_congruential.hpp>
- typedef boost::adjacency_list<> Graph;
- typedef boost::plod_iterator<boost::minstd_rand, Graph> SFGen;
- int main()
- {
- boost::minstd_rand gen;
- // Create graph with 100 nodes
- Graph g(SFGen(gen, 100, 2.5, 1000), SFGen(), 100);
- return 0;
- }
- </pre>
- <br>
- <HR>
- <TABLE>
- <TR valign=top>
- <TD nowrap>Copyright © 2005</TD><TD>
- <A HREF="http://www.boost.org/people/doug_gregor.html">Doug Gregor</A>, Indiana University (<script language="Javascript">address("cs.indiana.edu", "dgregor")</script>)<br>
- <A HREF="https://homes.cs.washington.edu/~al75">Andrew Lumsdaine</A>,
- Indiana University (<script language="Javascript">address("osl.iu.edu", "lums")</script>)
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