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Added thirdparty: boost library
This commit is contained in:
Viacheslav Demydiuk
+645
@@ -0,0 +1,645 @@
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// Copyright 2004 The Trustees of Indiana University.
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// Distributed under the Boost Software License, Version 1.0.
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// (See accompanying file LICENSE_1_0.txt or copy at
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// http://www.boost.org/LICENSE_1_0.txt)
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// Authors: Douglas Gregor
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// Andrew Lumsdaine
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#ifndef BOOST_GRAPH_BRANDES_BETWEENNESS_CENTRALITY_HPP
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#define BOOST_GRAPH_BRANDES_BETWEENNESS_CENTRALITY_HPP
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#include <stack>
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#include <vector>
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#include <boost/graph/overloading.hpp>
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#include <boost/graph/dijkstra_shortest_paths.hpp>
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#include <boost/graph/breadth_first_search.hpp>
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#include <boost/graph/relax.hpp>
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#include <boost/graph/graph_traits.hpp>
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#include <boost/tuple/tuple.hpp>
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#include <boost/type_traits/is_convertible.hpp>
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#include <boost/type_traits/is_same.hpp>
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#include <boost/mpl/if.hpp>
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#include <boost/property_map/property_map.hpp>
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#include <boost/graph/named_function_params.hpp>
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#include <algorithm>
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namespace boost
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{
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namespace detail
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{
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namespace graph
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{
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/**
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* Customized visitor passed to Dijkstra's algorithm by Brandes'
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* betweenness centrality algorithm. This visitor is responsible for
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* keeping track of the order in which vertices are discovered, the
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* predecessors on the shortest path(s) to a vertex, and the number
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* of shortest paths.
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*/
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template < typename Graph, typename WeightMap, typename IncomingMap,
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typename DistanceMap, typename PathCountMap >
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struct brandes_dijkstra_visitor : public bfs_visitor<>
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{
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typedef typename graph_traits< Graph >::vertex_descriptor
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vertex_descriptor;
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typedef
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typename graph_traits< Graph >::edge_descriptor edge_descriptor;
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brandes_dijkstra_visitor(
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std::stack< vertex_descriptor >& ordered_vertices,
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WeightMap weight, IncomingMap incoming, DistanceMap distance,
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PathCountMap path_count)
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: ordered_vertices(ordered_vertices)
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, weight(weight)
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, incoming(incoming)
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, distance(distance)
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, path_count(path_count)
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{
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}
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/**
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* Whenever an edge e = (v, w) is relaxed, the incoming edge list
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* for w is set to {(v, w)} and the shortest path count of w is set
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* to the number of paths that reach {v}.
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*/
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void edge_relaxed(edge_descriptor e, const Graph& g)
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{
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vertex_descriptor v = source(e, g), w = target(e, g);
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incoming[w].clear();
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incoming[w].push_back(e);
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put(path_count, w, get(path_count, v));
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}
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/**
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* If an edge e = (v, w) was not relaxed, it may still be the case
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* that we've found more equally-short paths, so include {(v, w)} in
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* the incoming edges of w and add all of the shortest paths to v to
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* the shortest path count of w.
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*/
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void edge_not_relaxed(edge_descriptor e, const Graph& g)
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{
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typedef typename property_traits< WeightMap >::value_type
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weight_type;
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typedef typename property_traits< DistanceMap >::value_type
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distance_type;
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vertex_descriptor v = source(e, g), w = target(e, g);
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distance_type d_v = get(distance, v), d_w = get(distance, w);
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weight_type w_e = get(weight, e);
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closed_plus< distance_type > combine;
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if (d_w == combine(d_v, w_e))
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{
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put(path_count, w, get(path_count, w) + get(path_count, v));
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incoming[w].push_back(e);
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}
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}
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/// Keep track of vertices as they are reached
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void examine_vertex(vertex_descriptor w, const Graph&)
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{
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ordered_vertices.push(w);
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}
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private:
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std::stack< vertex_descriptor >& ordered_vertices;
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WeightMap weight;
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IncomingMap incoming;
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DistanceMap distance;
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PathCountMap path_count;
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};
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/**
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* Function object that calls Dijkstra's shortest paths algorithm
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* using the Dijkstra visitor for the Brandes betweenness centrality
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* algorithm.
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*/
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template < typename WeightMap > struct brandes_dijkstra_shortest_paths
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{
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brandes_dijkstra_shortest_paths(WeightMap weight_map)
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: weight_map(weight_map)
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{
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}
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template < typename Graph, typename IncomingMap,
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typename DistanceMap, typename PathCountMap,
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typename VertexIndexMap >
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void operator()(Graph& g,
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typename graph_traits< Graph >::vertex_descriptor s,
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std::stack< typename graph_traits< Graph >::vertex_descriptor >&
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ov,
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IncomingMap incoming, DistanceMap distance,
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PathCountMap path_count, VertexIndexMap vertex_index)
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{
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typedef brandes_dijkstra_visitor< Graph, WeightMap, IncomingMap,
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DistanceMap, PathCountMap >
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visitor_type;
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visitor_type visitor(
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ov, weight_map, incoming, distance, path_count);
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dijkstra_shortest_paths(g, s,
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boost::weight_map(weight_map)
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.vertex_index_map(vertex_index)
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.distance_map(distance)
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.visitor(visitor));
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}
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private:
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WeightMap weight_map;
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};
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/**
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* Function object that invokes breadth-first search for the
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* unweighted form of the Brandes betweenness centrality algorithm.
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*/
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struct brandes_unweighted_shortest_paths
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{
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/**
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* Customized visitor passed to breadth-first search, which
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* records predecessor and the number of shortest paths to each
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* vertex.
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*/
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template < typename Graph, typename IncomingMap,
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typename DistanceMap, typename PathCountMap >
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struct visitor_type : public bfs_visitor<>
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{
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typedef typename graph_traits< Graph >::edge_descriptor
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edge_descriptor;
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typedef typename graph_traits< Graph >::vertex_descriptor
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vertex_descriptor;
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visitor_type(IncomingMap incoming, DistanceMap distance,
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PathCountMap path_count,
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std::stack< vertex_descriptor >& ordered_vertices)
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: incoming(incoming)
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, distance(distance)
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, path_count(path_count)
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, ordered_vertices(ordered_vertices)
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{
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}
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/// Keep track of vertices as they are reached
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void examine_vertex(vertex_descriptor v, Graph&)
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{
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ordered_vertices.push(v);
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}
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/**
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* Whenever an edge e = (v, w) is labelled a tree edge, the
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* incoming edge list for w is set to {(v, w)} and the shortest
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* path count of w is set to the number of paths that reach {v}.
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*/
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void tree_edge(edge_descriptor e, Graph& g)
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{
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vertex_descriptor v = source(e, g);
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vertex_descriptor w = target(e, g);
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put(distance, w, get(distance, v) + 1);
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put(path_count, w, get(path_count, v));
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incoming[w].push_back(e);
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}
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/**
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* If an edge e = (v, w) is not a tree edge, it may still be the
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* case that we've found more equally-short paths, so include
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* (v, w) in the incoming edge list of w and add all of the
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* shortest paths to v to the shortest path count of w.
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*/
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void non_tree_edge(edge_descriptor e, Graph& g)
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{
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vertex_descriptor v = source(e, g);
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vertex_descriptor w = target(e, g);
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if (get(distance, w) == get(distance, v) + 1)
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{
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put(path_count, w,
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get(path_count, w) + get(path_count, v));
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incoming[w].push_back(e);
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}
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}
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private:
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IncomingMap incoming;
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DistanceMap distance;
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PathCountMap path_count;
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std::stack< vertex_descriptor >& ordered_vertices;
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};
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template < typename Graph, typename IncomingMap,
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typename DistanceMap, typename PathCountMap,
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typename VertexIndexMap >
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void operator()(Graph& g,
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typename graph_traits< Graph >::vertex_descriptor s,
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std::stack< typename graph_traits< Graph >::vertex_descriptor >&
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ov,
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IncomingMap incoming, DistanceMap distance,
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PathCountMap path_count, VertexIndexMap vertex_index)
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{
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typedef typename graph_traits< Graph >::vertex_descriptor
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vertex_descriptor;
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visitor_type< Graph, IncomingMap, DistanceMap, PathCountMap >
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visitor(incoming, distance, path_count, ov);
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std::vector< default_color_type > colors(num_vertices(g),
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color_traits< default_color_type >::white());
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boost::queue< vertex_descriptor > Q;
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breadth_first_visit(g, s, Q, visitor,
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make_iterator_property_map(colors.begin(), vertex_index));
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}
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};
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// When the edge centrality map is a dummy property map, no
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// initialization is needed.
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template < typename Iter >
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inline void init_centrality_map(
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std::pair< Iter, Iter >, dummy_property_map)
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{
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}
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// When we have a real edge centrality map, initialize all of the
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// centralities to zero.
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template < typename Iter, typename Centrality >
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void init_centrality_map(
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std::pair< Iter, Iter > keys, Centrality centrality_map)
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{
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typedef typename property_traits< Centrality >::value_type
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centrality_type;
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while (keys.first != keys.second)
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{
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put(centrality_map, *keys.first, centrality_type(0));
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++keys.first;
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}
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}
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// When the edge centrality map is a dummy property map, no update
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// is performed.
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template < typename Key, typename T >
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inline void update_centrality(dummy_property_map, const Key&, const T&)
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{
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}
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// When we have a real edge centrality map, add the value to the map
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template < typename CentralityMap, typename Key, typename T >
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inline void update_centrality(
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CentralityMap centrality_map, Key k, const T& x)
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{
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put(centrality_map, k, get(centrality_map, k) + x);
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}
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template < typename Iter >
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inline void divide_centrality_by_two(
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std::pair< Iter, Iter >, dummy_property_map)
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{
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}
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template < typename Iter, typename CentralityMap >
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inline void divide_centrality_by_two(
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std::pair< Iter, Iter > keys, CentralityMap centrality_map)
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{
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typename property_traits< CentralityMap >::value_type two(2);
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while (keys.first != keys.second)
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{
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put(centrality_map, *keys.first,
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get(centrality_map, *keys.first) / two);
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++keys.first;
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}
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}
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template < typename Graph, typename CentralityMap,
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typename EdgeCentralityMap, typename IncomingMap,
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typename DistanceMap, typename DependencyMap, typename PathCountMap,
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typename VertexIndexMap, typename ShortestPaths >
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void brandes_betweenness_centrality_impl(const Graph& g,
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CentralityMap centrality, // C_B
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EdgeCentralityMap edge_centrality_map,
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IncomingMap incoming, // P
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DistanceMap distance, // d
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DependencyMap dependency, // delta
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PathCountMap path_count, // sigma
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VertexIndexMap vertex_index, ShortestPaths shortest_paths)
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{
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typedef
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typename graph_traits< Graph >::vertex_iterator vertex_iterator;
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typedef typename graph_traits< Graph >::vertex_descriptor
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vertex_descriptor;
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// Initialize centrality
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init_centrality_map(vertices(g), centrality);
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init_centrality_map(edges(g), edge_centrality_map);
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std::stack< vertex_descriptor > ordered_vertices;
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vertex_iterator s, s_end;
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for (boost::tie(s, s_end) = vertices(g); s != s_end; ++s)
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{
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// Initialize for this iteration
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vertex_iterator w, w_end;
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for (boost::tie(w, w_end) = vertices(g); w != w_end; ++w)
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{
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incoming[*w].clear();
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put(path_count, *w, 0);
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put(dependency, *w, 0);
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}
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put(path_count, *s, 1);
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// Execute the shortest paths algorithm. This will be either
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// Dijkstra's algorithm or a customized breadth-first search,
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// depending on whether the graph is weighted or unweighted.
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shortest_paths(g, *s, ordered_vertices, incoming, distance,
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path_count, vertex_index);
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while (!ordered_vertices.empty())
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{
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vertex_descriptor w = ordered_vertices.top();
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ordered_vertices.pop();
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typedef typename property_traits< IncomingMap >::value_type
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incoming_type;
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typedef typename incoming_type::iterator incoming_iterator;
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typedef
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typename property_traits< DependencyMap >::value_type
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dependency_type;
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for (incoming_iterator vw = incoming[w].begin();
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vw != incoming[w].end(); ++vw)
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{
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vertex_descriptor v = source(*vw, g);
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dependency_type factor
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= dependency_type(get(path_count, v))
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/ dependency_type(get(path_count, w));
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factor *= (dependency_type(1) + get(dependency, w));
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put(dependency, v, get(dependency, v) + factor);
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update_centrality(edge_centrality_map, *vw, factor);
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}
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if (w != *s)
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{
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update_centrality(centrality, w, get(dependency, w));
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}
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}
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}
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typedef typename graph_traits< Graph >::directed_category
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directed_category;
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const bool is_undirected
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= is_convertible< directed_category*, undirected_tag* >::value;
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if (is_undirected)
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{
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divide_centrality_by_two(vertices(g), centrality);
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divide_centrality_by_two(edges(g), edge_centrality_map);
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}
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}
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}
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} // end namespace detail::graph
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template < typename Graph, typename CentralityMap, typename EdgeCentralityMap,
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typename IncomingMap, typename DistanceMap, typename DependencyMap,
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typename PathCountMap, typename VertexIndexMap >
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void brandes_betweenness_centrality(const Graph& g,
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CentralityMap centrality, // C_B
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EdgeCentralityMap edge_centrality_map,
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IncomingMap incoming, // P
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DistanceMap distance, // d
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DependencyMap dependency, // delta
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PathCountMap path_count, // sigma
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VertexIndexMap vertex_index BOOST_GRAPH_ENABLE_IF_MODELS_PARM(
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Graph, vertex_list_graph_tag))
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{
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detail::graph::brandes_unweighted_shortest_paths shortest_paths;
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detail::graph::brandes_betweenness_centrality_impl(g, centrality,
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edge_centrality_map, incoming, distance, dependency, path_count,
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vertex_index, shortest_paths);
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}
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template < typename Graph, typename CentralityMap, typename EdgeCentralityMap,
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typename IncomingMap, typename DistanceMap, typename DependencyMap,
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typename PathCountMap, typename VertexIndexMap, typename WeightMap >
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void brandes_betweenness_centrality(const Graph& g,
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CentralityMap centrality, // C_B
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EdgeCentralityMap edge_centrality_map,
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IncomingMap incoming, // P
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DistanceMap distance, // d
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DependencyMap dependency, // delta
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PathCountMap path_count, // sigma
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VertexIndexMap vertex_index,
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WeightMap weight_map BOOST_GRAPH_ENABLE_IF_MODELS_PARM(
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Graph, vertex_list_graph_tag))
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{
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detail::graph::brandes_dijkstra_shortest_paths< WeightMap > shortest_paths(
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weight_map);
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detail::graph::brandes_betweenness_centrality_impl(g, centrality,
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edge_centrality_map, incoming, distance, dependency, path_count,
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vertex_index, shortest_paths);
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}
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namespace detail
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{
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namespace graph
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{
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template < typename Graph, typename CentralityMap,
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typename EdgeCentralityMap, typename WeightMap,
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typename VertexIndexMap >
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void brandes_betweenness_centrality_dispatch2(const Graph& g,
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CentralityMap centrality, EdgeCentralityMap edge_centrality_map,
|
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WeightMap weight_map, VertexIndexMap vertex_index)
|
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{
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typedef typename graph_traits< Graph >::degree_size_type
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degree_size_type;
|
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typedef
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typename graph_traits< Graph >::edge_descriptor edge_descriptor;
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typedef typename mpl::if_c<
|
||||
(is_same< CentralityMap, dummy_property_map >::value),
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EdgeCentralityMap, CentralityMap >::type a_centrality_map;
|
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typedef typename property_traits< a_centrality_map >::value_type
|
||||
centrality_type;
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||||
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||||
typename graph_traits< Graph >::vertices_size_type V
|
||||
= num_vertices(g);
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||||
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||||
std::vector< std::vector< edge_descriptor > > incoming(V);
|
||||
std::vector< centrality_type > distance(V);
|
||||
std::vector< centrality_type > dependency(V);
|
||||
std::vector< degree_size_type > path_count(V);
|
||||
|
||||
brandes_betweenness_centrality(g, centrality, edge_centrality_map,
|
||||
make_iterator_property_map(incoming.begin(), vertex_index),
|
||||
make_iterator_property_map(distance.begin(), vertex_index),
|
||||
make_iterator_property_map(dependency.begin(), vertex_index),
|
||||
make_iterator_property_map(path_count.begin(), vertex_index),
|
||||
vertex_index, weight_map);
|
||||
}
|
||||
|
||||
template < typename Graph, typename CentralityMap,
|
||||
typename EdgeCentralityMap, typename VertexIndexMap >
|
||||
void brandes_betweenness_centrality_dispatch2(const Graph& g,
|
||||
CentralityMap centrality, EdgeCentralityMap edge_centrality_map,
|
||||
VertexIndexMap vertex_index)
|
||||
{
|
||||
typedef typename graph_traits< Graph >::degree_size_type
|
||||
degree_size_type;
|
||||
typedef
|
||||
typename graph_traits< Graph >::edge_descriptor edge_descriptor;
|
||||
typedef typename mpl::if_c<
|
||||
(is_same< CentralityMap, dummy_property_map >::value),
|
||||
EdgeCentralityMap, CentralityMap >::type a_centrality_map;
|
||||
typedef typename property_traits< a_centrality_map >::value_type
|
||||
centrality_type;
|
||||
|
||||
typename graph_traits< Graph >::vertices_size_type V
|
||||
= num_vertices(g);
|
||||
|
||||
std::vector< std::vector< edge_descriptor > > incoming(V);
|
||||
std::vector< centrality_type > distance(V);
|
||||
std::vector< centrality_type > dependency(V);
|
||||
std::vector< degree_size_type > path_count(V);
|
||||
|
||||
brandes_betweenness_centrality(g, centrality, edge_centrality_map,
|
||||
make_iterator_property_map(incoming.begin(), vertex_index),
|
||||
make_iterator_property_map(distance.begin(), vertex_index),
|
||||
make_iterator_property_map(dependency.begin(), vertex_index),
|
||||
make_iterator_property_map(path_count.begin(), vertex_index),
|
||||
vertex_index);
|
||||
}
|
||||
|
||||
template < typename WeightMap >
|
||||
struct brandes_betweenness_centrality_dispatch1
|
||||
{
|
||||
template < typename Graph, typename CentralityMap,
|
||||
typename EdgeCentralityMap, typename VertexIndexMap >
|
||||
static void run(const Graph& g, CentralityMap centrality,
|
||||
EdgeCentralityMap edge_centrality_map,
|
||||
VertexIndexMap vertex_index, WeightMap weight_map)
|
||||
{
|
||||
brandes_betweenness_centrality_dispatch2(g, centrality,
|
||||
edge_centrality_map, weight_map, vertex_index);
|
||||
}
|
||||
};
|
||||
|
||||
template <>
|
||||
struct brandes_betweenness_centrality_dispatch1< param_not_found >
|
||||
{
|
||||
template < typename Graph, typename CentralityMap,
|
||||
typename EdgeCentralityMap, typename VertexIndexMap >
|
||||
static void run(const Graph& g, CentralityMap centrality,
|
||||
EdgeCentralityMap edge_centrality_map,
|
||||
VertexIndexMap vertex_index, param_not_found)
|
||||
{
|
||||
brandes_betweenness_centrality_dispatch2(
|
||||
g, centrality, edge_centrality_map, vertex_index);
|
||||
}
|
||||
};
|
||||
|
||||
template < typename T > struct is_bgl_named_params
|
||||
{
|
||||
BOOST_STATIC_CONSTANT(bool, value = false);
|
||||
};
|
||||
|
||||
template < typename Param, typename Tag, typename Rest >
|
||||
struct is_bgl_named_params< bgl_named_params< Param, Tag, Rest > >
|
||||
{
|
||||
BOOST_STATIC_CONSTANT(bool, value = true);
|
||||
};
|
||||
|
||||
}
|
||||
} // end namespace detail::graph
|
||||
|
||||
template < typename Graph, typename Param, typename Tag, typename Rest >
|
||||
void brandes_betweenness_centrality(const Graph& g,
|
||||
const bgl_named_params< Param, Tag, Rest >& params
|
||||
BOOST_GRAPH_ENABLE_IF_MODELS_PARM(Graph, vertex_list_graph_tag))
|
||||
{
|
||||
typedef bgl_named_params< Param, Tag, Rest > named_params;
|
||||
|
||||
typedef typename get_param_type< edge_weight_t, named_params >::type ew;
|
||||
detail::graph::brandes_betweenness_centrality_dispatch1< ew >::run(g,
|
||||
choose_param(
|
||||
get_param(params, vertex_centrality), dummy_property_map()),
|
||||
choose_param(get_param(params, edge_centrality), dummy_property_map()),
|
||||
choose_const_pmap(get_param(params, vertex_index), g, vertex_index),
|
||||
get_param(params, edge_weight));
|
||||
}
|
||||
|
||||
// disable_if is required to work around problem with MSVC 7.1 (it seems to not
|
||||
// get partial ordering getween this overload and the previous one correct)
|
||||
template < typename Graph, typename CentralityMap >
|
||||
typename disable_if< detail::graph::is_bgl_named_params< CentralityMap >,
|
||||
void >::type
|
||||
brandes_betweenness_centrality(const Graph& g,
|
||||
CentralityMap centrality BOOST_GRAPH_ENABLE_IF_MODELS_PARM(
|
||||
Graph, vertex_list_graph_tag))
|
||||
{
|
||||
detail::graph::brandes_betweenness_centrality_dispatch2(
|
||||
g, centrality, dummy_property_map(), get(vertex_index, g));
|
||||
}
|
||||
|
||||
template < typename Graph, typename CentralityMap, typename EdgeCentralityMap >
|
||||
void brandes_betweenness_centrality(const Graph& g, CentralityMap centrality,
|
||||
EdgeCentralityMap edge_centrality_map BOOST_GRAPH_ENABLE_IF_MODELS_PARM(
|
||||
Graph, vertex_list_graph_tag))
|
||||
{
|
||||
detail::graph::brandes_betweenness_centrality_dispatch2(
|
||||
g, centrality, edge_centrality_map, get(vertex_index, g));
|
||||
}
|
||||
|
||||
/**
|
||||
* Converts "absolute" betweenness centrality (as computed by the
|
||||
* brandes_betweenness_centrality algorithm) in the centrality map
|
||||
* into "relative" centrality. The result is placed back into the
|
||||
* given centrality map.
|
||||
*/
|
||||
template < typename Graph, typename CentralityMap >
|
||||
void relative_betweenness_centrality(const Graph& g, CentralityMap centrality)
|
||||
{
|
||||
typedef typename graph_traits< Graph >::vertex_iterator vertex_iterator;
|
||||
typedef
|
||||
typename property_traits< CentralityMap >::value_type centrality_type;
|
||||
|
||||
typename graph_traits< Graph >::vertices_size_type n = num_vertices(g);
|
||||
centrality_type factor
|
||||
= centrality_type(2) / centrality_type(n * n - 3 * n + 2);
|
||||
vertex_iterator v, v_end;
|
||||
for (boost::tie(v, v_end) = vertices(g); v != v_end; ++v)
|
||||
{
|
||||
put(centrality, *v, factor * get(centrality, *v));
|
||||
}
|
||||
}
|
||||
|
||||
// Compute the central point dominance of a graph.
|
||||
template < typename Graph, typename CentralityMap >
|
||||
typename property_traits< CentralityMap >::value_type central_point_dominance(
|
||||
const Graph& g,
|
||||
CentralityMap centrality BOOST_GRAPH_ENABLE_IF_MODELS_PARM(
|
||||
Graph, vertex_list_graph_tag))
|
||||
{
|
||||
using std::max;
|
||||
|
||||
typedef typename graph_traits< Graph >::vertex_iterator vertex_iterator;
|
||||
typedef
|
||||
typename property_traits< CentralityMap >::value_type centrality_type;
|
||||
|
||||
typename graph_traits< Graph >::vertices_size_type n = num_vertices(g);
|
||||
|
||||
// Find max centrality
|
||||
centrality_type max_centrality(0);
|
||||
vertex_iterator v, v_end;
|
||||
for (boost::tie(v, v_end) = vertices(g); v != v_end; ++v)
|
||||
{
|
||||
max_centrality = (max)(max_centrality, get(centrality, *v));
|
||||
}
|
||||
|
||||
// Compute central point dominance
|
||||
centrality_type sum(0);
|
||||
for (boost::tie(v, v_end) = vertices(g); v != v_end; ++v)
|
||||
{
|
||||
sum += (max_centrality - get(centrality, *v));
|
||||
}
|
||||
return sum / (n - 1);
|
||||
}
|
||||
|
||||
} // end namespace boost
|
||||
|
||||
#endif // BOOST_GRAPH_BRANDES_BETWEENNESS_CENTRALITY_HPP
|
||||
Reference in New Issue
Block a user