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Copy pathclustering_coefficient.cpp
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103 lines (83 loc) · 3.25 KB
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// (C) Copyright 2007-2009 Andrew Sutton
//
// Use, modification and distribution are subject to the
// Boost Software License, Version 1.0 (See accompanying file
// LICENSE_1_0.txt or http://www.boost.org/LICENSE_1_0.txt)
#include <iostream>
#include <boost/graph/undirected_graph.hpp>
#include <boost/graph/directed_graph.hpp>
#include <boost/graph/exterior_property.hpp>
#include <boost/graph/clustering_coefficient.hpp>
using namespace std;
using namespace boost;
// number of vertices in the graph
static const unsigned N = 5;
template < typename Graph > struct vertex_vector
{
typedef graph_traits< Graph > traits;
typedef vector< typename traits::vertex_descriptor > type;
};
template < typename Graph >
void build_graph(Graph& g, typename vertex_vector< Graph >::type& v)
{
// add vertices
for (size_t i = 0; i < N; ++i)
{
v[i] = add_vertex(g);
}
// add edges
add_edge(v[0], v[1], g);
add_edge(v[1], v[2], g);
add_edge(v[2], v[0], g);
add_edge(v[3], v[4], g);
add_edge(v[4], v[0], g);
}
template < typename Graph > void test_undirected()
{
typedef typename graph_traits< Graph >::vertex_descriptor Vertex;
typedef exterior_vertex_property< Graph, double > ClusteringProperty;
typedef typename ClusteringProperty::container_type ClusteringContainer;
typedef typename ClusteringProperty::map_type ClusteringMap;
Graph g;
vector< Vertex > v(N);
build_graph(g, v);
ClusteringContainer cc(num_vertices(g));
ClusteringMap cm(cc, g);
BOOST_ASSERT(num_paths_through_vertex(g, v[0]) == 3);
BOOST_ASSERT(num_paths_through_vertex(g, v[1]) == 1);
BOOST_ASSERT(num_paths_through_vertex(g, v[2]) == 1);
BOOST_ASSERT(num_paths_through_vertex(g, v[3]) == 0);
BOOST_ASSERT(num_paths_through_vertex(g, v[4]) == 1);
BOOST_ASSERT(num_triangles_on_vertex(g, v[0]) == 1);
BOOST_ASSERT(num_triangles_on_vertex(g, v[1]) == 1);
BOOST_ASSERT(num_triangles_on_vertex(g, v[2]) == 1);
BOOST_ASSERT(num_triangles_on_vertex(g, v[3]) == 0);
BOOST_ASSERT(num_triangles_on_vertex(g, v[4]) == 0);
// TODO: Need a FP approximation to assert here.
// BOOST_ASSERT(clustering_coefficient(g, v[0]) == double(1)/3);
BOOST_ASSERT(clustering_coefficient(g, v[1]) == 1);
BOOST_ASSERT(clustering_coefficient(g, v[2]) == 1);
BOOST_ASSERT(clustering_coefficient(g, v[3]) == 0);
BOOST_ASSERT(clustering_coefficient(g, v[4]) == 0);
all_clustering_coefficients(g, cm);
// TODO: Need a FP approximation to assert here.
// BOOST_ASSERT(cm[v[0]] == double(1)/3);
BOOST_ASSERT(cm[v[1]] == 1);
BOOST_ASSERT(cm[v[2]] == 1);
BOOST_ASSERT(cm[v[3]] == 0);
BOOST_ASSERT(cm[v[4]] == 0);
// I would have used check_close, but apparently, that requires
// me to link this against a library - which I don't really want
// to do. Basically, this makes sure that that coefficient is
// within some tolerance (like 1/10 million).
double coef = mean_clustering_coefficient(g, cm);
BOOST_ASSERT((coef - (7.0f / 15.0f)) < 1e-7f);
}
int main(int, char*[])
{
typedef undirected_graph<> Graph;
// typedef directed_graph<> Digraph;
// TODO: write a test for directed clustering coefficient.
test_undirected< Graph >();
// test<Digraph>();
}