[Boost-users] request for help re: brandes_betweenness_centrality for weighted graph

Subject: [Boost-users] request for help re: brandes_betweenness_centrality for weighted graph
From: allenem_at_[hidden]
Date: 2009-09-29 15:10:50

Hi-

I've just recently started to use the BGL and was wondering if someone 
could provide an example (and/or just let me know where I am going 
wrong) in trying to execute the brandes_betweenness_centrality algorithm 
for a weighted graph. 

Below are the relevant code snippets from my program. 
I am able to compile and run the code, and have successfully iterated 
over all elements (vertices, edges, and "interaction_weights" to verify 
that the data are stored correctly) but the calculated betweenness 
values are the same whether or not I use the edge weight map, which 
suggests that they are not being considered in the calculation even when 
passed as a parameter to the brandes_betweenness_centrality function.  
What am I missing?

Thank you,

Emily

#include <boost/graph/graph_traits.hpp> // iterator functions
#include <boost/graph/adjacency_list.hpp>
#include <boost/graph/betweenness_centrality.hpp>
#include <map>
#include <vector>

using namespace std;
using namespace boost;

struct order_edges {
  template <typename T>
  bool operator() (const T& x, const T& y) const {
    return x.get_property() < y.get_property();
  }
};

/* =============================================================
   Main
   ============================================================ */

int main(int argc, char **argv) {

  // Define the Graph
  typedef property < vertex_centrality_t, double > CentralityMap;
  typedef adjacency_list<vecS, vecS, bidirectionalS, CentralityMap> Graph;
 
  typedef graph_traits<Graph>::vertex_descriptor Vertex;
  typedef graph_traits<Graph>::edge_descriptor Edge;

  typedef map<Edge, double, order_edges> edge_weight_map_t;
  edge_weight_map_t base_map;
  associative_property_map<edge_weight_map_t> interaction_weight(base_map);

  Graph g; // instance of the graph
 
  // determine vertices based upon input from a file

  // add edges and assign values to associated interaction weights from 
a file ....
 
  brandes_betweenness_centrality(g, get(vertex_centrality,g), 
interaction_weight);
 
}