> vc = g.community_infomap() You could try the following: g2 = g.copy() g2.contract_vertices(vc.membership) g2.es["weight"] = 1 g2.simplify(combine_edges="sum")
This would give you a graph where the nodes represent the communities of the original graph, the edges are weighted, and the weight of an edge going between node A and B is the number of edges connecting community A and B. g2.get_adjacency(attribute="weight") would then give you the weighted adjacency matrix of g2, which is essentially a similarity matrix between the communities. Of course it is very well conceivable that other similarity or distance measures make more sense, but this is a good starting point. > My ultimate goal is to use this similarity matrix and multidimensional > scaling to make a nice 2d layout of the discovered communities You can use any layout algorithm on g2 (including g2.layout_mds for what it's worth) to obtain a layout. Cheers, Tamas _______________________________________________ igraph-help mailing list [email protected] https://lists.nongnu.org/mailman/listinfo/igraph-help
