I tested the running time of the igraph implementation of neighborhood_size it does indeed appear to be fast and memory efficient (although I don't know exactly how it works). I would also like to count the number of edges within a 2 hop neighborhood of each node. One way is
[g2.subgraph(g2.neighborhood(v, order = 2)).ecount() for v in g.vs] Is there a better/faster igraph way? Raphael On 15 September 2012 09:21, Raphael Clifford <[email protected]> wrote: > I would like to count the number of vertices within a 2 hop distance > of each node in a large sparse graph. I see there is a function which > one could call with neighborhood size(vertices=g.vs, order=2). What > method is used to do the calculation? > > A classic way to do it would be to represent the graph as a sparse > matrix, square it using a clever sparse matrix multiplication > algorithm and count the number of elements in each row that are > non-negative. I am wondering how this would compare to the > implemented method in igraph. Can igraph make a sparse matrix that > could be fed directly into > http://docs.scipy.org/doc/scipy/reference/generated/scipy.sparse.csr_matrix.html#scipy.sparse.csr_matrix > for example? > > Raphael _______________________________________________ igraph-help mailing list [email protected] https://lists.nongnu.org/mailman/listinfo/igraph-help
