Thank you, this solved my problems! Best wishes.
2016-02-08 11:38 GMT+01:00 Tiago de Paula Peixoto <[email protected]>: > On 08.02.2016 11:31, Danilo Giuffrida wrote: > > Yes. For example in the original directed network I have the triangle: > > (1)<--(2)<-->(3)-->(1) > > then I obtain the undirected network by means of g.set_directed(False) > > and evaluate the local clustering of node 1, finding C(1)=2 (instead > > of C(1)=1). This happens for all the nodes in this network, i.e. their > > local clustering is always between 0 and 2. Of course I could simply > > divide by two, but I would like to understand what is going wrong. I > > know that for directed/undirected network the normalization is > > different, hence I guess that something is not going on with the > > set_directed method. > > This is because if you make the network undirected, it becomes a > multigraph, i.e. there are _two_ edges between 2 and 3. The clustering > coefficient is normalized only for _simple_ graphs, with at most one > edge between nodes. > > If you want to transform the network into a multigraph, you can filter > the parallel edges out: > > u = GraphView(g, efilt=logical_not(label_parallel_edges(g, > mark_only=True).fa)) > > or remove them with remove_parallel_edges(). > > Best, > Tiago > > -- > Tiago de Paula Peixoto <[email protected]> > > > _______________________________________________ > graph-tool mailing list > [email protected] > http://lists.skewed.de/mailman/listinfo/graph-tool > >
_______________________________________________ graph-tool mailing list [email protected] http://lists.skewed.de/mailman/listinfo/graph-tool
