Hi!I'm trying to perform community detection algorithm with /nested stochastic block model/ and I had some questions: Is there a way to take into account the weights of the edges? I read in *BlockState* about some /weights/, but did not understand what it is and how to use them. How to get the hierarchical results from the /nested stochastic block model/ to obtain a kind of agglomerative dendrogram? How to obtain numerical values of each vertex belonging to the clusters, after margins collectioning, like it drew in pie vertex chart in examples? How to measure quality of partitioning: is it any other metrics, than was in examples? Is it necessary that both/ Model Evidence/ was bigger and /Bethe Entropy/ was lower? What if only one metrics performs better, then other degrades? Thank you very much for your tremendous work on algorithms and only one multi-threaded library for working with graphs! I hope my questions are not too stupid and help someone else. -- View this message in context: http://main-discussion-list-for-the-graph-tool-project.982480.n3.nabble.com/... Sent from the Main discussion list for the graph-tool project mailing list archive at Nabble.com.