Dear Dr Peixoto,


I would like to solve some questions I have about inference algorithms for the identification of large-scale network structure via the statistical inference of generative models.

Minimize_blockmodel algorithm takes an hour to finish using my network  with 21000 nodes (like the hierarchical version), and it spends two days and a half with overlap. However, I have run an hierarchical analysis with overlap, and it is still running since 14 days ago. So my first question is: is this time normal, or maybe there is any problem? Do you know how long could it ussually takes?

Secondly, I have repeated some of these analysis with exactly same options but I get different solutions (similar but different), so I wonder if the algorithm is heuristic (I thought it was exact).

My last question question regards bipartite analysis. I have two types of nodes in my network and I wonder if there are any analytical difference when running these algorithms with the bipartite option (clabel=True, and different labels in each group of nodes) or not, because it seems that the program “knows” my network is bipartite in any case. If there are differences between bipartite and “unipartite” analysis (clabel=False), is it possible to compare description length between them to model selection?

Thank you very much for your help!


Best regards,



Andrea