Thanks for the reply. In the section (VI) of your paper "Inferring the mesoscale structure of layered, edge-valued and time-varying networks", you used the layered stochastic block model for a temporal network. I have a similar data set which I do not want to fix the membership for the nodes of different layers to the same block over all layers (nodes can change their block memberships over time). I am wondering again how I can use graph tool for this case? Which method or constructor should I use?
On Wed, Jul 18, 2018 at 1:07 PM, Tiago de Paula Peixoto firstname.lastname@example.org wrote:
Am 16.07.2018 um 22:46 schrieb Zahra Sheikhbahaee:
Thanks for the explanation. I have another question:
In the "Inferring the mesoscale structure of layered, edge-valued and time-varying networks", you compared two way of constructing layered structures: first approach: You assumed an adjacency matrix in each independent layer. The second method, the collapsed graph considered as a result of merging all the adjacency matrices together.
I am wondering how I can use graph_tool for the first method? Which
or class should I use?
You have to pass the option "layers=True" to the LayeredBlockState constructor:
If there is a class, is it still possible to consider a graph with weighted edges?
Yes, it accepts 'recs/rec_types/rec_params' just like the regular BlockState.
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