Ni! Hi Philipp, Yes, there are more straightforward paths to the same information: # get some graph and model it import graph_tool.all as gt g = gt.collection.data["celegansneural"] s = gt.minimize_nested_blockmodel_dl(g) # get your groups of vertices in a dictionary l0 = s.levels[0] block2vertices = dict() for i in range(l0.B): block2vertices[i] = gt.find_vertex(l0.g, l0.b, i) Cheers .~´ On Tue, Jun 19, 2018 at 7:01 PM, P-M <pmj27@cam.ac.uk> wrote:
(I should probably add that I am only interested in relations between the nodes in a given block with each other, so am happy to work with vertex filters.)
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