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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