Am 19.06.2018 um 21:01 schrieb Alexandre Hannud Abdo:
> 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)

Since find_vertex() is O(N), the above is O(B * N). A faster O(N) approach
is simply:

groups = defaultdict(list)
for v in g.vertices():
   groups[l0.b[v]].append(v)

Best,
Tiago
-- 
Tiago de Paula Peixoto <[email protected]>
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