In my network, they have a weight value for each vertex, after applying the
algorithm I need to add this weight to each group in the hierarchy. So it would
have a total weight of each of group B.
g = gt.Graph(directed=True)
dh['Cidades 1'] = g.add_vertex()
g.add_edge_list(dg.values, hashed =True)
weights = df['Valores']
ew = g.new_edge_property('double')
ew.a = weights
g.ep['edge_weight'] = ew
state = gt.minimize_nested_blockmodel_dl(g,
state_args=dict(recs=[g.ep.edge_weight],
rec_types=["discrete-binomial"]))
l: 0, N: 5550, B: 283
l: 1, N: 283, B: 57
l: 2, N: 57, B: 14
l: 3, N: 14, B: 3
l: 4, N: 3, B: 1
l: 5, N: 1, B: 1
>From the code below I have the table of the corresponding numbers of each
>node, I just don't know if they are in order, if it's in order with the
>corresponding nodes of the previous hierarchy my problem is already solved,
>just add the similar. For example I need to add all the weights of group 1 of
>hierarchy 0, then I need to do the same for group 1 of hierarchy 1, so on.
>Could you help me write down the weight of the group?
def r(i):
return levels[5].get_blocks()[i]
hierarquia1 = []
for i in range(5550):
hierarquia1.append(r(i))
___
graph-tool mailing list -- graph-tool@skewed.de
To unsubscribe send an email to graph-tool-le...@skewed.de
