Am 23.10.18 um 20:43 schrieb Ozgun Altunkaya: > When I return the above function, it is reasonably fast, however the edge > indices don't match with those of graph (no weights), hence the weights are > wrong.
This is because you are using the edge descriptors of the wrong graph. What
you probably want to do is:
for e in graph.edges():
weight = get_weight(int(e.source()))
ne = weighted_graph.add_edge(int(e.source()), int(e.target()))
weights[ne] = weight
> Also, I need to generate weighted_graph for at least 5-10 times, each with
> different weights (however the edges and vertices are remain the same,
> only weights change.) Is there a faster/better way to do this?
You can access the weights as a numpy array via:
weights.fa
It can be faster to just update this array, than to re-generate the whole
thing from scratch.
Best,
Tiago
--
Tiago de Paula Peixoto <ti...@skewed.de>
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