avoid random result randomness in find_partition

[kalthwaini]

as many clustering algorithms, find_partition is giving diff results over multiple executions of same input. I'm trying to stablize this and have fixed results of same input. I have tried the seed parameter, but didn't work for me. Is there a way to reach this? (have same results for same input)

[prakritipaul]

Similar question as mine.

[vtraag]

Sorry for the late reply!

Could you perhaps include some code that demonstrates the problem for you?

If I run

part1 = la.find_partition(G, la.ModularityVertexPartition, seed=0)
part2 = la.find_partition(G, la.ModularityVertexPartition, seed=0)

then part1.membership == part2.membership, in other words, I get identical partition, even for random graphs G.