Dear Arttu.
This is currently not supported, but will soon be possible with a new
StackedBlockState that will appear in the next release.
Please open a feature-request issue in the website so you will be
notified when this becomes available.
Best,
Tiago
Am 02.02.22 um 18:46 schrieb arttu.malkam...@helsinki.fi:
Hello,
Given a situation where I'm trying to fit a LayeredBlockState with somewhat
different edge weight distributions across the layers, is it possible to pass
different rec_types for different layers when using LayeredBlockState? Or
should I pick one that fits the aggregate distribution of my ten layers? Or is
it perhaps best to convert the weights in each layer to discrete values?
This is how I'm currently doing it, but I know that "real-normal" works better
for the first two layers if I fit them separately.
state = gt.minimize_blockmodel_dl(g, state = gt.LayeredBlockState, state_args =
dict(deg_corr = True, overlap = True, layers = True, ec = g.ep.layer, recs =
[g.ep.weight], rec_types = ["real-exponential"]))
Best,
Arttu
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Tiago de Paula Peixoto <ti...@skewed.de>
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