k. Is it from the simulation or based on a unique property of the
network?
sincerely,
Gege Hou
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for s in ss]
rstate = gt.EpidemicsBlockState(g, s=ss, beta = None, r=1e-6,
global_beta=.2,
state_args=dict(B=1), nested=False)
"
Why couldn't I use an empty graph as a starting point?
Sincerely,
Gege Hou
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state().copy()]
si_state.iterate_async()
s.append(si_state.get_state().copy())
# Each time series should be represented as a single vector-valued
# vertex property map with the states for each note at each time.
s = gt.group_vector_property(s)
ss.append(s)
"
sincerely
uot;, gt.similarity(g, gm, g.new_ep("double", 1),
gm.ep.eprob))
print("Inversed temperature: %g ± %g" % (mean(betas), std(betas)))
Moreover, I also wonder how to do a nested version for the same network.
Please let me know if you need more information on the question. ot
