Hi,
These belong to the issue tracker. Could you please try again to login
and post there?
Best,
Tiago
Am 06.05.21 um 10:13 schrieb hazaa:
hi,
I'm writing to report several issues with the multicanonical sampler, using gt
version 2.37. ((haven't been able to login on gitlab tracker)
First with the NestedBlockState
g = gt.collection.data["celegansneural"]
state = gt.NestedBlockState(g)
nbins=100
S0 = state.entropy()
Smin,Smax = S0*0.90,S0*1.1
ms= gt.MulticanonicalState(state,Smin,Smax, nbins=nbins)
gt.multicanonical_equilibrate(ms)
Will return:
/usr/lib/python3/dist-packages/graph_tool/inference/mcmc.py in sweep(self,
**kwargs)
426
427 def sweep(self, **kwargs):
--> 428 self._state.multicanonical_sweep(self, **kwargs)
429
430 def get_energies(self):
TypeError: multicanonical_sweep() takes 1 positional argument but 2 were given
Then with BlockState:
state = gt.BlockState(g)
nbins=100
S0 = state.entropy()
Smin,Smax = S0*0.90,S0*1.1
ms= gt.MulticanonicalState(state,Smin,Smax, nbins=nbins)
gt.multicanonical_equilibrate(ms) #THIS IS OK
ds,nattempts,nmoves = state.multicanonical_sweep(ms,niter=10 )
The last line fails with the following output:
/usr/lib/python3/dist-packages/graph_tool/inference/blockmodel.py in
_multicanonical_sweep_dispatch(self, multicanonical_state)
1702
_get_rng())
1703 else:
-> 1704 return
libinference.multicanonical_sweep(multicanonical_state,
1705 self._state,
_get_rng())
1706
TypeError: No registered converter was able to extract a C++ reference to type
boost::any from this Python object of type NoneType
Thanks for this wonderful module!
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--
Tiago de Paula Peixoto <ti...@skewed.de>
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