Hi,
I am getting the following error when using get_edges_prob() with
layered SBMs. Minimal example:
import graph_tool.all as gt
import numpy as np
gr=gt.generate_sbm(b=np.array([0]*500+[1]*500),probs=np.array([[10000,200],[200,10000]]))
etype=gr.new_edge_property('int')
gr.ep.etype=etype
for e in gr.edges():
gr.ep.etype[e]=np.random.choice([0,1,2,3])
state = gt.minimize_nested_blockmodel_dl(gr,
deg_corr=True,layers=True,state_args=dict(ec=gr.ep.etype,layers=True),verbose=False)
state.get_edges_prob([[2,32,0],[3,4,2]],spurious=[])
---------------------------------------------------------------------------
UnboundLocalError Traceback (most recent call last)
<ipython-input-30-a1758ce2345d> in<module>()
7 gr.ep.etype[e]=np.random.choice([0,1,2,3])
8 state= gt.inference.minimize_nested_blockmodel_dl(gr,
deg_corr=True,layers=True,state_args=dict(ec=gr.ep.etype,layers=True),verbose=False)
----> 9state.get_edges_prob([[2,32,0],[3,4,2]],spurious=[])
/usr/lib/python2.7/dist-packages/graph_tool/inference/nested_blockmodel.py
inget_edges_prob(self, missing, spurious, entropy_args)
481 lstate._state.clear_egroups()
482
--> 483L+= lstate.get_edges_prob(missing, spurious, entropy_args=eargs)
484 if isinstance(self.levels[0], LayeredBlockState):
485 missing= [(lstate.b[u], lstate.b[v], l_) for u, v,
l_in missing]
/usr/lib/python2.7/dist-packages/graph_tool/inference/layered_blockmodel.py
inget_edges_prob(self, missing, spurious, entropy_args)
934 state= self.layer_states[l[0]]
935 state.g.remove_edge(e)
--> 936for u, v, lin old_es:
937 if not l[1]:
938 state= self.agg_state
UnboundLocalError: local variable 'old_es' referenced before assignment
Regards,
Anatol
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