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)
----> 9 state.get_edges_prob([[2,32,0],[3,4,2]],spurious=[])

/usr/lib/python2.7/dist-packages/graph_tool/inference/nested_blockmodel.py in get_edges_prob(self, missing, spurious, entropy_args)
    481                     lstate._state.clear_egroups()
    482 
--> 483             L += 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 in get_edges_prob(self, missing, spurious, entropy_args)
    934                     state = self.layer_states[l[0]]
    935                 state.g.remove_edge(e)
--> 936             for u, v, l in old_es:
    937                 if not l[1]:
    938                     state = self.agg_state

UnboundLocalError: local variable 'old_es' referenced before assignment


Regards,
Anatol