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