Hi all, I have a NestedBlockState with LayeredBlockState as basis, two layers. I would like to predict edges that are missing in one or the other layer (besides, is this even possible?). However, given a list of missing edges (and a list of spurious ones) I tried this a_state.get_edges_prob(missing, spurious) and get this error AttributeError Traceback (most recent call last) <ipython-input-68-b3bc5280d3da> in <module> ----> 1 a_state.get_edges_prob([missing], spurious) ~/anaconda3/envs/experimental/lib/python3.8/site-packages/graph_tool/inference/nested_blockmodel.py in get_edges_prob(self, missing, spurious, entropy_args) 441 lstate._state.clear_egroups() 442 --> 443 L += lstate.get_edges_prob(missing, spurious, entropy_args=eargs) 444 if isinstance(self.levels[0], LayeredBlockState): 445 missing = [(lstate.b[u], lstate.b[v], l_) for u, v, l_ in missing] ~/anaconda3/envs/experimental/lib/python3.8/site-packages/graph_tool/inference/blockmodel.py in get_edges_prob(self, missing, spurious, entropy_args) 1204 pos[v] = self.b[v] 1205 -> 1206 self.remove_vertex(pos.keys()) 1207 1208 try: ~/anaconda3/envs/experimental/lib/python3.8/site-packages/graph_tool/inference/blockmodel.py in remove_vertex(self, v) 1144 twice. 1145 """ -> 1146 self._state.remove_vertex(int(v)) 1147 1148 def add_vertex(self, v, r): AttributeError: 'graph_tool::BlockState<boost::undirected_adaptor<b' object has no attribute 'remove_vertex' I'm not sure what's happening here, but as far as I know gt.BlockState (and gt.NestedBlockState and gt.LayeredBlockState) have a remove_vertex method defined, right?