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?