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There are still some lingering issues with using original vs. transposed graphs, e.g.,
>>> predicates = ["rdfs:subClassOf"]
>>> tp = oi.termset_pairwise_similarity(["BFO:0000006"], ["BFO:0000018"], predicates)
Graph contains multiple disconnected components. Will ignore all but the largest component. 24 components are present. Largest component has 35 nodes.
>>> oi = get_implementation_from_shorthand("grape:sqlite:obo:phenio")
>>> tp = oi.termset_pairwise_similarity(["eye"], ["eyelash"], predicates)
Graph contains multiple disconnected components. Will ignore all but the largest component. 31982 components are present. Largest component has 242712 nodes.
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/home/harry/oakx-grape/src/oakx_grape/grape_implementation.py", line 324, in termset_pairwise_similarity
resnik_model = self._make_grape_resnik_model(dag=dag)
File "/home/harry/oakx-grape/src/oakx_grape/grape_implementation.py", line 287, in _make_grape_resnik_model
resnik_model.fit(graph, node_counts=counts)
File "/home/harry/oakx-grape/.venv/lib/python3.9/site-packages/embiggen/similarities/dag_resnik.py", line 32, in fit
self._model.fit(
ValueError: The current graph instance Unnamed is not directed acyclic.
This suggests that the graph isn't being interpreted as a DAG because the edges are going in the wrong direction - an issue that transposition will fix unless the original graph is already "correct".
Graphs should only be transposed if necessary, not by default.
The text was updated successfully, but these errors were encountered:
There are still some lingering issues with using original vs. transposed graphs, e.g.,
This suggests that the graph isn't being interpreted as a DAG because the edges are going in the wrong direction - an issue that transposition will fix unless the original graph is already "correct".
Graphs should only be transposed if necessary, not by default.
The text was updated successfully, but these errors were encountered: