def build_nx_graph(
self,
nx_graph: nx.DiGraph,
*,
bipartite: bool = False,
) -> nx.DiGraph:
"""
Factory pattern to populate a [`networkx.DiGraph`](https://networkx.org/documentation/latest/reference/classes/digraph.html) object, using transforms in this subgraph.
See <https://networkx.org/>
nx_graph:
pass in an unpopulated [`networkx.DiGraph`](https://networkx.org/documentation/latest/reference/classes/digraph.html) object; must be a [`cugraph.DiGrap`](https://docs.rapids.ai/api/cugraph/stable/api.html#digraph) if GPUs are enabled
bipartite:
flag for whether the `(subject, object)` pairs should be partitioned into *bipartite sets*, in other words whether the *adjacency matrix* is symmetric; ignored if GPUs are enabled
returns:
the populated `NetworkX` graph object; uses the [RAPIDS `cuGraph` library](https://docs.rapids.ai/api/cugraph/stable/) if GPUs are enabled
"""
if self.kg.use_gpus:
df = self.build_df()
nx_graph.from_cudf_edgelist(df, source="src", destination="dst")
else:
for row in self.kg.query(self.sparql, bindings=self.bindings):
s_id = self.transform(row[self.src_dst[0]])
s_label = self.n3fy(row[self.src_dst[0]])
o_id = self.transform(row[self.src_dst[1]])
o_label = self.n3fy(row[self.src_dst[1]])
if bipartite:
nx_graph.add_node(s_id, label=s_label, bipartite=0)
nx_graph.add_node(o_id, label=o_label, bipartite=1)
else:
nx_graph.add_node(s_id, label=s_label)
nx_graph.add_node(o_id, label=o_label)
nx_graph.add_edge(s_id, o_id)
return nx_graph
