def _run_stochastic_block_model(self,
write=False,
write_property=None,
**kwargs):
raise CommunityDetector.PartitionError(
"Stochastic block model is not implemented "
"for Neo4j-based graphs")
def _run_girvan_newman(self,
weight=None,
n_communitites=2,
intermediate=False):
raise CommunityDetector.PartitionError(
"Girvan-Newman algorithm is not implemented "
"for Neo4j-based graphs")
def detect_communities(self,
strategy="louvain",
weight=None,
n_communities=2,
intermediate=False,
write=False,
write_property=None,
**kwargs):
"""Detect community partition using the input strategy."""
if strategy not in CommunityDetector._strategies.keys():
raise CommunityDetector.PartitionError(
f"Unknown community detection strategy '{strategy}'")
partition = getattr(self, CommunityDetector._strategies[strategy])(
weight=weight,
n_communities=n_communities,
intermediate=intermediate,
write=write,
write_property=write_property,
**kwargs)
return partition
def _run_stochastic_block_model(self, **kwargs):
raise CommunityDetector.PartitionError(
"Stochastic block model is not implemented "
"for NetworkX-based graphs")
def _run_label_propagation(self, **kwargs):
raise CommunityDetector.PartitionError(
"Label propagation algorithm is not implemented "
"for Neo4j-based graphs")
def _run_louvain(self, **kwargs):
raise CommunityDetector.PartitionError(
"Louvain algorithm is not implemented "
"for graph-tool-based graphs")