def test_aslpaw(self):
g = nx.karate_club_graph()
coms = algorithms.aslpaw(g)
self.assertEqual(type(coms.communities), list)
if len(coms.communities) > 0:
self.assertEqual(type(coms.communities[0]), list)
self.assertEqual(type(coms.communities[0][0]), int)
communities = algorithms.egonet_splitter(g, **clust_kwargs)
elif (options.method == 'nmnf'):
communities = algorithms.nmnf(g, **clust_kwargs)
elif (options.method == 'nnsed'):
communities = algorithms.nnsed(g, **clust_kwargs)
elif (options.method == 'slpa'):
communities = algorithms.slpa(g, **clust_kwargs)
elif (options.method == 'bimlpa'):
communities = actlgorithms.bimlpa(g, **clust_kwargs)
elif (options.method == 'wcommunity'):
communities = algorithms.wCommunity(g, **clust_kwargs)
elif (options.method == 'aslpaw'):
import warnings
with warnings.catch_warnings():
warnings.filterwarnings("ignore")
communities = algorithms.aslpaw(g)
elif (options.method == 'external'):
from collections import defaultdict
from cdlib import NodeClustering
coms_to_node = defaultdict(list)
f = open(options.external, 'r')
for line in f:
fields = line.strip("\n").split("\t")
coms_to_node[fields[0]].append(fields[1])
coms = [list(c) for c in coms_to_node.values()]
communities = NodeClustering(coms,
g,
"external",
method_parameters={},
overlap=True)
else:
