def test_nmnf(self):
     g = nx.karate_club_graph()
     coms = algorithms.nmnf(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)
예제 #2
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 #elif(options.method == 'sbm_dl'):
 #	communities = algorithms.sbm_dl(g)
 #elif(options.method == 'sbm_dl_nested'):
 #	communities = algorithms.sbm_dl_nested(g)
 elif (options.method == 'lais2'):
     communities = algorithms.lais2(g, **clust_kwargs)
 elif (options.method == 'big_clam'):
     communities = algorithms.big_clam(g, **clust_kwargs)
 elif (options.method == 'danmf'):
     communities = algorithms.danmf(g, **clust_kwargs)
 elif (options.method == 'ego_networks'):
     communities = algorithms.ego_networks(g, **clust_kwargs)
 elif (options.method == 'egonet_splitter'):
     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