def test_kclique(self):
g = get_string_graph()
coms = algorithms.kclique(g, 3)
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]), str)
def test_ranking_comp(self):
g = nx.karate_club_graph()
coms = algorithms.louvain(g)
coms2 = algorithms.kclique(g, 2)
coms3 = algorithms.label_propagation(g)
rk = evaluation.ComparisonRanking([coms, coms2, coms3])
rk.rank(evaluation.overlapping_normalized_mutual_information_LFK)
rk.rank(evaluation.overlapping_normalized_mutual_information_MGH)
rk.rank(evaluation.omega)
rnk, _ = rk.topsis()
self.assertEqual(len(rnk), 3)
pc = rk.bonferroni_post_hoc()
self.assertLessEqual(len(pc), 4)
def kclique(k) : return lambda G : algorithms.kclique(G, k) algos['kclique'] = kclique(20)