def purity(self) -> evaluation.FitnessResult:
"""Purity is the product of the frequencies of the most frequent labels carried by the nodes within the communities
:return: FitnessResult object
"""
res = None
if self.coms_labels is not None:
res = evaluation.purity(self.coms_labels)
return res
def test_purity(self):
l1 = ["one", "two", "three", "four"]
l2 = ["A", "B", "C"]
g_attr = nx.barabasi_albert_graph(100, 5)
labels = dict()
for node in g_attr.nodes():
labels[node] = {"l1": random.choice(l1), "l2": random.choice(l2)}
coms = eva(g_attr, labels, alpha=0.8)
pur = evaluation.purity(coms)
self.assertGreaterEqual(pur.score, 0)
self.assertLessEqual(pur.score, 1)