def test_disconnected_communites(self):
graph = nx.Graph([(0,1),(1,2),(2,0),(3,4),(3,5),(4,5)])
partition = wm.WeightedPartition(graph, communities=[set([0, 1, 2]), set([3, 4, 5])])
wcd = nr.within_community_degree(partition)
self.assertAlmostEqual(wcd, {0: 0.0, 1: 0.0, 2: 0.0, 3: 0.0, 4: 0.0, 5: 0.0})
pc = nr.participation_coefficient(partition)
self.assertEqual(pc, {0: 0.0, 1: 0.0, 2: 0.0, 3: 0.0, 4: 0.0, 5: 0.0})
def test_disconnected_communites(self):
graph = nx.Graph([(0, 1), (1, 2), (2, 0), (3, 4), (3, 5), (4, 5)])
partition = wm.WeightedPartition(
graph, communities=[set([0, 1, 2]), set([3, 4, 5])])
wcd = nr.within_community_degree(partition)
self.assertAlmostEqual(wcd, {
0: 0.0,
1: 0.0,
2: 0.0,
3: 0.0,
4: 0.0,
5: 0.0
})
pc = nr.participation_coefficient(partition)
self.assertEqual(pc, {0: 0.0, 1: 0.0, 2: 0.0, 3: 0.0, 4: 0.0, 5: 0.0})
def test_high_low_pc(self):
graph = nx.Graph([(0, 1), (1, 2), (2, 0), (0, 3), (3, 4), (3, 5),
(4, 5)])
partition = wm.WeightedPartition(
graph, communities=[set([0, 1, 2]), set([3, 4, 5])])
pc = nr.participation_coefficient(partition)
self.assertAlmostEqual(
pc, {
0: 0.4444444444444444,
1: 0.0,
2: 0.0,
3: 0.4444444444444444,
4: 0.0,
5: 0.0
})
def test_high_low_pc(self):
graph = nx.Graph([(0,1),(1,2),(2,0),(0,3),(3,4),(3,5),(4,5)])
partition = wm.WeightedPartition(graph, communities=[set([0, 1, 2]), set([3, 4, 5])])
pc = nr.participation_coefficient(partition)
self.assertAlmostEqual(pc,{0: 0.4444444444444444, 1: 0.0, 2: 0.0, 3: 0.4444444444444444, 4: 0.0, 5: 0.0})
