1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
|
import pytest
import networkx as nx
def test_modularity_increase():
G = nx.LFR_benchmark_graph(
250, 3, 1.5, 0.009, average_degree=5, min_community=20, seed=10
)
partition = [{u} for u in G.nodes()]
mod = nx.community.modularity(G, partition)
partition = nx.community.louvain_communities(G)
assert nx.community.modularity(G, partition) > mod
def test_valid_partition():
G = nx.LFR_benchmark_graph(
250, 3, 1.5, 0.009, average_degree=5, min_community=20, seed=10
)
H = G.to_directed()
partition = nx.community.louvain_communities(G)
partition2 = nx.community.louvain_communities(H)
assert nx.community.is_partition(G, partition)
assert nx.community.is_partition(H, partition2)
def test_karate_club_partition():
G = nx.karate_club_graph()
part = [
{0, 1, 2, 3, 7, 9, 11, 12, 13, 17, 19, 21},
{16, 4, 5, 6, 10},
{23, 25, 27, 28, 24, 31},
{32, 33, 8, 14, 15, 18, 20, 22, 26, 29, 30},
]
partition = nx.community.louvain_communities(G, seed=2, weight=None)
assert part == partition
def test_partition_iterator():
G = nx.path_graph(15)
parts_iter = nx.community.louvain_partitions(G, seed=42)
first_part = next(parts_iter)
first_copy = [s.copy() for s in first_part]
# gh-5901 reports sets changing after next partition is yielded
assert first_copy[0] == first_part[0]
second_part = next(parts_iter)
assert first_copy[0] == first_part[0]
def test_undirected_selfloops():
G = nx.karate_club_graph()
expected_partition = nx.community.louvain_communities(G, seed=2, weight=None)
part = [
{0, 1, 2, 3, 7, 9, 11, 12, 13, 17, 19, 21},
{16, 4, 5, 6, 10},
{23, 25, 27, 28, 24, 31},
{32, 33, 8, 14, 15, 18, 20, 22, 26, 29, 30},
]
assert expected_partition == part
G.add_weighted_edges_from([(i, i, i * 1000) for i in range(9)])
# large self-loop weight impacts partition
partition = nx.community.louvain_communities(G, seed=2, weight="weight")
assert part != partition
# small self-loop weights aren't enough to impact partition in this graph
partition = nx.community.louvain_communities(G, seed=2, weight=None)
assert part == partition
def test_directed_selfloops():
G = nx.DiGraph()
G.add_nodes_from(range(11))
G_edges = [
(0, 2),
(0, 1),
(1, 0),
(2, 1),
(2, 0),
(3, 4),
(4, 3),
(7, 8),
(8, 7),
(9, 10),
(10, 9),
]
G.add_edges_from(G_edges)
G_expected_partition = nx.community.louvain_communities(G, seed=123, weight=None)
G.add_weighted_edges_from([(i, i, i * 1000) for i in range(3)])
# large self-loop weight impacts partition
G_partition = nx.community.louvain_communities(G, seed=123, weight="weight")
assert G_partition != G_expected_partition
# small self-loop weights aren't enough to impact partition in this graph
G_partition = nx.community.louvain_communities(G, seed=123, weight=None)
assert G_partition == G_expected_partition
def test_directed_partition():
"""
Test 2 cases that were looping infinitely
from issues #5175 and #5704
"""
G = nx.DiGraph()
H = nx.DiGraph()
G.add_nodes_from(range(10))
H.add_nodes_from([1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11])
G_edges = [
(0, 2),
(0, 1),
(1, 0),
(2, 1),
(2, 0),
(3, 4),
(4, 3),
(7, 8),
(8, 7),
(9, 10),
(10, 9),
]
H_edges = [
(1, 2),
(1, 6),
(1, 9),
(2, 3),
(2, 4),
(2, 5),
(3, 4),
(4, 3),
(4, 5),
(5, 4),
(6, 7),
(6, 8),
(9, 10),
(9, 11),
(10, 11),
(11, 10),
]
G.add_edges_from(G_edges)
H.add_edges_from(H_edges)
G_expected_partition = [{0, 1, 2}, {3, 4}, {5}, {6}, {8, 7}, {9, 10}]
G_partition = nx.community.louvain_communities(G, seed=123, weight=None)
H_expected_partition = [{2, 3, 4, 5}, {8, 1, 6, 7}, {9, 10, 11}]
H_partition = nx.community.louvain_communities(H, seed=123, weight=None)
assert G_partition == G_expected_partition
assert H_partition == H_expected_partition
def test_none_weight_param():
G = nx.karate_club_graph()
nx.set_edge_attributes(
G, {edge: i * i for i, edge in enumerate(G.edges)}, name="foo"
)
part = [
{0, 1, 2, 3, 7, 9, 11, 12, 13, 17, 19, 21},
{16, 4, 5, 6, 10},
{23, 25, 27, 28, 24, 31},
{32, 33, 8, 14, 15, 18, 20, 22, 26, 29, 30},
]
partition1 = nx.community.louvain_communities(G, weight=None, seed=2)
partition2 = nx.community.louvain_communities(G, weight="foo", seed=2)
partition3 = nx.community.louvain_communities(G, weight="weight", seed=2)
assert part == partition1
assert part != partition2
assert part != partition3
assert partition2 != partition3
def test_quality():
G = nx.LFR_benchmark_graph(
250, 3, 1.5, 0.009, average_degree=5, min_community=20, seed=10
)
H = nx.gn_graph(200, seed=1234)
I = nx.MultiGraph(G)
J = nx.MultiDiGraph(H)
partition = nx.community.louvain_communities(G)
partition2 = nx.community.louvain_communities(H)
partition3 = nx.community.louvain_communities(I)
partition4 = nx.community.louvain_communities(J)
quality = nx.community.partition_quality(G, partition)[0]
quality2 = nx.community.partition_quality(H, partition2)[0]
quality3 = nx.community.partition_quality(I, partition3)[0]
quality4 = nx.community.partition_quality(J, partition4)[0]
assert quality >= 0.65
assert quality2 >= 0.65
assert quality3 >= 0.65
assert quality4 >= 0.65
def test_multigraph():
G = nx.karate_club_graph()
H = nx.MultiGraph(G)
G.add_edge(0, 1, weight=10)
H.add_edge(0, 1, weight=9)
G.add_edge(0, 9, foo=20)
H.add_edge(0, 9, foo=20)
partition1 = nx.community.louvain_communities(G, seed=1234)
partition2 = nx.community.louvain_communities(H, seed=1234)
partition3 = nx.community.louvain_communities(H, weight="foo", seed=1234)
assert partition1 == partition2 != partition3
def test_resolution():
G = nx.LFR_benchmark_graph(
250, 3, 1.5, 0.009, average_degree=5, min_community=20, seed=10
)
partition1 = nx.community.louvain_communities(G, resolution=0.5, seed=12)
partition2 = nx.community.louvain_communities(G, seed=12)
partition3 = nx.community.louvain_communities(G, resolution=2, seed=12)
assert len(partition1) <= len(partition2) <= len(partition3)
def test_threshold():
G = nx.LFR_benchmark_graph(
250, 3, 1.5, 0.009, average_degree=5, min_community=20, seed=10
)
partition1 = nx.community.louvain_communities(G, threshold=0.3, seed=2)
partition2 = nx.community.louvain_communities(G, seed=2)
mod1 = nx.community.modularity(G, partition1)
mod2 = nx.community.modularity(G, partition2)
assert mod1 <= mod2
def test_empty_graph():
G = nx.Graph()
G.add_nodes_from(range(5))
expected = [{0}, {1}, {2}, {3}, {4}]
assert nx.community.louvain_communities(G) == expected
def test_max_level():
G = nx.LFR_benchmark_graph(
250, 3, 1.5, 0.009, average_degree=5, min_community=20, seed=10
)
parts_iter = nx.community.louvain_partitions(G, seed=42)
for max_level, expected in enumerate(parts_iter, 1):
partition = nx.community.louvain_communities(G, max_level=max_level, seed=42)
assert partition == expected
assert max_level > 1 # Ensure we are actually testing max_level
# max_level is an upper limit; it's okay if we stop before it's hit.
partition = nx.community.louvain_communities(G, max_level=max_level + 1, seed=42)
assert partition == expected
with pytest.raises(
ValueError, match="max_level argument must be a positive integer"
):
nx.community.louvain_communities(G, max_level=0)
|
