def test_krackhardt_kite_graph(self):
"""Weighted betweenness centrality: Krackhardt kite graph"""
G = nx.krackhardt_kite_graph()
G = nx.Graph(G)
for e in G.edges:
G.edges[e]["weight"] = 1
b_answer = {
0: 1.667,
1: 1.667,
2: 0.000,
3: 7.333,
4: 0.000,
5: 16.667,
6: 16.667,
7: 28.000,
8: 16.000,
9: 0.000,
}
for b in b_answer:
b_answer[b] /= 2
b = nx.builtin.betweenness_centrality(G,
weight="weight",
normalized=False)
for n in sorted(G):
assert almost_equal(b[n], b_answer[n], 3)
def test_krackhardt_kite_graph_normalized(self):
"""Weighted betweenness centrality:
Krackhardt kite graph normalized
"""
G = nx.krackhardt_kite_graph()
G = nx.Graph(G)
for e in G.edges:
G.edges[e]["weight"] = 1
b_answer = {
0: 0.023,
1: 0.023,
2: 0.000,
3: 0.102,
4: 0.000,
5: 0.231,
6: 0.231,
7: 0.389,
8: 0.222,
9: 0.000,
}
b = nx.builtin.betweenness_centrality(G,
weight="weight",
normalized=True)
for n in sorted(G):
assert almost_equal(b[n], b_answer[n], 3)
def setup_class(cls):
cls.K = nx.krackhardt_kite_graph()
cls.P3 = nx.path_graph(3)
cls.P4 = nx.path_graph(4)
cls.K5 = nx.complete_graph(5)
cls.C4 = nx.cycle_graph(4)
cls.T = nx.balanced_tree(r=2, h=2)
cls.Gb = nx.Graph()
cls.Gb.add_edges_from([(0, 1), (0, 2), (1, 3), (2, 3), (2, 4), (4, 5),
(3, 5)])
F = nx.florentine_families_graph()
cls.F = F
cls.LM = nx.les_miserables_graph()
# Create random undirected, unweighted graph for testing incremental version
cls.undirected_G = nx.fast_gnp_random_graph(n=100, p=0.6, seed=123)
cls.undirected_G_cc = nx.builtin.closeness_centrality(cls.undirected_G)