def test_eigenvector_v_katz_random(self):
G = nx.gnp_random_graph(10, 0.5, seed=1234)
l = float(max(eigvals(nx.adjacency_matrix(G).todense())))
e = nx.eigenvector_centrality_numpy(G)
k = nx.katz_centrality_numpy(G, 1.0 / l)
for n in G:
assert almost_equal(e[n], k[n])
def test_P3_unweighted(self):
"""Katz centrality: P3"""
alpha = 0.1
G = nx.path_graph(3)
b_answer = {
0: 0.5598852584152165,
1: 0.6107839182711449,
2: 0.5598852584152162
}
b = nx.katz_centrality_numpy(G, alpha, weight=None)
for n in sorted(G):
assert almost_equal(b[n], b_answer[n], places=4)
def test_beta_as_dict(self):
alpha = 0.1
beta = {0: 1.0, 1: 1.0, 2: 1.0}
b_answer = {
0: 0.5598852584152165,
1: 0.6107839182711449,
2: 0.5598852584152162
}
G = nx.path_graph(3)
b = nx.katz_centrality_numpy(G, alpha, beta)
for n in sorted(G):
assert almost_equal(b[n], b_answer[n], places=4)
def test_multiple_alpha(self):
alpha_list = [0.1, 0.2, 0.3, 0.4, 0.5, 0.6]
for alpha in alpha_list:
b_answer = {
0.1: {
0: 0.5598852584152165,
1: 0.6107839182711449,
2: 0.5598852584152162,
},
0.2: {
0: 0.5454545454545454,
1: 0.6363636363636365,
2: 0.5454545454545454,
},
0.3: {
0: 0.5333964609104419,
1: 0.6564879518897746,
2: 0.5333964609104419,
},
0.4: {
0: 0.5232045649263551,
1: 0.6726915834767423,
2: 0.5232045649263551,
},
0.5: {
0: 0.5144957746691622,
1: 0.6859943117075809,
2: 0.5144957746691622,
},
0.6: {
0: 0.5069794004195823,
1: 0.6970966755769258,
2: 0.5069794004195823,
},
}
G = nx.path_graph(3)
b = nx.katz_centrality_numpy(G, alpha)
for n in sorted(G):
assert almost_equal(b[n], b_answer[alpha][n], places=4)
def test_katz_centrality_unweighted(self):
H = self.H
alpha = self.H.alpha
p = nx.katz_centrality_numpy(H, alpha, weight="weight")
for (a, b) in zip(list(p.values()), self.H.evc):
assert almost_equal(a, b)
def test_bad_beta_numbe(self):
with pytest.raises(nx.NetworkXException):
G = nx.Graph([(0, 1)])
e = nx.katz_centrality_numpy(G, 0.1, beta="foo")
def test_bad_beta(self):
with pytest.raises(nx.NetworkXException):
G = nx.Graph([(0, 1)])
beta = {0: 77}
e = nx.katz_centrality_numpy(G, 0.1, beta=beta)