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):
"""Eigenvector centrality: P3"""
G = nx.path_graph(3)
b_answer = {0: 0.5, 1: 0.7071, 2: 0.5}
b = nx.eigenvector_centrality_numpy(G, weight=None)
for n in sorted(G):
assert almost_equal(b[n], b_answer[n], places=4)
def test_K5_unweighted(self):
"""Katz centrality: K5"""
G = nx.complete_graph(5)
alpha = 0.1
b = nx.katz_centrality(G, alpha, weight=None)
v = math.sqrt(1 / 5.0)
b_answer = dict.fromkeys(G, v)
for n in sorted(G):
assert almost_equal(b[n], b_answer[n])
nstart = dict([(n, 1) for n in G])
b = nx.eigenvector_centrality_numpy(G, weight=None)
for n in sorted(G):
assert almost_equal(b[n], b_answer[n], places=3)
def test_K5(self):
"""Eigenvector centrality: K5"""
G = nx.complete_graph(5)
b = nx.eigenvector_centrality(G)
v = math.sqrt(1 / 5.0)
b_answer = dict.fromkeys(G, v)
for n in sorted(G):
assert almost_equal(b[n], b_answer[n])
nstart = dict([(n, 1) for n in G])
b = nx.eigenvector_centrality(G, nstart=nstart)
for n in sorted(G):
assert almost_equal(b[n], b_answer[n])
b = nx.eigenvector_centrality_numpy(G)
for n in sorted(G):
assert almost_equal(b[n], b_answer[n], places=3)
def test_empty_numpy(self):
with pytest.raises(nx.NetworkXException):
e = nx.eigenvector_centrality_numpy(nx.Graph())
def test_eigenvector_centrality_unweighted_numpy(self):
G = self.H
p = nx.eigenvector_centrality_numpy(G)
for (a, b) in zip(list(p.values()), self.G.evc):
assert almost_equal(a, b)