def test_K4_normalized(self):
"Approximate current-flow betweenness centrality: K4 normalized"
G = networkx.complete_graph(4)
b = networkx.current_flow_betweenness_centrality(G, normalized=True)
epsilon = 0.1
ba = approximate_cfbc(G, normalized=True, epsilon=0.5 * epsilon)
for n in sorted(G):
assert_allclose(b[n], ba[n], atol=epsilon)
def test_K4(self):
"Approximate current-flow betweenness centrality: K4"
G = nx.complete_graph(4)
b = nx.current_flow_betweenness_centrality(G, normalized=False)
epsilon = 0.1
ba = approximate_cfbc(G, normalized=False, epsilon=0.5 * epsilon)
for n in sorted(G):
np.testing.assert_allclose(b[n], ba[n], atol=epsilon * len(G)**2)
def test_grid(self):
"Approximate current-flow betweenness centrality: 2d grid"
G = nx.grid_2d_graph(4, 4)
b = nx.current_flow_betweenness_centrality(G, normalized=True)
epsilon = 0.1
ba = approximate_cfbc(G, normalized=True, epsilon=0.5 * epsilon)
for n in sorted(G):
np.testing.assert_allclose(b[n], ba[n], atol=epsilon)
def test_grid(self):
"Approximate current-flow betweenness centrality: 2d grid"
G=nx.grid_2d_graph(4,4)
b=nx.current_flow_betweenness_centrality(G,normalized=True)
epsilon=0.1
ba = approximate_cfbc(G,normalized=True, epsilon=0.5*epsilon)
for n in sorted(G):
assert_allclose(b[n],ba[n],atol=epsilon)
def test_K4(self):
"Approximate current-flow betweenness centrality: K4"
G=nx.complete_graph(4)
b=nx.current_flow_betweenness_centrality(G,normalized=False)
epsilon=0.1
ba = approximate_cfbc(G,normalized=False, epsilon=0.5*epsilon)
for n in sorted(G):
assert_allclose(b[n],ba[n],atol=epsilon*len(G)**2)
def test_K4_normalized(self):
"Approximate current-flow betweenness centrality: K4 normalized"
G=networkx.complete_graph(4)
b=networkx.current_flow_betweenness_centrality(G,normalized=True)
epsilon=0.1
ba = approximate_cfbc(G,normalized=True, epsilon=epsilon)
for n in sorted(G):
assert_allclose(b[n],ba[n],atol=epsilon)
def test_star(self):
"Approximate current-flow betweenness centrality: star"
G = nx.Graph()
nx.add_star(G, ["a", "b", "c", "d"])
b = nx.current_flow_betweenness_centrality(G, normalized=True)
epsilon = 0.1
ba = approximate_cfbc(G, normalized=True, epsilon=0.5 * epsilon)
for n in sorted(G):
np.testing.assert_allclose(b[n], ba[n], atol=epsilon)
def test_star(self):
"Approximate current-flow betweenness centrality: star"
G=nx.Graph()
nx.add_star(G, ['a', 'b', 'c', 'd'])
b=nx.current_flow_betweenness_centrality(G,normalized=True)
epsilon=0.1
ba = approximate_cfbc(G,normalized=True, epsilon=0.5*epsilon)
for n in sorted(G):
assert_allclose(b[n],ba[n],atol=epsilon)
def test_star(self):
"Approximate current-flow betweenness centrality: star"
G = networkx.Graph()
G.add_star(['a', 'b', 'c', 'd'])
b = networkx.current_flow_betweenness_centrality(G, normalized=True)
epsilon = 0.1
ba = approximate_cfbc(G, normalized=True, epsilon=0.5 * epsilon)
for n in sorted(G):
assert_allclose(b[n], ba[n], atol=epsilon)
def test_solvers(self):
"Approximate current-flow betweenness centrality: solvers"
G=networkx.complete_graph(4)
epsilon=0.1
for solver in ['full','lu','cg']:
b=approximate_cfbc(G,normalized=False,solver=solver,epsilon=epsilon)
b_answer={0: 0.75, 1: 0.75, 2: 0.75, 3: 0.75}
for n in sorted(G):
assert_allclose(b[n],b_answer[n],atol=epsilon)
def test_solvers(self):
"Approximate current-flow betweenness centrality: solvers"
G = nx.complete_graph(4)
epsilon = 0.1
for solver in ["full", "lu", "cg"]:
b = approximate_cfbc(
G, normalized=False, solver=solver, epsilon=0.5 * epsilon
)
b_answer = {0: 0.75, 1: 0.75, 2: 0.75, 3: 0.75}
for n in sorted(G):
np.testing.assert_allclose(b[n], b_answer[n], atol=epsilon)
def test_seed(self):
G = nx.complete_graph(4)
b = approximate_cfbc(G, normalized=False, epsilon=0.05, seed=1)
b_answer = {0: 0.75, 1: 0.75, 2: 0.75, 3: 0.75}
for n in sorted(G):
np.testing.assert_allclose(b[n], b_answer[n], atol=0.1)
def test_seed(self):
G = nx.complete_graph(4)
b = approximate_cfbc(G, normalized=False, epsilon=0.05, seed=1)
b_answer = {0: 0.75, 1: 0.75, 2: 0.75, 3: 0.75}
for n in sorted(G):
assert_allclose(b[n], b_answer[n], atol=0.1)