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)