#!/usr/bin/env python from nose.tools import * import networkx from networkx import betweenness_centrality_subset,\ edge_betweenness_centrality_subset class TestSubsetBetweennessCentrality: def test_K5(self): """Betweenness centrality: K5""" G=networkx.complete_graph(5) b=betweenness_centrality_subset(G, sources=[0], targets=[1,3], weight=None) b_answer={0: 0.0, 1: 0.0, 2: 0.0, 3: 0.0, 4: 0.0} for n in sorted(G): assert_almost_equal(b[n],b_answer[n]) def test_P5_directed(self): """Betweenness centrality: P5 directed""" G=networkx.DiGraph() G.add_path(list(range(5))) b_answer={0:0,1:1,2:1,3:0,4:0,5:0} b=betweenness_centrality_subset(G, sources=[0], targets=[3], weight=None) for n in sorted(G): assert_almost_equal(b[n],b_answer[n]) def test_P5(self): """Betweenness centrality: P5""" G=networkx.Graph() G.add_path(list(range(5))) b_answer={0:0,1:0.5,2:0.5,3:0,4:0,5:0} b=betweenness_centrality_subset(G, sources=[0], targets=[3], weight=None) for n in sorted(G): assert_almost_equal(b[n],b_answer[n]) def test_P5_multiple_target(self): """Betweenness centrality: P5 multiple target""" G=networkx.Graph() G.add_path(list(range(5))) b_answer={0:0,1:1,2:1,3:0.5,4:0,5:0} b=betweenness_centrality_subset(G, sources=[0], targets=[3,4], weight=None) for n in sorted(G): assert_almost_equal(b[n],b_answer[n]) def test_box(self): """Betweenness centrality: box""" G=networkx.Graph() G.add_edge(0,1) G.add_edge(0,2) G.add_edge(1,3) G.add_edge(2,3) b_answer={0:0,1:0.25,2:0.25,3:0} b=betweenness_centrality_subset(G, sources=[0], targets=[3], weight=None) for n in sorted(G): assert_almost_equal(b[n],b_answer[n]) def test_box_and_path(self): """Betweenness centrality: box and path""" G=networkx.Graph() G.add_edge(0,1) G.add_edge(0,2) G.add_edge(1,3) G.add_edge(2,3) G.add_edge(3,4) G.add_edge(4,5) b_answer={0:0,1:0.5,2:0.5,3:0.5,4:0,5:0} b=betweenness_centrality_subset(G, sources=[0], targets=[3,4], weight=None) for n in sorted(G): assert_almost_equal(b[n],b_answer[n]) def test_box_and_path2(self): """Betweenness centrality: box and path multiple target""" G=networkx.Graph() G.add_edge(0,1) G.add_edge(1,2) G.add_edge(2,3) G.add_edge(1,20) G.add_edge(20,3) G.add_edge(3,4) b_answer={0:0,1:1.0,2:0.5,20:0.5,3:0.5,4:0} b=betweenness_centrality_subset(G, sources=[0], targets=[3,4]) for n in sorted(G): assert_almost_equal(b[n],b_answer[n]) class TestBetweennessCentralitySources: def test_K5(self): """Betweenness centrality: K5""" G=networkx.complete_graph(5) b=networkx.betweenness_centrality_source(G, weight=None, normalized=False) b_answer={0: 0.0, 1: 0.0, 2: 0.0, 3: 0.0, 4: 0.0} for n in sorted(G): assert_almost_equal(b[n],b_answer[n]) def test_P3(self): """Betweenness centrality: P3""" G=networkx.path_graph(3) b_answer={0: 0.0, 1: 1.0, 2: 0.0} b=networkx.betweenness_centrality_source(G, weight=None, normalized=True) for n in sorted(G): assert_almost_equal(b[n],b_answer[n]) class TestEdgeSubsetBetweennessCentrality: def test_K5(self): """Edge betweenness centrality: K5""" G=networkx.complete_graph(5) b=edge_betweenness_centrality_subset(G, sources=[0], targets=[1,3], weight=None) b_answer=dict.fromkeys(G.edges(),0) b_answer[(0,3)]=0.5 b_answer[(0,1)]=0.5 for n in sorted(G.edges()): print(n,b[n]) assert_almost_equal(b[n],b_answer[n]) def test_P5_directed(self): """Edge betweenness centrality: P5 directed""" G=networkx.DiGraph() G.add_path(list(range(5))) b_answer=dict.fromkeys(G.edges(),0) b_answer[(0,1)]=1 b_answer[(1,2)]=1 b_answer[(2,3)]=1 b=edge_betweenness_centrality_subset(G, sources=[0], targets=[3], weight=None) for n in sorted(G.edges()): assert_almost_equal(b[n],b_answer[n]) def test_P5(self): """Edge betweenness centrality: P5""" G=networkx.Graph() G.add_path(list(range(5))) b_answer=dict.fromkeys(G.edges(),0) b_answer[(0,1)]=0.5 b_answer[(1,2)]=0.5 b_answer[(2,3)]=0.5 b=edge_betweenness_centrality_subset(G, sources=[0], targets=[3], weight=None) for n in sorted(G.edges()): assert_almost_equal(b[n],b_answer[n]) def test_P5_multiple_target(self): """Edge betweenness centrality: P5 multiple target""" G=networkx.Graph() G.add_path(list(range(5))) b_answer=dict.fromkeys(G.edges(),0) b_answer[(0,1)]=1 b_answer[(1,2)]=1 b_answer[(2,3)]=1 b_answer[(3,4)]=0.5 b=edge_betweenness_centrality_subset(G, sources=[0], targets=[3,4], weight=None) for n in sorted(G.edges()): assert_almost_equal(b[n],b_answer[n]) def test_box(self): """Edge etweenness centrality: box""" G=networkx.Graph() G.add_edge(0,1) G.add_edge(0,2) G.add_edge(1,3) G.add_edge(2,3) b_answer=dict.fromkeys(G.edges(),0) b_answer[(0,1)]=0.25 b_answer[(0,2)]=0.25 b_answer[(1,3)]=0.25 b_answer[(2,3)]=0.25 b=edge_betweenness_centrality_subset(G, sources=[0], targets=[3], weight=None) for n in sorted(G.edges()): assert_almost_equal(b[n],b_answer[n]) def test_box_and_path(self): """Edge etweenness centrality: box and path""" G=networkx.Graph() G.add_edge(0,1) G.add_edge(0,2) G.add_edge(1,3) G.add_edge(2,3) G.add_edge(3,4) G.add_edge(4,5) b_answer=dict.fromkeys(G.edges(),0) b_answer[(0,1)]=1.0/2 b_answer[(0,2)]=1.0/2 b_answer[(1,3)]=1.0/2 b_answer[(2,3)]=1.0/2 b_answer[(3,4)]=1.0/2 b=edge_betweenness_centrality_subset(G, sources=[0], targets=[3,4], weight=None) for n in sorted(G.edges()): assert_almost_equal(b[n],b_answer[n]) def test_box_and_path2(self): """Edge betweenness centrality: box and path multiple target""" G=networkx.Graph() G.add_edge(0,1) G.add_edge(1,2) G.add_edge(2,3) G.add_edge(1,20) G.add_edge(20,3) G.add_edge(3,4) b_answer=dict.fromkeys(G.edges(),0) b_answer[(0,1)]=1.0 b_answer[(1,20)]=1.0/2 b_answer[(3,20)]=1.0/2 b_answer[(1,2)]=1.0/2 b_answer[(2,3)]=1.0/2 b_answer[(3,4)]=1.0/2 b=edge_betweenness_centrality_subset(G, sources=[0], targets=[3,4], weight=None) for n in sorted(G.edges()): assert_almost_equal(b[n],b_answer[n])