def test_betweenness_centrality(self):
c = nx.bipartite_betweenness_centrality(self.P4, [1, 3])
answer = {0: 0.0, 1: 1.0, 2: 1.0, 3: 0.0}
assert_equal(c, answer)
c = nx.bipartite_betweenness_centrality(self.K3, [0, 1, 2])
answer = {0: 0.125, 1: 0.125, 2: 0.125, 3: 0.125, 4: 0.125, 5: 0.125}
assert_equal(c, answer)
c = nx.bipartite_betweenness_centrality(self.C4, [0, 2])
answer = {0: 0.25, 1: 0.25, 2: 0.25, 3: 0.25}
assert_equal(c, answer)
def test_betweenness_centrality(self):
c = nx.bipartite_betweenness_centrality(self.P4, [1,3])
answer = {0: 0.0, 1: 1.0, 2: 1.0, 3: 0.0}
assert_equal(c, answer)
c = nx.bipartite_betweenness_centrality(self.K3, [0,1,2])
answer = {0: 0.125, 1: 0.125, 2: 0.125, 3: 0.125, 4: 0.125, 5: 0.125}
assert_equal(c, answer)
c = nx.bipartite_betweenness_centrality(self.C4, [0,2])
answer = {0: 0.25, 1: 0.25, 2: 0.25, 3: 0.25}
assert_equal(c, answer)
def test_davis_betweenness_centrality(self):
G = self.davis
bet = nx.bipartite_betweenness_centrality(G, self.top_nodes)
answer = {
'E8': 0.24,
'E9': 0.23,
'E7': 0.13,
'Nora Fayette': 0.11,
'Evelyn Jefferson': 0.10,
'Theresa Anderson': 0.09,
'E6': 0.07,
'Sylvia Avondale': 0.07,
'Laura Mandeville': 0.05,
'Brenda Rogers': 0.05,
'Katherina Rogers': 0.05,
'E5': 0.04,
'Helen Lloyd': 0.04,
'E3': 0.02,
'Ruth DeSand': 0.02,
'Verne Sanderson': 0.02,
'E12': 0.02,
'Myra Liddel': 0.02,
'E11': 0.02,
'Eleanor Nye': 0.01,
'Frances Anderson': 0.01,
'Pearl Oglethorpe': 0.01,
'E4': 0.01,
'Charlotte McDowd': 0.01,
'E10': 0.01,
'Olivia Carleton': 0.01,
'Flora Price': 0.01,
'E2': 0.00,
'E1': 0.00,
'Dorothy Murchison': 0.00,
'E13': 0.00,
'E14': 0.00
}
for node, value in answer.items():
assert_almost_equal(value, bet[node], places=2)
def test_davis_betweenness_centrality(self):
G = self.davis
bet = nx.bipartite_betweenness_centrality(G, self.top_nodes)
answer = {'E8':0.24,
'E9':0.23,
'E7':0.13,
'Nora Fayette':0.11,
'Evelyn Jefferson':0.10,
'Theresa Anderson':0.09,
'E6':0.07,
'Sylvia Avondale':0.07,
'Laura Mandeville':0.05,
'Brenda Rogers':0.05,
'Katherina Rogers':0.05,
'E5':0.04,
'Helen Lloyd':0.04,
'E3':0.02,
'Ruth DeSand':0.02,
'Verne Sanderson':0.02,
'E12':0.02,
'Myra Liddel':0.02,
'E11':0.02,
'Eleanor Nye':0.01,
'Frances Anderson':0.01,
'Pearl Oglethorpe':0.01,
'E4':0.01,
'Charlotte McDowd':0.01,
'E10':0.01,
'Olivia Carleton':0.01,
'Flora Price':0.01,
'E2':0.00,
'E1':0.00,
'Dorothy Murchison':0.00,
'E13':0.00,
'E14':0.00}
for node, value in answer.items():
assert_almost_equal(value, bet[node], places=2)
