Mercurial > repos > shellac > sam_consensus_v3
diff env/lib/python3.9/site-packages/networkx/algorithms/bipartite/tests/test_centrality.py @ 0:4f3585e2f14b draft default tip
"planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
author | shellac |
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date | Mon, 22 Mar 2021 18:12:50 +0000 |
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--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/env/lib/python3.9/site-packages/networkx/algorithms/bipartite/tests/test_centrality.py Mon Mar 22 18:12:50 2021 +0000 @@ -0,0 +1,175 @@ +import networkx as nx +from networkx.algorithms import bipartite +from networkx.testing import almost_equal + + +class TestBipartiteCentrality: + @classmethod + def setup_class(cls): + cls.P4 = nx.path_graph(4) + cls.K3 = nx.complete_bipartite_graph(3, 3) + cls.C4 = nx.cycle_graph(4) + cls.davis = nx.davis_southern_women_graph() + cls.top_nodes = [ + n for n, d in cls.davis.nodes(data=True) if d["bipartite"] == 0 + ] + + def test_degree_centrality(self): + d = bipartite.degree_centrality(self.P4, [1, 3]) + answer = {0: 0.5, 1: 1.0, 2: 1.0, 3: 0.5} + assert d == answer + d = bipartite.degree_centrality(self.K3, [0, 1, 2]) + answer = {0: 1.0, 1: 1.0, 2: 1.0, 3: 1.0, 4: 1.0, 5: 1.0} + assert d == answer + d = bipartite.degree_centrality(self.C4, [0, 2]) + answer = {0: 1.0, 1: 1.0, 2: 1.0, 3: 1.0} + assert d == answer + + def test_betweenness_centrality(self): + c = bipartite.betweenness_centrality(self.P4, [1, 3]) + answer = {0: 0.0, 1: 1.0, 2: 1.0, 3: 0.0} + assert c == answer + c = 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 c == answer + c = bipartite.betweenness_centrality(self.C4, [0, 2]) + answer = {0: 0.25, 1: 0.25, 2: 0.25, 3: 0.25} + assert c == answer + + def test_closeness_centrality(self): + c = bipartite.closeness_centrality(self.P4, [1, 3]) + answer = {0: 2.0 / 3, 1: 1.0, 2: 1.0, 3: 2.0 / 3} + assert c == answer + c = bipartite.closeness_centrality(self.K3, [0, 1, 2]) + answer = {0: 1.0, 1: 1.0, 2: 1.0, 3: 1.0, 4: 1.0, 5: 1.0} + assert c == answer + c = bipartite.closeness_centrality(self.C4, [0, 2]) + answer = {0: 1.0, 1: 1.0, 2: 1.0, 3: 1.0} + assert c == answer + G = nx.Graph() + G.add_node(0) + G.add_node(1) + c = bipartite.closeness_centrality(G, [0]) + assert c == {1: 0.0} + c = bipartite.closeness_centrality(G, [1]) + assert c == {1: 0.0} + + def test_davis_degree_centrality(self): + G = self.davis + deg = bipartite.degree_centrality(G, self.top_nodes) + answer = { + "E8": 0.78, + "E9": 0.67, + "E7": 0.56, + "Nora Fayette": 0.57, + "Evelyn Jefferson": 0.57, + "Theresa Anderson": 0.57, + "E6": 0.44, + "Sylvia Avondale": 0.50, + "Laura Mandeville": 0.50, + "Brenda Rogers": 0.50, + "Katherina Rogers": 0.43, + "E5": 0.44, + "Helen Lloyd": 0.36, + "E3": 0.33, + "Ruth DeSand": 0.29, + "Verne Sanderson": 0.29, + "E12": 0.33, + "Myra Liddel": 0.29, + "E11": 0.22, + "Eleanor Nye": 0.29, + "Frances Anderson": 0.29, + "Pearl Oglethorpe": 0.21, + "E4": 0.22, + "Charlotte McDowd": 0.29, + "E10": 0.28, + "Olivia Carleton": 0.14, + "Flora Price": 0.14, + "E2": 0.17, + "E1": 0.17, + "Dorothy Murchison": 0.14, + "E13": 0.17, + "E14": 0.17, + } + for node, value in answer.items(): + assert almost_equal(value, deg[node], places=2) + + def test_davis_betweenness_centrality(self): + G = self.davis + bet = 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_closeness_centrality(self): + G = self.davis + clos = bipartite.closeness_centrality(G, self.top_nodes) + answer = { + "E8": 0.85, + "E9": 0.79, + "E7": 0.73, + "Nora Fayette": 0.80, + "Evelyn Jefferson": 0.80, + "Theresa Anderson": 0.80, + "E6": 0.69, + "Sylvia Avondale": 0.77, + "Laura Mandeville": 0.73, + "Brenda Rogers": 0.73, + "Katherina Rogers": 0.73, + "E5": 0.59, + "Helen Lloyd": 0.73, + "E3": 0.56, + "Ruth DeSand": 0.71, + "Verne Sanderson": 0.71, + "E12": 0.56, + "Myra Liddel": 0.69, + "E11": 0.54, + "Eleanor Nye": 0.67, + "Frances Anderson": 0.67, + "Pearl Oglethorpe": 0.67, + "E4": 0.54, + "Charlotte McDowd": 0.60, + "E10": 0.55, + "Olivia Carleton": 0.59, + "Flora Price": 0.59, + "E2": 0.52, + "E1": 0.52, + "Dorothy Murchison": 0.65, + "E13": 0.52, + "E14": 0.52, + } + for node, value in answer.items(): + assert almost_equal(value, clos[node], places=2)