81 lines
2.8 KiB
Python
81 lines
2.8 KiB
Python
#!/usr/bin/env python
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import networkx as nx
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from networkx.testing import almost_equal
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def example1a_G():
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G = nx.Graph()
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G.add_node(1, percolation=0.1)
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G.add_node(2, percolation=0.2)
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G.add_node(3, percolation=0.2)
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G.add_node(4, percolation=0.2)
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G.add_node(5, percolation=0.3)
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G.add_node(6, percolation=0.2)
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G.add_node(7, percolation=0.5)
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G.add_node(8, percolation=0.5)
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G.add_edges_from([(1, 4), (2, 4), (3, 4), (4, 5), (5, 6), (6, 7), (6, 8)])
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return G
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def example1b_G():
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G = nx.Graph()
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G.add_node(1, percolation=0.3)
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G.add_node(2, percolation=0.5)
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G.add_node(3, percolation=0.5)
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G.add_node(4, percolation=0.2)
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G.add_node(5, percolation=0.3)
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G.add_node(6, percolation=0.2)
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G.add_node(7, percolation=0.1)
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G.add_node(8, percolation=0.1)
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G.add_edges_from([(1, 4), (2, 4), (3, 4), (4, 5), (5, 6), (6, 7), (6, 8)])
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return G
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class TestPercolationCentrality(object):
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def test_percolation_example1a(self):
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"""percolation centrality: example 1a"""
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G = example1a_G()
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p = nx.percolation_centrality(G)
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p_answer = {4: 0.625, 6: 0.667}
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for n in p_answer:
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assert almost_equal(p[n], p_answer[n], places=3)
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def test_percolation_example1b(self):
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"""percolation centrality: example 1a"""
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G = example1b_G()
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p = nx.percolation_centrality(G)
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p_answer = {4: 0.825, 6: 0.4}
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for n in p_answer:
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assert almost_equal(p[n], p_answer[n], places=3)
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def test_converge_to_betweenness(self):
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"""percolation centrality: should converge to betweenness
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centrality when all nodes are percolated the same"""
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# taken from betweenness test test_florentine_families_graph
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G = nx.florentine_families_graph()
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b_answer =\
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{'Acciaiuoli': 0.000,
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'Albizzi': 0.212,
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'Barbadori': 0.093,
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'Bischeri': 0.104,
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'Castellani': 0.055,
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'Ginori': 0.000,
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'Guadagni': 0.255,
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'Lamberteschi': 0.000,
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'Medici': 0.522,
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'Pazzi': 0.000,
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'Peruzzi': 0.022,
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'Ridolfi': 0.114,
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'Salviati': 0.143,
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'Strozzi': 0.103,
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'Tornabuoni': 0.092}
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p_states = {k: 1.0 for k, v in b_answer.items()}
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p_answer = nx.percolation_centrality(G, states=p_states)
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for n in sorted(G):
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assert almost_equal(p_answer[n], b_answer[n], places=3)
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p_states = {k: 0.3 for k, v in b_answer.items()}
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p_answer = nx.percolation_centrality(G, states=p_states)
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for n in sorted(G):
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assert almost_equal(p_answer[n], b_answer[n], places=3)
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