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iof-tools / networkxMiCe / networkx-master / networkx / algorithms / centrality / tests / test_percolation_centrality.py @ 5cef0f13

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#!/usr/bin/env python
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from __future__ import division
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from nose.tools import *
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import networkx as nx
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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)