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networkx / algorithms / centrality / tests / test_subgraph.py
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from collections import defaultdict
from nose.tools import *
from nose import SkipTest
import networkx as nx
from networkx.algorithms.centrality.subgraph_alg import *


class TestSubgraph:
    @classmethod
    def setupClass(cls):
        global numpy
        global scipy
        try:
            import numpy
        except ImportError:
            raise SkipTest('NumPy not available.')
        try:
            import scipy
        except ImportError:
            raise SkipTest('SciPy not available.')

    def test_subgraph_centrality(self):
        answer = {0: 1.5430806348152433, 1: 1.5430806348152433}
        result = subgraph_centrality(nx.path_graph(2))
        for k, v in result.items():
            assert_almost_equal(answer[k], result[k], places=7)

        answer1 = {'1': 1.6445956054135658,
                   'Albert': 2.4368257358712189,
                   'Aric': 2.4368257358712193,
                   'Dan': 3.1306328496328168,
                   'Franck': 2.3876142275231915}
        G1 = nx.Graph([('Franck', 'Aric'), ('Aric', 'Dan'), ('Dan', 'Albert'),
                       ('Albert', 'Franck'), ('Dan', '1'), ('Franck', 'Albert')])
        result1 = subgraph_centrality(G1)
        for k, v in result1.items():
            assert_almost_equal(answer1[k], result1[k], places=7)
        result1 = subgraph_centrality_exp(G1)
        for k, v in result1.items():
            assert_almost_equal(answer1[k], result1[k], places=7)

    def test_subgraph_centrality_big_graph(self):
        g199 = nx.complete_graph(199)
        g200 = nx.complete_graph(200)

        comm199 = nx.subgraph_centrality(g199)
        comm199_exp = nx.subgraph_centrality_exp(g199)

        comm200 = nx.subgraph_centrality(g200)
        comm200_exp = nx.subgraph_centrality_exp(g200)

    def test_communicability_betweenness_centrality(self):
        answer = {0: 0.07017447951484615, 1: 0.71565598701107991,
                  2: 0.71565598701107991, 3: 0.07017447951484615}
        result = communicability_betweenness_centrality(nx.path_graph(4))
        for k, v in result.items():
            assert_almost_equal(answer[k], result[k], places=7)

        answer1 = {'1': 0.060039074193949521,
                   'Albert': 0.315470761661372,
                   'Aric': 0.31547076166137211,
                   'Dan': 0.68297778678316201,
                   'Franck': 0.21977926617449497}
        G1 = nx.Graph([('Franck', 'Aric'),
                       ('Aric', 'Dan'), ('Dan', 'Albert'), ('Albert', 'Franck'),
                       ('Dan', '1'), ('Franck', 'Albert')])
        result1 = communicability_betweenness_centrality(G1)
        for k, v in result1.items():
            assert_almost_equal(answer1[k], result1[k], places=7)

    def test_estrada_index(self):
        answer = 1041.2470334195475
        result = estrada_index(nx.karate_club_graph())
        assert_almost_equal(answer, result, places=7)