43 lines
1.4 KiB
Python
43 lines
1.4 KiB
Python
import networkx as nx
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def small_ego_G():
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"""The sample network from https://arxiv.org/pdf/1310.6753v1.pdf"""
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edges = [('a', 'b'), ('a', 'c'), ('b', 'c'), ('b', 'd'),
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('b', 'e'), ('b', 'f'), ('c', 'd'), ('c', 'f'), ('c', 'h'), ('d', 'f'), ('e', 'f'),
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('f', 'h'), ('h', 'j'), ('h', 'k'), ('i', 'j'), ('i', 'k'), ('j', 'k'), ('u', 'a'),
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('u', 'b'), ('u', 'c'), ('u', 'd'), ('u', 'e'), ('u', 'f'), ('u', 'g'), ('u', 'h'),
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('u', 'i'), ('u', 'j'), ('u', 'k')]
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G = nx.Graph()
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G.add_edges_from(edges)
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return G
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class TestDispersion(object):
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def test_article(self):
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"""our algorithm matches article's"""
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G = small_ego_G()
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disp_uh = nx.dispersion(G, 'u', 'h', normalized=False)
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disp_ub = nx.dispersion(G, 'u', 'b', normalized=False)
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assert disp_uh == 4
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assert disp_ub == 1
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def test_results_length(self):
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"""there is a result for every node"""
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G = small_ego_G()
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disp = nx.dispersion(G)
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disp_Gu = nx.dispersion(G, 'u')
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disp_uv = nx.dispersion(G, 'u', 'h')
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assert len(disp) == len(G)
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assert len(disp_Gu) == len(G) - 1
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assert type(disp_uv) is float
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def test_impossible_things(self):
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G = nx.karate_club_graph()
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disp = nx.dispersion(G)
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for u in disp:
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for v in disp[u]:
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assert disp[u][v] >= 0
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