Mercurial > repos > shellac > sam_consensus_v3
annotate env/lib/python3.9/site-packages/networkx/algorithms/centrality/tests/test_percolation_centrality.py @ 0:4f3585e2f14b draft default tip
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author | shellac |
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date | Mon, 22 Mar 2021 18:12:50 +0000 |
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1 import networkx as nx |
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2 from networkx.testing import almost_equal |
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3 |
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4 |
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5 def example1a_G(): |
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6 G = nx.Graph() |
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7 G.add_node(1, percolation=0.1) |
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8 G.add_node(2, percolation=0.2) |
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9 G.add_node(3, percolation=0.2) |
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10 G.add_node(4, percolation=0.2) |
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11 G.add_node(5, percolation=0.3) |
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12 G.add_node(6, percolation=0.2) |
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13 G.add_node(7, percolation=0.5) |
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14 G.add_node(8, percolation=0.5) |
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15 G.add_edges_from([(1, 4), (2, 4), (3, 4), (4, 5), (5, 6), (6, 7), (6, 8)]) |
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16 return G |
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17 |
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18 |
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19 def example1b_G(): |
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20 G = nx.Graph() |
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21 G.add_node(1, percolation=0.3) |
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22 G.add_node(2, percolation=0.5) |
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23 G.add_node(3, percolation=0.5) |
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24 G.add_node(4, percolation=0.2) |
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25 G.add_node(5, percolation=0.3) |
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26 G.add_node(6, percolation=0.2) |
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27 G.add_node(7, percolation=0.1) |
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28 G.add_node(8, percolation=0.1) |
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29 G.add_edges_from([(1, 4), (2, 4), (3, 4), (4, 5), (5, 6), (6, 7), (6, 8)]) |
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30 return G |
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31 |
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32 |
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33 class TestPercolationCentrality: |
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34 def test_percolation_example1a(self): |
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35 """percolation centrality: example 1a""" |
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36 G = example1a_G() |
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37 p = nx.percolation_centrality(G) |
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38 p_answer = {4: 0.625, 6: 0.667} |
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39 for n in p_answer: |
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40 assert almost_equal(p[n], p_answer[n], places=3) |
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41 |
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42 def test_percolation_example1b(self): |
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43 """percolation centrality: example 1a""" |
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44 G = example1b_G() |
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45 p = nx.percolation_centrality(G) |
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46 p_answer = {4: 0.825, 6: 0.4} |
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47 for n in p_answer: |
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48 assert almost_equal(p[n], p_answer[n], places=3) |
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49 |
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50 def test_converge_to_betweenness(self): |
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51 """percolation centrality: should converge to betweenness |
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52 centrality when all nodes are percolated the same""" |
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53 # taken from betweenness test test_florentine_families_graph |
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54 G = nx.florentine_families_graph() |
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55 b_answer = { |
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56 "Acciaiuoli": 0.000, |
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57 "Albizzi": 0.212, |
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58 "Barbadori": 0.093, |
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59 "Bischeri": 0.104, |
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60 "Castellani": 0.055, |
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61 "Ginori": 0.000, |
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62 "Guadagni": 0.255, |
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63 "Lamberteschi": 0.000, |
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64 "Medici": 0.522, |
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65 "Pazzi": 0.000, |
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66 "Peruzzi": 0.022, |
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67 "Ridolfi": 0.114, |
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68 "Salviati": 0.143, |
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69 "Strozzi": 0.103, |
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70 "Tornabuoni": 0.092, |
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71 } |
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72 |
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73 p_states = {k: 1.0 for k, v in b_answer.items()} |
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74 p_answer = nx.percolation_centrality(G, states=p_states) |
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75 for n in sorted(G): |
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76 assert almost_equal(p_answer[n], b_answer[n], places=3) |
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77 |
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78 p_states = {k: 0.3 for k, v in b_answer.items()} |
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79 p_answer = nx.percolation_centrality(G, states=p_states) |
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80 for n in sorted(G): |
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81 assert almost_equal(p_answer[n], b_answer[n], places=3) |