Mercurial > repos > shellac > sam_consensus_v3
annotate env/lib/python3.9/site-packages/networkx/algorithms/flow/tests/test_gomory_hu.py @ 0:4f3585e2f14b draft default tip
"planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
author | shellac |
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date | Mon, 22 Mar 2021 18:12:50 +0000 |
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1 from itertools import combinations |
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2 import pytest |
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3 |
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4 import networkx as nx |
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5 from networkx.algorithms.flow import boykov_kolmogorov |
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6 from networkx.algorithms.flow import edmonds_karp |
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7 from networkx.algorithms.flow import preflow_push |
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8 from networkx.algorithms.flow import shortest_augmenting_path |
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9 from networkx.algorithms.flow import dinitz |
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10 |
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11 flow_funcs = [ |
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12 boykov_kolmogorov, |
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13 dinitz, |
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14 edmonds_karp, |
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15 preflow_push, |
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16 shortest_augmenting_path, |
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17 ] |
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18 |
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19 |
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20 class TestGomoryHuTree: |
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21 def minimum_edge_weight(self, T, u, v): |
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22 path = nx.shortest_path(T, u, v, weight="weight") |
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23 return min((T[u][v]["weight"], (u, v)) for (u, v) in zip(path, path[1:])) |
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24 |
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25 def compute_cutset(self, G, T_orig, edge): |
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26 T = T_orig.copy() |
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27 T.remove_edge(*edge) |
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28 U, V = list(nx.connected_components(T)) |
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29 cutset = set() |
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30 for x, nbrs in ((n, G[n]) for n in U): |
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31 cutset.update((x, y) for y in nbrs if y in V) |
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32 return cutset |
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33 |
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34 def test_default_flow_function_karate_club_graph(self): |
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35 G = nx.karate_club_graph() |
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36 nx.set_edge_attributes(G, 1, "capacity") |
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37 T = nx.gomory_hu_tree(G) |
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38 assert nx.is_tree(T) |
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39 for u, v in combinations(G, 2): |
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40 cut_value, edge = self.minimum_edge_weight(T, u, v) |
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41 assert nx.minimum_cut_value(G, u, v) == cut_value |
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42 |
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43 def test_karate_club_graph(self): |
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44 G = nx.karate_club_graph() |
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45 nx.set_edge_attributes(G, 1, "capacity") |
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46 for flow_func in flow_funcs: |
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47 T = nx.gomory_hu_tree(G, flow_func=flow_func) |
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48 assert nx.is_tree(T) |
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49 for u, v in combinations(G, 2): |
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50 cut_value, edge = self.minimum_edge_weight(T, u, v) |
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51 assert nx.minimum_cut_value(G, u, v) == cut_value |
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52 |
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53 def test_davis_southern_women_graph(self): |
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54 G = nx.davis_southern_women_graph() |
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55 nx.set_edge_attributes(G, 1, "capacity") |
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56 for flow_func in flow_funcs: |
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57 T = nx.gomory_hu_tree(G, flow_func=flow_func) |
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58 assert nx.is_tree(T) |
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59 for u, v in combinations(G, 2): |
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60 cut_value, edge = self.minimum_edge_weight(T, u, v) |
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61 assert nx.minimum_cut_value(G, u, v) == cut_value |
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62 |
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63 def test_florentine_families_graph(self): |
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64 G = nx.florentine_families_graph() |
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65 nx.set_edge_attributes(G, 1, "capacity") |
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66 for flow_func in flow_funcs: |
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67 T = nx.gomory_hu_tree(G, flow_func=flow_func) |
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68 assert nx.is_tree(T) |
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69 for u, v in combinations(G, 2): |
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70 cut_value, edge = self.minimum_edge_weight(T, u, v) |
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71 assert nx.minimum_cut_value(G, u, v) == cut_value |
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72 |
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73 @pytest.mark.slow |
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74 def test_les_miserables_graph_cutset(self): |
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75 G = nx.les_miserables_graph() |
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76 nx.set_edge_attributes(G, 1, "capacity") |
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77 for flow_func in flow_funcs: |
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78 T = nx.gomory_hu_tree(G, flow_func=flow_func) |
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79 assert nx.is_tree(T) |
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80 for u, v in combinations(G, 2): |
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81 cut_value, edge = self.minimum_edge_weight(T, u, v) |
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82 assert nx.minimum_cut_value(G, u, v) == cut_value |
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83 |
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84 def test_karate_club_graph_cutset(self): |
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85 G = nx.karate_club_graph() |
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86 nx.set_edge_attributes(G, 1, "capacity") |
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87 T = nx.gomory_hu_tree(G) |
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88 assert nx.is_tree(T) |
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89 u, v = 0, 33 |
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90 cut_value, edge = self.minimum_edge_weight(T, u, v) |
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91 cutset = self.compute_cutset(G, T, edge) |
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92 assert cut_value == len(cutset) |
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93 |
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94 def test_wikipedia_example(self): |
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95 # Example from https://en.wikipedia.org/wiki/Gomory%E2%80%93Hu_tree |
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96 G = nx.Graph() |
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97 G.add_weighted_edges_from( |
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98 ( |
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99 (0, 1, 1), |
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100 (0, 2, 7), |
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101 (1, 2, 1), |
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102 (1, 3, 3), |
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103 (1, 4, 2), |
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104 (2, 4, 4), |
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105 (3, 4, 1), |
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106 (3, 5, 6), |
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107 (4, 5, 2), |
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108 ) |
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109 ) |
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110 for flow_func in flow_funcs: |
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111 T = nx.gomory_hu_tree(G, capacity="weight", flow_func=flow_func) |
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112 assert nx.is_tree(T) |
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113 for u, v in combinations(G, 2): |
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114 cut_value, edge = self.minimum_edge_weight(T, u, v) |
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115 assert nx.minimum_cut_value(G, u, v, capacity="weight") == cut_value |
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116 |
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117 def test_directed_raises(self): |
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118 with pytest.raises(nx.NetworkXNotImplemented): |
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119 G = nx.DiGraph() |
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120 T = nx.gomory_hu_tree(G) |
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121 |
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122 def test_empty_raises(self): |
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123 with pytest.raises(nx.NetworkXError): |
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124 G = nx.empty_graph() |
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125 T = nx.gomory_hu_tree(G) |