annotate env/lib/python3.9/site-packages/networkx/algorithms/tests/test_chains.py @ 0:4f3585e2f14b draft default tip

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author shellac
date Mon, 22 Mar 2021 18:12:50 +0000
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1 """Unit tests for the chain decomposition functions."""
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2 from itertools import cycle
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3 from itertools import islice
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4
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5 import networkx as nx
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6
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7
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8 def cycles(seq):
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9 """Yields cyclic permutations of the given sequence.
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10
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11 For example::
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12
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13 >>> list(cycles("abc"))
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14 [('a', 'b', 'c'), ('b', 'c', 'a'), ('c', 'a', 'b')]
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15
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16 """
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17 n = len(seq)
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18 cycled_seq = cycle(seq)
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19 for x in seq:
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20 yield tuple(islice(cycled_seq, n))
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21 next(cycled_seq)
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22
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23
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24 def cyclic_equals(seq1, seq2):
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25 """Decide whether two sequences are equal up to cyclic permutations.
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26
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27 For example::
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28
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29 >>> cyclic_equals("xyz", "zxy")
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30 True
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31 >>> cyclic_equals("xyz", "zyx")
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32 False
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33
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34 """
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35 # Cast seq2 to a tuple since `cycles()` yields tuples.
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36 seq2 = tuple(seq2)
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37 return any(x == tuple(seq2) for x in cycles(seq1))
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38
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39
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40 class TestChainDecomposition:
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41 """Unit tests for the chain decomposition function."""
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42
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43 def assertContainsChain(self, chain, expected):
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44 # A cycle could be expressed in two different orientations, one
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45 # forward and one backward, so we need to check for cyclic
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46 # equality in both orientations.
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47 reversed_chain = list(reversed([tuple(reversed(e)) for e in chain]))
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48 for candidate in expected:
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49 if cyclic_equals(chain, candidate):
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50 break
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51 if cyclic_equals(reversed_chain, candidate):
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52 break
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53 else:
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54 self.fail("chain not found")
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55
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56 def test_decomposition(self):
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57 edges = [
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58 # DFS tree edges.
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59 (1, 2),
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60 (2, 3),
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61 (3, 4),
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62 (3, 5),
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63 (5, 6),
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64 (6, 7),
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65 (7, 8),
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66 (5, 9),
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67 (9, 10),
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68 # Nontree edges.
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69 (1, 3),
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70 (1, 4),
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71 (2, 5),
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72 (5, 10),
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73 (6, 8),
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74 ]
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75 G = nx.Graph(edges)
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76 expected = [
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77 [(1, 3), (3, 2), (2, 1)],
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78 [(1, 4), (4, 3)],
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79 [(2, 5), (5, 3)],
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80 [(5, 10), (10, 9), (9, 5)],
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81 [(6, 8), (8, 7), (7, 6)],
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82 ]
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83 chains = list(nx.chain_decomposition(G, root=1))
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84 assert len(chains) == len(expected)
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85
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86 # This chain decomposition isn't unique
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87 # for chain in chains:
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88 # print(chain)
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89 # self.assertContainsChain(chain, expected)
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90
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91 def test_barbell_graph(self):
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92 # The (3, 0) barbell graph has two triangles joined by a single edge.
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93 G = nx.barbell_graph(3, 0)
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94 chains = list(nx.chain_decomposition(G, root=0))
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95 expected = [[(0, 1), (1, 2), (2, 0)], [(3, 4), (4, 5), (5, 3)]]
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96 assert len(chains) == len(expected)
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97 for chain in chains:
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98 self.assertContainsChain(chain, expected)
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99
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100 def test_disconnected_graph(self):
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101 """Test for a graph with multiple connected components."""
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102 G = nx.barbell_graph(3, 0)
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103 H = nx.barbell_graph(3, 0)
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104 mapping = dict(zip(range(6), "abcdef"))
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105 nx.relabel_nodes(H, mapping, copy=False)
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106 G = nx.union(G, H)
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107 chains = list(nx.chain_decomposition(G))
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108 expected = [
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109 [(0, 1), (1, 2), (2, 0)],
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110 [(3, 4), (4, 5), (5, 3)],
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111 [("a", "b"), ("b", "c"), ("c", "a")],
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112 [("d", "e"), ("e", "f"), ("f", "d")],
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113 ]
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114 assert len(chains) == len(expected)
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115 for chain in chains:
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116 self.assertContainsChain(chain, expected)
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117
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118 def test_disconnected_graph_root_node(self):
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119 """Test for a single component of a disconnected graph."""
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120 G = nx.barbell_graph(3, 0)
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121 H = nx.barbell_graph(3, 0)
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122 mapping = dict(zip(range(6), "abcdef"))
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123 nx.relabel_nodes(H, mapping, copy=False)
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124 G = nx.union(G, H)
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125 chains = list(nx.chain_decomposition(G, root="a"))
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126 expected = [
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127 [("a", "b"), ("b", "c"), ("c", "a")],
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128 [("d", "e"), ("e", "f"), ("f", "d")],
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129 ]
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130 assert len(chains) == len(expected)
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131 for chain in chains:
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132 self.assertContainsChain(chain, expected)