Mercurial > repos > shellac > sam_consensus_v3
annotate env/lib/python3.9/sitepackages/networkx/algorithms/tests/test_dag.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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0
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1 from itertools import combinations, permutations 
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2 
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3 import pytest 
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4 
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5 import networkx as nx 
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6 from networkx.testing.utils import assert_edges_equal 
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7 from networkx.utils import consume 
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8 from networkx.utils import pairwise 
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9 
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10 
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11 class TestDagLongestPath: 
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12 """Unit tests computing the longest path in a directed acyclic graph.""" 
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13 
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14 def test_empty(self): 
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15 G = nx.DiGraph() 
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16 assert nx.dag_longest_path(G) == [] 
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17 
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18 def test_unweighted1(self): 
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19 edges = [(1, 2), (2, 3), (2, 4), (3, 5), (5, 6), (3, 7)] 
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20 G = nx.DiGraph(edges) 
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21 assert nx.dag_longest_path(G) == [1, 2, 3, 5, 6] 
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22 
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23 def test_unweighted2(self): 
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24 edges = [(1, 2), (2, 3), (3, 4), (4, 5), (1, 3), (1, 5), (3, 5)] 
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25 G = nx.DiGraph(edges) 
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26 assert nx.dag_longest_path(G) == [1, 2, 3, 4, 5] 
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27 
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28 def test_weighted(self): 
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29 G = nx.DiGraph() 
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30 edges = [(1, 2, 5), (2, 3, 1), (3, 4, 1), (4, 5, 0), (3, 5, 4), (1, 6, 2)] 
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31 G.add_weighted_edges_from(edges) 
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32 assert nx.dag_longest_path(G) == [2, 3, 5] 
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33 
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34 def test_undirected_not_implemented(self): 
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35 G = nx.Graph() 
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36 pytest.raises(nx.NetworkXNotImplemented, nx.dag_longest_path, G) 
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37 
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38 def test_unorderable_nodes(self): 
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39 """Tests that computing the longest path does not depend on 
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40 nodes being orderable. 
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41 
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42 For more information, see issue #1989. 
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43 
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44 """ 
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45 # Create the directed path graph on four nodes in a diamond shape, 
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46 # with nodes represented as (unorderable) Python objects. 
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47 nodes = [object() for n in range(4)] 
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48 G = nx.DiGraph() 
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49 G.add_edge(nodes[0], nodes[1]) 
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50 G.add_edge(nodes[0], nodes[2]) 
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51 G.add_edge(nodes[2], nodes[3]) 
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52 G.add_edge(nodes[1], nodes[3]) 
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53 
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54 # this will raise NotImplementedError when nodes need to be ordered 
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55 nx.dag_longest_path(G) 
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56 
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57 
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58 class TestDagLongestPathLength: 
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59 """Unit tests for computing the length of a longest path in a 
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60 directed acyclic graph. 
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61 
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62 """ 
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63 
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64 def test_unweighted(self): 
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65 edges = [(1, 2), (2, 3), (2, 4), (3, 5), (5, 6), (5, 7)] 
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66 G = nx.DiGraph(edges) 
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67 assert nx.dag_longest_path_length(G) == 4 
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68 
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69 edges = [(1, 2), (2, 3), (3, 4), (4, 5), (1, 3), (1, 5), (3, 5)] 
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70 G = nx.DiGraph(edges) 
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71 assert nx.dag_longest_path_length(G) == 4 
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72 
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73 # test degenerate graphs 
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74 G = nx.DiGraph() 
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75 G.add_node(1) 
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76 assert nx.dag_longest_path_length(G) == 0 
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77 
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78 def test_undirected_not_implemented(self): 
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79 G = nx.Graph() 
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80 pytest.raises(nx.NetworkXNotImplemented, nx.dag_longest_path_length, G) 
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81 
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82 def test_weighted(self): 
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83 edges = [(1, 2, 5), (2, 3, 1), (3, 4, 1), (4, 5, 0), (3, 5, 4), (1, 6, 2)] 
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84 G = nx.DiGraph() 
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85 G.add_weighted_edges_from(edges) 
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86 assert nx.dag_longest_path_length(G) == 5 
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87 
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88 
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89 class TestDAG: 
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90 @classmethod 
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91 def setup_class(cls): 
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92 pass 
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93 
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94 def test_topological_sort1(self): 
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95 DG = nx.DiGraph([(1, 2), (1, 3), (2, 3)]) 
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96 
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97 for algorithm in [nx.topological_sort, nx.lexicographical_topological_sort]: 
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98 assert tuple(algorithm(DG)) == (1, 2, 3) 
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99 
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100 DG.add_edge(3, 2) 
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101 
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102 for algorithm in [nx.topological_sort, nx.lexicographical_topological_sort]: 
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103 pytest.raises(nx.NetworkXUnfeasible, consume, algorithm(DG)) 
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104 
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105 DG.remove_edge(2, 3) 
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106 
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107 for algorithm in [nx.topological_sort, nx.lexicographical_topological_sort]: 
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108 assert tuple(algorithm(DG)) == (1, 3, 2) 
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109 
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110 DG.remove_edge(3, 2) 
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111 
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112 assert tuple(nx.topological_sort(DG)) in {(1, 2, 3), (1, 3, 2)} 
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113 assert tuple(nx.lexicographical_topological_sort(DG)) == (1, 2, 3) 
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114 
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115 def test_is_directed_acyclic_graph(self): 
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116 G = nx.generators.complete_graph(2) 
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117 assert not nx.is_directed_acyclic_graph(G) 
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118 assert not nx.is_directed_acyclic_graph(G.to_directed()) 
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119 assert not nx.is_directed_acyclic_graph(nx.Graph([(3, 4), (4, 5)])) 
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120 assert nx.is_directed_acyclic_graph(nx.DiGraph([(3, 4), (4, 5)])) 
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121 
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122 def test_topological_sort2(self): 
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123 DG = nx.DiGraph( 
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124 { 
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125 1: [2], 
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126 2: [3], 
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127 3: [4], 
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128 4: [5], 
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129 5: [1], 
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130 11: [12], 
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131 12: [13], 
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132 13: [14], 
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133 14: [15], 
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134 } 
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135 ) 
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136 pytest.raises(nx.NetworkXUnfeasible, consume, nx.topological_sort(DG)) 
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137 
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138 assert not nx.is_directed_acyclic_graph(DG) 
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139 
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140 DG.remove_edge(1, 2) 
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141 consume(nx.topological_sort(DG)) 
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142 assert nx.is_directed_acyclic_graph(DG) 
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143 
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144 def test_topological_sort3(self): 
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145 DG = nx.DiGraph() 
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146 DG.add_edges_from([(1, i) for i in range(2, 5)]) 
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147 DG.add_edges_from([(2, i) for i in range(5, 9)]) 
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148 DG.add_edges_from([(6, i) for i in range(9, 12)]) 
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149 DG.add_edges_from([(4, i) for i in range(12, 15)]) 
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150 
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151 def validate(order): 
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152 assert isinstance(order, list) 
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153 assert set(order) == set(DG) 
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154 for u, v in combinations(order, 2): 
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155 assert not nx.has_path(DG, v, u) 
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156 
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157 validate(list(nx.topological_sort(DG))) 
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158 
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159 DG.add_edge(14, 1) 
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160 pytest.raises(nx.NetworkXUnfeasible, consume, nx.topological_sort(DG)) 
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161 
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162 def test_topological_sort4(self): 
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163 G = nx.Graph() 
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164 G.add_edge(1, 2) 
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165 # Only directed graphs can be topologically sorted. 
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166 pytest.raises(nx.NetworkXError, consume, nx.topological_sort(G)) 
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167 
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168 def test_topological_sort5(self): 
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169 G = nx.DiGraph() 
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170 G.add_edge(0, 1) 
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171 assert list(nx.topological_sort(G)) == [0, 1] 
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172 
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173 def test_topological_sort6(self): 
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174 for algorithm in [nx.topological_sort, nx.lexicographical_topological_sort]: 
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175 
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176 def runtime_error(): 
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177 DG = nx.DiGraph([(1, 2), (2, 3), (3, 4)]) 
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178 first = True 
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179 for x in algorithm(DG): 
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180 if first: 
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181 first = False 
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182 DG.add_edge(5  x, 5) 
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183 
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184 def unfeasible_error(): 
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185 DG = nx.DiGraph([(1, 2), (2, 3), (3, 4)]) 
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186 first = True 
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187 for x in algorithm(DG): 
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188 if first: 
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189 first = False 
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190 DG.remove_node(4) 
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191 
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192 def runtime_error2(): 
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193 DG = nx.DiGraph([(1, 2), (2, 3), (3, 4)]) 
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194 first = True 
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195 for x in algorithm(DG): 
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196 if first: 
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197 first = False 
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198 DG.remove_node(2) 
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199 
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200 pytest.raises(RuntimeError, runtime_error) 
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201 pytest.raises(RuntimeError, runtime_error2) 
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202 pytest.raises(nx.NetworkXUnfeasible, unfeasible_error) 
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203 
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204 def test_all_topological_sorts_1(self): 
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205 DG = nx.DiGraph([(1, 2), (2, 3), (3, 4), (4, 5)]) 
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206 assert list(nx.all_topological_sorts(DG)) == [[1, 2, 3, 4, 5]] 
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207 
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208 def test_all_topological_sorts_2(self): 
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209 DG = nx.DiGraph([(1, 3), (2, 1), (2, 4), (4, 3), (4, 5)]) 
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210 assert sorted(nx.all_topological_sorts(DG)) == [ 
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211 [2, 1, 4, 3, 5], 
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212 [2, 1, 4, 5, 3], 
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213 [2, 4, 1, 3, 5], 
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214 [2, 4, 1, 5, 3], 
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215 [2, 4, 5, 1, 3], 
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216 ] 
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217 
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218 def test_all_topological_sorts_3(self): 
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219 def unfeasible(): 
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220 DG = nx.DiGraph([(1, 2), (2, 3), (3, 4), (4, 2), (4, 5)]) 
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221 # convert to list to execute generator 
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222 list(nx.all_topological_sorts(DG)) 
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223 
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224 def not_implemented(): 
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225 G = nx.Graph([(1, 2), (2, 3)]) 
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226 # convert to list to execute generator 
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227 list(nx.all_topological_sorts(G)) 
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228 
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229 def not_implemted_2(): 
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230 G = nx.MultiGraph([(1, 2), (1, 2), (2, 3)]) 
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231 list(nx.all_topological_sorts(G)) 
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232 
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233 pytest.raises(nx.NetworkXUnfeasible, unfeasible) 
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234 pytest.raises(nx.NetworkXNotImplemented, not_implemented) 
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235 pytest.raises(nx.NetworkXNotImplemented, not_implemted_2) 
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236 
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237 def test_all_topological_sorts_4(self): 
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238 DG = nx.DiGraph() 
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239 for i in range(7): 
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240 DG.add_node(i) 
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241 assert sorted(map(list, permutations(DG.nodes))) == sorted( 
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242 nx.all_topological_sorts(DG) 
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243 ) 
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244 
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245 def test_all_topological_sorts_multigraph_1(self): 
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246 DG = nx.MultiDiGraph([(1, 2), (1, 2), (2, 3), (3, 4), (3, 5), (3, 5), (3, 5)]) 
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247 assert sorted(nx.all_topological_sorts(DG)) == sorted( 
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248 [[1, 2, 3, 4, 5], [1, 2, 3, 5, 4]] 
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249 ) 
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250 
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251 def test_all_topological_sorts_multigraph_2(self): 
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252 N = 9 
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253 edges = [] 
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254 for i in range(1, N): 
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255 edges.extend([(i, i + 1)] * i) 
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256 DG = nx.MultiDiGraph(edges) 
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257 assert list(nx.all_topological_sorts(DG)) == [list(range(1, N + 1))] 
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258 
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259 def test_ancestors(self): 
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260 G = nx.DiGraph() 
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261 ancestors = nx.algorithms.dag.ancestors 
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262 G.add_edges_from([(1, 2), (1, 3), (4, 2), (4, 3), (4, 5), (2, 6), (5, 6)]) 
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263 assert ancestors(G, 6) == {1, 2, 4, 5} 
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264 assert ancestors(G, 3) == {1, 4} 
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265 assert ancestors(G, 1) == set() 
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266 pytest.raises(nx.NetworkXError, ancestors, G, 8) 
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267 
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268 def test_descendants(self): 
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269 G = nx.DiGraph() 
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270 descendants = nx.algorithms.dag.descendants 
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271 G.add_edges_from([(1, 2), (1, 3), (4, 2), (4, 3), (4, 5), (2, 6), (5, 6)]) 
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272 assert descendants(G, 1) == {2, 3, 6} 
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273 assert descendants(G, 4) == {2, 3, 5, 6} 
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274 assert descendants(G, 3) == set() 
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275 pytest.raises(nx.NetworkXError, descendants, G, 8) 
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276 
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277 def test_transitive_closure(self): 
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278 G = nx.DiGraph([(1, 2), (2, 3), (3, 4)]) 
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279 solution = [(1, 2), (1, 3), (1, 4), (2, 3), (2, 4), (3, 4)] 
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280 assert_edges_equal(nx.transitive_closure(G).edges(), solution) 
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281 G = nx.DiGraph([(1, 2), (2, 3), (2, 4)]) 
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282 solution = [(1, 2), (1, 3), (1, 4), (2, 3), (2, 4)] 
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283 assert_edges_equal(nx.transitive_closure(G).edges(), solution) 
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284 G = nx.DiGraph([(1, 2), (2, 3), (3, 1)]) 
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285 solution = [(1, 2), (2, 1), (2, 3), (3, 2), (1, 3), (3, 1)] 
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286 soln = sorted(solution + [(n, n) for n in G]) 
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287 assert_edges_equal(sorted(nx.transitive_closure(G).edges()), soln) 
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288 G = nx.Graph([(1, 2), (2, 3), (3, 4)]) 
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289 pytest.raises(nx.NetworkXNotImplemented, nx.transitive_closure, G) 
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290 
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291 # test if edge data is copied 
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292 G = nx.DiGraph([(1, 2, {"a": 3}), (2, 3, {"b": 0}), (3, 4)]) 
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293 H = nx.transitive_closure(G) 
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294 for u, v in G.edges(): 
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295 assert G.get_edge_data(u, v) == H.get_edge_data(u, v) 
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296 
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297 k = 10 
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298 G = nx.DiGraph((i, i + 1, {"f": "b", "weight": i}) for i in range(k)) 
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299 H = nx.transitive_closure(G) 
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300 for u, v in G.edges(): 
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301 assert G.get_edge_data(u, v) == H.get_edge_data(u, v) 
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302 
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303 def test_reflexive_transitive_closure(self): 
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304 G = nx.DiGraph([(1, 2), (2, 3), (3, 4)]) 
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305 solution = [(1, 2), (1, 3), (1, 4), (2, 3), (2, 4), (3, 4)] 
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306 soln = sorted(solution + [(n, n) for n in G]) 
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307 assert_edges_equal(nx.transitive_closure(G).edges(), solution) 
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308 assert_edges_equal(nx.transitive_closure(G, False).edges(), solution) 
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309 assert_edges_equal(nx.transitive_closure(G, True).edges(), soln) 
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310 assert_edges_equal(nx.transitive_closure(G, None).edges(), solution) 
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311 
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312 G = nx.DiGraph([(1, 2), (2, 3), (2, 4)]) 
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313 solution = [(1, 2), (1, 3), (1, 4), (2, 3), (2, 4)] 
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314 soln = sorted(solution + [(n, n) for n in G]) 
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315 assert_edges_equal(nx.transitive_closure(G).edges(), solution) 
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316 assert_edges_equal(nx.transitive_closure(G, False).edges(), solution) 
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317 assert_edges_equal(nx.transitive_closure(G, True).edges(), soln) 
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318 assert_edges_equal(nx.transitive_closure(G, None).edges(), solution) 
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319 
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320 G = nx.DiGraph([(1, 2), (2, 3), (3, 1)]) 
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321 solution = sorted([(1, 2), (2, 1), (2, 3), (3, 2), (1, 3), (3, 1)]) 
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322 soln = sorted(solution + [(n, n) for n in G]) 
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323 assert_edges_equal(sorted(nx.transitive_closure(G).edges()), soln) 
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324 assert_edges_equal(sorted(nx.transitive_closure(G, False).edges()), soln) 
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325 assert_edges_equal(sorted(nx.transitive_closure(G, None).edges()), solution) 
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326 assert_edges_equal(sorted(nx.transitive_closure(G, True).edges()), soln) 
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327 
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328 def test_transitive_closure_dag(self): 
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329 G = nx.DiGraph([(1, 2), (2, 3), (3, 4)]) 
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330 transitive_closure = nx.algorithms.dag.transitive_closure_dag 
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331 solution = [(1, 2), (1, 3), (1, 4), (2, 3), (2, 4), (3, 4)] 
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332 assert_edges_equal(transitive_closure(G).edges(), solution) 
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333 G = nx.DiGraph([(1, 2), (2, 3), (2, 4)]) 
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334 solution = [(1, 2), (1, 3), (1, 4), (2, 3), (2, 4)] 
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335 assert_edges_equal(transitive_closure(G).edges(), solution) 
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336 G = nx.Graph([(1, 2), (2, 3), (3, 4)]) 
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337 pytest.raises(nx.NetworkXNotImplemented, transitive_closure, G) 
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338 
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339 # test if edge data is copied 
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340 G = nx.DiGraph([(1, 2, {"a": 3}), (2, 3, {"b": 0}), (3, 4)]) 
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341 H = transitive_closure(G) 
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342 for u, v in G.edges(): 
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343 assert G.get_edge_data(u, v) == H.get_edge_data(u, v) 
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344 
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345 k = 10 
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346 G = nx.DiGraph((i, i + 1, {"foo": "bar", "weight": i}) for i in range(k)) 
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347 H = transitive_closure(G) 
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348 for u, v in G.edges(): 
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349 assert G.get_edge_data(u, v) == H.get_edge_data(u, v) 
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350 
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351 def test_transitive_reduction(self): 
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352 G = nx.DiGraph([(1, 2), (1, 3), (1, 4), (2, 3), (2, 4), (3, 4)]) 
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353 transitive_reduction = nx.algorithms.dag.transitive_reduction 
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354 solution = [(1, 2), (2, 3), (3, 4)] 
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355 assert_edges_equal(transitive_reduction(G).edges(), solution) 
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356 G = nx.DiGraph([(1, 2), (1, 3), (1, 4), (2, 3), (2, 4)]) 
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357 transitive_reduction = nx.algorithms.dag.transitive_reduction 
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358 solution = [(1, 2), (2, 3), (2, 4)] 
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359 assert_edges_equal(transitive_reduction(G).edges(), solution) 
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360 G = nx.Graph([(1, 2), (2, 3), (3, 4)]) 
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361 pytest.raises(nx.NetworkXNotImplemented, transitive_reduction, G) 
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362 
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363 def _check_antichains(self, solution, result): 
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364 sol = [frozenset(a) for a in solution] 
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365 res = [frozenset(a) for a in result] 
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366 assert set(sol) == set(res) 
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367 
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368 def test_antichains(self): 
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369 antichains = nx.algorithms.dag.antichains 
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370 G = nx.DiGraph([(1, 2), (2, 3), (3, 4)]) 
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371 solution = [[], [4], [3], [2], [1]] 
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372 self._check_antichains(list(antichains(G)), solution) 
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373 G = nx.DiGraph([(1, 2), (2, 3), (2, 4), (3, 5), (5, 6), (5, 7)]) 
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374 solution = [ 
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375 [], 
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376 [4], 
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377 [7], 
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378 [7, 4], 
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379 [6], 
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380 [6, 4], 
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381 [6, 7], 
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382 [6, 7, 4], 
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383 [5], 
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384 [5, 4], 
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385 [3], 
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386 [3, 4], 
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387 [2], 
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388 [1], 
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389 ] 
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390 self._check_antichains(list(antichains(G)), solution) 
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391 G = nx.DiGraph([(1, 2), (1, 3), (3, 4), (3, 5), (5, 6)]) 
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392 solution = [ 
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393 [], 
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394 [6], 
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395 [5], 
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396 [4], 
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397 [4, 6], 
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398 [4, 5], 
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399 [3], 
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400 [2], 
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401 [2, 6], 
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402 [2, 5], 
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403 [2, 4], 
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404 [2, 4, 6], 
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405 [2, 4, 5], 
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406 [2, 3], 
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407 [1], 
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408 ] 
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409 self._check_antichains(list(antichains(G)), solution) 
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410 G = nx.DiGraph({0: [1, 2], 1: [4], 2: [3], 3: [4]}) 
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411 solution = [[], [4], [3], [2], [1], [1, 3], [1, 2], [0]] 
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412 self._check_antichains(list(antichains(G)), solution) 
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413 G = nx.DiGraph() 
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414 self._check_antichains(list(antichains(G)), [[]]) 
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415 G = nx.DiGraph() 
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416 G.add_nodes_from([0, 1, 2]) 
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417 solution = [[], [0], [1], [1, 0], [2], [2, 0], [2, 1], [2, 1, 0]] 
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418 self._check_antichains(list(antichains(G)), solution) 
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419 
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420 def f(x): 
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421 return list(antichains(x)) 
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422 
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423 G = nx.Graph([(1, 2), (2, 3), (3, 4)]) 
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424 pytest.raises(nx.NetworkXNotImplemented, f, G) 
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425 G = nx.DiGraph([(1, 2), (2, 3), (3, 1)]) 
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426 pytest.raises(nx.NetworkXUnfeasible, f, G) 
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427 
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428 def test_lexicographical_topological_sort(self): 
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429 G = nx.DiGraph([(1, 2), (2, 3), (1, 4), (1, 5), (2, 6)]) 
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430 assert list(nx.lexicographical_topological_sort(G)) == [1, 2, 3, 4, 5, 6] 
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431 assert list(nx.lexicographical_topological_sort(G, key=lambda x: x)) == [ 
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432 1, 
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433 2, 
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434 3, 
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435 4, 
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436 5, 
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437 6, 
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438 ] 
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439 assert list(nx.lexicographical_topological_sort(G, key=lambda x: x)) == [ 
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440 1, 
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441 5, 
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442 4, 
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443 2, 
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444 6, 
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445 3, 
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446 ] 
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447 
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448 def test_lexicographical_topological_sort2(self): 
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449 """ 
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450 Check the case of two or more nodes with same key value. 
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451 Want to avoid exception raised due to comparing nodes directly. 
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452 See Issue #3493 
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453 """ 
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454 
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455 class Test_Node: 
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456 def __init__(self, n): 
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457 self.label = n 
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458 self.priority = 1 
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459 
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460 def __repr__(self): 
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461 return f"Node({self.label})" 
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462 
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463 def sorting_key(node): 
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464 return node.priority 
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465 
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466 test_nodes = [Test_Node(n) for n in range(4)] 
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467 G = nx.DiGraph() 
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468 edges = [(0, 1), (0, 2), (0, 3), (2, 3)] 
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469 G.add_edges_from((test_nodes[a], test_nodes[b]) for a, b in edges) 
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470 
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471 sorting = list(nx.lexicographical_topological_sort(G, key=sorting_key)) 
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472 assert sorting == test_nodes 
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473 
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474 
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475 def test_is_aperiodic_cycle(): 
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476 G = nx.DiGraph() 
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477 nx.add_cycle(G, [1, 2, 3, 4]) 
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478 assert not nx.is_aperiodic(G) 
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479 
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480 
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481 def test_is_aperiodic_cycle2(): 
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482 G = nx.DiGraph() 
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483 nx.add_cycle(G, [1, 2, 3, 4]) 
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484 nx.add_cycle(G, [3, 4, 5, 6, 7]) 
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485 assert nx.is_aperiodic(G) 
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486 
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487 
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488 def test_is_aperiodic_cycle3(): 
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489 G = nx.DiGraph() 
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490 nx.add_cycle(G, [1, 2, 3, 4]) 
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491 nx.add_cycle(G, [3, 4, 5, 6]) 
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492 assert not nx.is_aperiodic(G) 
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493 
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494 
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495 def test_is_aperiodic_cycle4(): 
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496 G = nx.DiGraph() 
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497 nx.add_cycle(G, [1, 2, 3, 4]) 
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498 G.add_edge(1, 3) 
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499 assert nx.is_aperiodic(G) 
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500 
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501 
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502 def test_is_aperiodic_selfloop(): 
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503 G = nx.DiGraph() 
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504 nx.add_cycle(G, [1, 2, 3, 4]) 
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505 G.add_edge(1, 1) 
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506 assert nx.is_aperiodic(G) 
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507 
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508 
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509 def test_is_aperiodic_raise(): 
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510 G = nx.Graph() 
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511 pytest.raises(nx.NetworkXError, nx.is_aperiodic, G) 
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512 
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513 
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514 def test_is_aperiodic_bipartite(): 
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515 # Bipartite graph 
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516 G = nx.DiGraph(nx.davis_southern_women_graph()) 
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517 assert not nx.is_aperiodic(G) 
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518 
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519 
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520 def test_is_aperiodic_rary_tree(): 
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521 G = nx.full_rary_tree(3, 27, create_using=nx.DiGraph()) 
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522 assert not nx.is_aperiodic(G) 
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523 
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524 
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525 def test_is_aperiodic_disconnected(): 
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526 # disconnected graph 
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527 G = nx.DiGraph() 
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528 nx.add_cycle(G, [1, 2, 3, 4]) 
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529 nx.add_cycle(G, [5, 6, 7, 8]) 
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530 assert not nx.is_aperiodic(G) 
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531 G.add_edge(1, 3) 
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532 G.add_edge(5, 7) 
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533 assert nx.is_aperiodic(G) 
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534 
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535 
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536 def test_is_aperiodic_disconnected2(): 
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537 G = nx.DiGraph() 
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538 nx.add_cycle(G, [0, 1, 2]) 
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539 G.add_edge(3, 3) 
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540 assert not nx.is_aperiodic(G) 
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541 
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542 
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543 class TestDagToBranching: 
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544 """Unit tests for the :func:`networkx.dag_to_branching` function.""" 
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545 
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546 def test_single_root(self): 
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547 """Tests that a directed acyclic graph with a single degree 
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548 zero node produces an arborescence. 
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549 
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550 """ 
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551 G = nx.DiGraph([(0, 1), (0, 2), (1, 3), (2, 3)]) 
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552 B = nx.dag_to_branching(G) 
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553 expected = nx.DiGraph([(0, 1), (1, 3), (0, 2), (2, 4)]) 
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554 assert nx.is_arborescence(B) 
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555 assert nx.is_isomorphic(B, expected) 
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556 
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557 def test_multiple_roots(self): 
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558 """Tests that a directed acyclic graph with multiple degree zero 
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559 nodes creates an arborescence with multiple (weakly) connected 
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560 components. 
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561 
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562 """ 
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563 G = nx.DiGraph([(0, 1), (0, 2), (1, 3), (2, 3), (5, 2)]) 
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564 B = nx.dag_to_branching(G) 
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565 expected = nx.DiGraph([(0, 1), (1, 3), (0, 2), (2, 4), (5, 6), (6, 7)]) 
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566 assert nx.is_branching(B) 
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567 assert not nx.is_arborescence(B) 
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568 assert nx.is_isomorphic(B, expected) 
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569 
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570 # # Attributes are not copied by this function. If they were, this would 
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571 # # be a good test to uncomment. 
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572 # def test_copy_attributes(self): 
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573 # """Tests that node attributes are copied in the branching.""" 
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574 # G = nx.DiGraph([(0, 1), (0, 2), (1, 3), (2, 3)]) 
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575 # for v in G: 
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576 # G.node[v]['label'] = str(v) 
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577 # B = nx.dag_to_branching(G) 
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578 # # Determine the root node of the branching. 
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579 # root = next(v for v, d in B.in_degree() if d == 0) 
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580 # assert_equal(B.node[root]['label'], '0') 
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581 # children = B[root] 
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582 # # Get the left and right children, nodes 1 and 2, respectively. 
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583 # left, right = sorted(children, key=lambda v: B.node[v]['label']) 
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584 # assert_equal(B.node[left]['label'], '1') 
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585 # assert_equal(B.node[right]['label'], '2') 
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586 # # Get the left grandchild. 
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587 # children = B[left] 
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588 # assert_equal(len(children), 1) 
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589 # left_grandchild = arbitrary_element(children) 
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590 # assert_equal(B.node[left_grandchild]['label'], '3') 
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591 # # Get the right grandchild. 
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592 # children = B[right] 
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593 # assert_equal(len(children), 1) 
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594 # right_grandchild = arbitrary_element(children) 
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595 # assert_equal(B.node[right_grandchild]['label'], '3') 
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596 
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597 def test_already_arborescence(self): 
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598 """Tests that a directed acyclic graph that is already an 
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599 arborescence produces an isomorphic arborescence as output. 
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600 
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601 """ 
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602 A = nx.balanced_tree(2, 2, create_using=nx.DiGraph()) 
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603 B = nx.dag_to_branching(A) 
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604 assert nx.is_isomorphic(A, B) 
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605 
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606 def test_already_branching(self): 
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607 """Tests that a directed acyclic graph that is already a 
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608 branching produces an isomorphic branching as output. 
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609 
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610 """ 
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611 T1 = nx.balanced_tree(2, 2, create_using=nx.DiGraph()) 
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612 T2 = nx.balanced_tree(2, 2, create_using=nx.DiGraph()) 
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613 G = nx.disjoint_union(T1, T2) 
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614 B = nx.dag_to_branching(G) 
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615 assert nx.is_isomorphic(G, B) 
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616 
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617 def test_not_acyclic(self): 
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618 """Tests that a nonacyclic graph causes an exception.""" 
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619 with pytest.raises(nx.HasACycle): 
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620 G = nx.DiGraph(pairwise("abc", cyclic=True)) 
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621 nx.dag_to_branching(G) 
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622 
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623 def test_undirected(self): 
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624 with pytest.raises(nx.NetworkXNotImplemented): 
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625 nx.dag_to_branching(nx.Graph()) 
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626 
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627 def test_multigraph(self): 
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628 with pytest.raises(nx.NetworkXNotImplemented): 
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629 nx.dag_to_branching(nx.MultiGraph()) 
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630 
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631 def test_multidigraph(self): 
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632 with pytest.raises(nx.NetworkXNotImplemented): 
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633 nx.dag_to_branching(nx.MultiDiGraph()) 