Mercurial > repos > shellac > sam_consensus_v3
annotate env/lib/python3.9/site-packages/networkx/algorithms/operators/tests/test_product.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 import pytest |
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2 import networkx as nx |
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3 from networkx.testing import assert_edges_equal |
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4 |
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5 |
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6 def test_tensor_product_raises(): |
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7 with pytest.raises(nx.NetworkXError): |
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8 P = nx.tensor_product(nx.DiGraph(), nx.Graph()) |
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9 |
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10 |
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11 def test_tensor_product_null(): |
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12 null = nx.null_graph() |
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13 empty10 = nx.empty_graph(10) |
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14 K3 = nx.complete_graph(3) |
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15 K10 = nx.complete_graph(10) |
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16 P3 = nx.path_graph(3) |
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17 P10 = nx.path_graph(10) |
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18 # null graph |
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19 G = nx.tensor_product(null, null) |
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20 assert nx.is_isomorphic(G, null) |
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21 # null_graph X anything = null_graph and v.v. |
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22 G = nx.tensor_product(null, empty10) |
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23 assert nx.is_isomorphic(G, null) |
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24 G = nx.tensor_product(null, K3) |
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25 assert nx.is_isomorphic(G, null) |
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26 G = nx.tensor_product(null, K10) |
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27 assert nx.is_isomorphic(G, null) |
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28 G = nx.tensor_product(null, P3) |
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29 assert nx.is_isomorphic(G, null) |
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30 G = nx.tensor_product(null, P10) |
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31 assert nx.is_isomorphic(G, null) |
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32 G = nx.tensor_product(empty10, null) |
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33 assert nx.is_isomorphic(G, null) |
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34 G = nx.tensor_product(K3, null) |
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35 assert nx.is_isomorphic(G, null) |
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36 G = nx.tensor_product(K10, null) |
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37 assert nx.is_isomorphic(G, null) |
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38 G = nx.tensor_product(P3, null) |
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39 assert nx.is_isomorphic(G, null) |
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40 G = nx.tensor_product(P10, null) |
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41 assert nx.is_isomorphic(G, null) |
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42 |
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43 |
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44 def test_tensor_product_size(): |
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45 P5 = nx.path_graph(5) |
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46 K3 = nx.complete_graph(3) |
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47 K5 = nx.complete_graph(5) |
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48 |
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49 G = nx.tensor_product(P5, K3) |
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50 assert nx.number_of_nodes(G) == 5 * 3 |
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51 G = nx.tensor_product(K3, K5) |
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52 assert nx.number_of_nodes(G) == 3 * 5 |
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53 |
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54 |
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55 def test_tensor_product_combinations(): |
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56 # basic smoke test, more realistic tests would be useful |
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57 P5 = nx.path_graph(5) |
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58 K3 = nx.complete_graph(3) |
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59 G = nx.tensor_product(P5, K3) |
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60 assert nx.number_of_nodes(G) == 5 * 3 |
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61 G = nx.tensor_product(P5, nx.MultiGraph(K3)) |
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62 assert nx.number_of_nodes(G) == 5 * 3 |
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63 G = nx.tensor_product(nx.MultiGraph(P5), K3) |
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64 assert nx.number_of_nodes(G) == 5 * 3 |
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65 G = nx.tensor_product(nx.MultiGraph(P5), nx.MultiGraph(K3)) |
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66 assert nx.number_of_nodes(G) == 5 * 3 |
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67 |
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68 G = nx.tensor_product(nx.DiGraph(P5), nx.DiGraph(K3)) |
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69 assert nx.number_of_nodes(G) == 5 * 3 |
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70 |
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71 |
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72 def test_tensor_product_classic_result(): |
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73 K2 = nx.complete_graph(2) |
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74 G = nx.petersen_graph() |
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75 G = nx.tensor_product(G, K2) |
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76 assert nx.is_isomorphic(G, nx.desargues_graph()) |
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77 |
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78 G = nx.cycle_graph(5) |
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79 G = nx.tensor_product(G, K2) |
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80 assert nx.is_isomorphic(G, nx.cycle_graph(10)) |
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81 |
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82 G = nx.tetrahedral_graph() |
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83 G = nx.tensor_product(G, K2) |
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84 assert nx.is_isomorphic(G, nx.cubical_graph()) |
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85 |
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86 |
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87 def test_tensor_product_random(): |
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88 G = nx.erdos_renyi_graph(10, 2 / 10.0) |
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89 H = nx.erdos_renyi_graph(10, 2 / 10.0) |
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90 GH = nx.tensor_product(G, H) |
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91 |
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92 for (u_G, u_H) in GH.nodes(): |
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93 for (v_G, v_H) in GH.nodes(): |
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94 if H.has_edge(u_H, v_H) and G.has_edge(u_G, v_G): |
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95 assert GH.has_edge((u_G, u_H), (v_G, v_H)) |
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96 else: |
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97 assert not GH.has_edge((u_G, u_H), (v_G, v_H)) |
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98 |
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99 |
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100 def test_cartesian_product_multigraph(): |
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101 G = nx.MultiGraph() |
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102 G.add_edge(1, 2, key=0) |
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103 G.add_edge(1, 2, key=1) |
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104 H = nx.MultiGraph() |
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105 H.add_edge(3, 4, key=0) |
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106 H.add_edge(3, 4, key=1) |
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107 GH = nx.cartesian_product(G, H) |
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108 assert set(GH) == {(1, 3), (2, 3), (2, 4), (1, 4)} |
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109 assert {(frozenset([u, v]), k) for u, v, k in GH.edges(keys=True)} == { |
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110 (frozenset([u, v]), k) |
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111 for u, v, k in [ |
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112 ((1, 3), (2, 3), 0), |
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113 ((1, 3), (2, 3), 1), |
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114 ((1, 3), (1, 4), 0), |
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115 ((1, 3), (1, 4), 1), |
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116 ((2, 3), (2, 4), 0), |
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117 ((2, 3), (2, 4), 1), |
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118 ((2, 4), (1, 4), 0), |
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119 ((2, 4), (1, 4), 1), |
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120 ] |
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121 } |
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122 |
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123 |
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124 def test_cartesian_product_raises(): |
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125 with pytest.raises(nx.NetworkXError): |
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126 P = nx.cartesian_product(nx.DiGraph(), nx.Graph()) |
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127 |
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128 |
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129 def test_cartesian_product_null(): |
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130 null = nx.null_graph() |
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131 empty10 = nx.empty_graph(10) |
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132 K3 = nx.complete_graph(3) |
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133 K10 = nx.complete_graph(10) |
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134 P3 = nx.path_graph(3) |
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135 P10 = nx.path_graph(10) |
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136 # null graph |
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137 G = nx.cartesian_product(null, null) |
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138 assert nx.is_isomorphic(G, null) |
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139 # null_graph X anything = null_graph and v.v. |
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140 G = nx.cartesian_product(null, empty10) |
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141 assert nx.is_isomorphic(G, null) |
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142 G = nx.cartesian_product(null, K3) |
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143 assert nx.is_isomorphic(G, null) |
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144 G = nx.cartesian_product(null, K10) |
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145 assert nx.is_isomorphic(G, null) |
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146 G = nx.cartesian_product(null, P3) |
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147 assert nx.is_isomorphic(G, null) |
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148 G = nx.cartesian_product(null, P10) |
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149 assert nx.is_isomorphic(G, null) |
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150 G = nx.cartesian_product(empty10, null) |
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151 assert nx.is_isomorphic(G, null) |
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152 G = nx.cartesian_product(K3, null) |
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153 assert nx.is_isomorphic(G, null) |
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154 G = nx.cartesian_product(K10, null) |
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155 assert nx.is_isomorphic(G, null) |
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156 G = nx.cartesian_product(P3, null) |
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157 assert nx.is_isomorphic(G, null) |
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158 G = nx.cartesian_product(P10, null) |
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159 assert nx.is_isomorphic(G, null) |
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160 |
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161 |
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162 def test_cartesian_product_size(): |
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163 # order(GXH)=order(G)*order(H) |
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164 K5 = nx.complete_graph(5) |
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165 P5 = nx.path_graph(5) |
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166 K3 = nx.complete_graph(3) |
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167 G = nx.cartesian_product(P5, K3) |
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168 assert nx.number_of_nodes(G) == 5 * 3 |
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169 assert nx.number_of_edges(G) == nx.number_of_edges(P5) * nx.number_of_nodes( |
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170 K3 |
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171 ) + nx.number_of_edges(K3) * nx.number_of_nodes(P5) |
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172 G = nx.cartesian_product(K3, K5) |
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173 assert nx.number_of_nodes(G) == 3 * 5 |
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174 assert nx.number_of_edges(G) == nx.number_of_edges(K5) * nx.number_of_nodes( |
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175 K3 |
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176 ) + nx.number_of_edges(K3) * nx.number_of_nodes(K5) |
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177 |
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178 |
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179 def test_cartesian_product_classic(): |
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180 # test some classic product graphs |
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181 P2 = nx.path_graph(2) |
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182 P3 = nx.path_graph(3) |
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183 # cube = 2-path X 2-path |
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184 G = nx.cartesian_product(P2, P2) |
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185 G = nx.cartesian_product(P2, G) |
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186 assert nx.is_isomorphic(G, nx.cubical_graph()) |
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187 |
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188 # 3x3 grid |
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189 G = nx.cartesian_product(P3, P3) |
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190 assert nx.is_isomorphic(G, nx.grid_2d_graph(3, 3)) |
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191 |
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192 |
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193 def test_cartesian_product_random(): |
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194 G = nx.erdos_renyi_graph(10, 2 / 10.0) |
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195 H = nx.erdos_renyi_graph(10, 2 / 10.0) |
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196 GH = nx.cartesian_product(G, H) |
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197 |
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198 for (u_G, u_H) in GH.nodes(): |
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199 for (v_G, v_H) in GH.nodes(): |
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200 if (u_G == v_G and H.has_edge(u_H, v_H)) or ( |
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201 u_H == v_H and G.has_edge(u_G, v_G) |
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202 ): |
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203 assert GH.has_edge((u_G, u_H), (v_G, v_H)) |
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204 else: |
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205 assert not GH.has_edge((u_G, u_H), (v_G, v_H)) |
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206 |
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207 |
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208 def test_lexicographic_product_raises(): |
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209 with pytest.raises(nx.NetworkXError): |
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210 P = nx.lexicographic_product(nx.DiGraph(), nx.Graph()) |
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211 |
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212 |
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213 def test_lexicographic_product_null(): |
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214 null = nx.null_graph() |
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215 empty10 = nx.empty_graph(10) |
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216 K3 = nx.complete_graph(3) |
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217 K10 = nx.complete_graph(10) |
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218 P3 = nx.path_graph(3) |
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219 P10 = nx.path_graph(10) |
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220 # null graph |
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221 G = nx.lexicographic_product(null, null) |
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222 assert nx.is_isomorphic(G, null) |
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223 # null_graph X anything = null_graph and v.v. |
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224 G = nx.lexicographic_product(null, empty10) |
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225 assert nx.is_isomorphic(G, null) |
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226 G = nx.lexicographic_product(null, K3) |
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227 assert nx.is_isomorphic(G, null) |
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228 G = nx.lexicographic_product(null, K10) |
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229 assert nx.is_isomorphic(G, null) |
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230 G = nx.lexicographic_product(null, P3) |
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231 assert nx.is_isomorphic(G, null) |
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232 G = nx.lexicographic_product(null, P10) |
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233 assert nx.is_isomorphic(G, null) |
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234 G = nx.lexicographic_product(empty10, null) |
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235 assert nx.is_isomorphic(G, null) |
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236 G = nx.lexicographic_product(K3, null) |
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237 assert nx.is_isomorphic(G, null) |
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238 G = nx.lexicographic_product(K10, null) |
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239 assert nx.is_isomorphic(G, null) |
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240 G = nx.lexicographic_product(P3, null) |
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241 assert nx.is_isomorphic(G, null) |
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242 G = nx.lexicographic_product(P10, null) |
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243 assert nx.is_isomorphic(G, null) |
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244 |
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245 |
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246 def test_lexicographic_product_size(): |
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247 K5 = nx.complete_graph(5) |
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248 P5 = nx.path_graph(5) |
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249 K3 = nx.complete_graph(3) |
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250 G = nx.lexicographic_product(P5, K3) |
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251 assert nx.number_of_nodes(G) == 5 * 3 |
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252 G = nx.lexicographic_product(K3, K5) |
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253 assert nx.number_of_nodes(G) == 3 * 5 |
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254 |
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255 |
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256 def test_lexicographic_product_combinations(): |
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257 P5 = nx.path_graph(5) |
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258 K3 = nx.complete_graph(3) |
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259 G = nx.lexicographic_product(P5, K3) |
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260 assert nx.number_of_nodes(G) == 5 * 3 |
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261 G = nx.lexicographic_product(nx.MultiGraph(P5), K3) |
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262 assert nx.number_of_nodes(G) == 5 * 3 |
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263 G = nx.lexicographic_product(P5, nx.MultiGraph(K3)) |
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264 assert nx.number_of_nodes(G) == 5 * 3 |
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265 G = nx.lexicographic_product(nx.MultiGraph(P5), nx.MultiGraph(K3)) |
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266 assert nx.number_of_nodes(G) == 5 * 3 |
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267 |
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268 # No classic easily found classic results for lexicographic product |
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269 |
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270 |
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271 def test_lexicographic_product_random(): |
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272 G = nx.erdos_renyi_graph(10, 2 / 10.0) |
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273 H = nx.erdos_renyi_graph(10, 2 / 10.0) |
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274 GH = nx.lexicographic_product(G, H) |
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275 |
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276 for (u_G, u_H) in GH.nodes(): |
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277 for (v_G, v_H) in GH.nodes(): |
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278 if G.has_edge(u_G, v_G) or (u_G == v_G and H.has_edge(u_H, v_H)): |
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279 assert GH.has_edge((u_G, u_H), (v_G, v_H)) |
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280 else: |
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281 assert not GH.has_edge((u_G, u_H), (v_G, v_H)) |
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282 |
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283 |
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284 def test_strong_product_raises(): |
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285 with pytest.raises(nx.NetworkXError): |
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286 P = nx.strong_product(nx.DiGraph(), nx.Graph()) |
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287 |
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288 |
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289 def test_strong_product_null(): |
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290 null = nx.null_graph() |
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291 empty10 = nx.empty_graph(10) |
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292 K3 = nx.complete_graph(3) |
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293 K10 = nx.complete_graph(10) |
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294 P3 = nx.path_graph(3) |
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295 P10 = nx.path_graph(10) |
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296 # null graph |
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297 G = nx.strong_product(null, null) |
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298 assert nx.is_isomorphic(G, null) |
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299 # null_graph X anything = null_graph and v.v. |
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300 G = nx.strong_product(null, empty10) |
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301 assert nx.is_isomorphic(G, null) |
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302 G = nx.strong_product(null, K3) |
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303 assert nx.is_isomorphic(G, null) |
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304 G = nx.strong_product(null, K10) |
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305 assert nx.is_isomorphic(G, null) |
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306 G = nx.strong_product(null, P3) |
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307 assert nx.is_isomorphic(G, null) |
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308 G = nx.strong_product(null, P10) |
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309 assert nx.is_isomorphic(G, null) |
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310 G = nx.strong_product(empty10, null) |
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311 assert nx.is_isomorphic(G, null) |
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312 G = nx.strong_product(K3, null) |
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313 assert nx.is_isomorphic(G, null) |
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314 G = nx.strong_product(K10, null) |
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315 assert nx.is_isomorphic(G, null) |
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316 G = nx.strong_product(P3, null) |
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317 assert nx.is_isomorphic(G, null) |
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318 G = nx.strong_product(P10, null) |
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319 assert nx.is_isomorphic(G, null) |
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320 |
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321 |
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322 def test_strong_product_size(): |
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323 K5 = nx.complete_graph(5) |
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324 P5 = nx.path_graph(5) |
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325 K3 = nx.complete_graph(3) |
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326 G = nx.strong_product(P5, K3) |
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327 assert nx.number_of_nodes(G) == 5 * 3 |
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328 G = nx.strong_product(K3, K5) |
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329 assert nx.number_of_nodes(G) == 3 * 5 |
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330 |
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331 |
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332 def test_strong_product_combinations(): |
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333 P5 = nx.path_graph(5) |
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334 K3 = nx.complete_graph(3) |
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335 G = nx.strong_product(P5, K3) |
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336 assert nx.number_of_nodes(G) == 5 * 3 |
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337 G = nx.strong_product(nx.MultiGraph(P5), K3) |
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338 assert nx.number_of_nodes(G) == 5 * 3 |
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339 G = nx.strong_product(P5, nx.MultiGraph(K3)) |
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340 assert nx.number_of_nodes(G) == 5 * 3 |
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341 G = nx.strong_product(nx.MultiGraph(P5), nx.MultiGraph(K3)) |
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342 assert nx.number_of_nodes(G) == 5 * 3 |
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343 |
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344 # No classic easily found classic results for strong product |
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345 |
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346 |
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347 def test_strong_product_random(): |
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348 G = nx.erdos_renyi_graph(10, 2 / 10.0) |
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349 H = nx.erdos_renyi_graph(10, 2 / 10.0) |
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350 GH = nx.strong_product(G, H) |
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351 |
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352 for (u_G, u_H) in GH.nodes(): |
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353 for (v_G, v_H) in GH.nodes(): |
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354 if ( |
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355 (u_G == v_G and H.has_edge(u_H, v_H)) |
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356 or (u_H == v_H and G.has_edge(u_G, v_G)) |
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357 or (G.has_edge(u_G, v_G) and H.has_edge(u_H, v_H)) |
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358 ): |
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359 assert GH.has_edge((u_G, u_H), (v_G, v_H)) |
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360 else: |
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361 assert not GH.has_edge((u_G, u_H), (v_G, v_H)) |
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362 |
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363 |
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364 def test_graph_power_raises(): |
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365 with pytest.raises(nx.NetworkXNotImplemented): |
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366 nx.power(nx.MultiDiGraph(), 2) |
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367 |
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368 |
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369 def test_graph_power(): |
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370 # wikipedia example for graph power |
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371 G = nx.cycle_graph(7) |
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372 G.add_edge(6, 7) |
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373 G.add_edge(7, 8) |
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374 G.add_edge(8, 9) |
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375 G.add_edge(9, 2) |
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376 H = nx.power(G, 2) |
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377 |
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378 assert_edges_equal( |
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379 list(H.edges()), |
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380 [ |
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381 (0, 1), |
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382 (0, 2), |
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383 (0, 5), |
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384 (0, 6), |
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385 (0, 7), |
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386 (1, 9), |
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387 (1, 2), |
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388 (1, 3), |
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389 (1, 6), |
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390 (2, 3), |
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391 (2, 4), |
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392 (2, 8), |
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393 (2, 9), |
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394 (3, 4), |
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395 (3, 5), |
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396 (3, 9), |
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397 (4, 5), |
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398 (4, 6), |
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399 (5, 6), |
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400 (5, 7), |
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401 (6, 7), |
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402 (6, 8), |
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403 (7, 8), |
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404 (7, 9), |
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405 (8, 9), |
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406 ], |
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407 ) |
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408 |
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409 |
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410 def test_graph_power_negative(): |
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411 with pytest.raises(ValueError): |
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412 nx.power(nx.Graph(), -1) |
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413 |
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414 |
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415 def test_rooted_product_raises(): |
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416 with pytest.raises(nx.NetworkXError): |
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417 nx.rooted_product(nx.Graph(), nx.path_graph(2), 10) |
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418 |
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419 |
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420 def test_rooted_product(): |
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421 G = nx.cycle_graph(5) |
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422 H = nx.Graph() |
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423 H.add_edges_from([("a", "b"), ("b", "c"), ("b", "d")]) |
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424 R = nx.rooted_product(G, H, "a") |
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425 assert len(R) == len(G) * len(H) |
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426 assert R.size() == G.size() + len(G) * H.size() |