Mercurial > repos > shellac > sam_consensus_v3
annotate env/lib/python3.9/site-packages/networkx/algorithms/tests/test_distance_measures.py @ 0:4f3585e2f14b draft default tip
"planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
author | shellac |
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date | Mon, 22 Mar 2021 18:12:50 +0000 |
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1 from random import Random |
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2 |
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3 import pytest |
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4 |
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5 |
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6 import networkx as nx |
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7 from networkx import convert_node_labels_to_integers as cnlti |
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8 |
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9 |
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10 class TestDistance: |
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11 def setup_method(self): |
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12 G = cnlti(nx.grid_2d_graph(4, 4), first_label=1, ordering="sorted") |
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13 self.G = G |
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14 |
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15 def test_eccentricity(self): |
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16 assert nx.eccentricity(self.G, 1) == 6 |
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17 e = nx.eccentricity(self.G) |
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18 assert e[1] == 6 |
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19 |
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20 sp = dict(nx.shortest_path_length(self.G)) |
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21 e = nx.eccentricity(self.G, sp=sp) |
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22 assert e[1] == 6 |
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23 |
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24 e = nx.eccentricity(self.G, v=1) |
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25 assert e == 6 |
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26 |
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27 # This behavior changed in version 1.8 (ticket #739) |
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28 e = nx.eccentricity(self.G, v=[1, 1]) |
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29 assert e[1] == 6 |
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30 e = nx.eccentricity(self.G, v=[1, 2]) |
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31 assert e[1] == 6 |
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32 |
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33 # test against graph with one node |
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34 G = nx.path_graph(1) |
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35 e = nx.eccentricity(G) |
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36 assert e[0] == 0 |
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37 e = nx.eccentricity(G, v=0) |
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38 assert e == 0 |
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39 pytest.raises(nx.NetworkXError, nx.eccentricity, G, 1) |
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40 |
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41 # test against empty graph |
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42 G = nx.empty_graph() |
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43 e = nx.eccentricity(G) |
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44 assert e == {} |
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45 |
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46 def test_diameter(self): |
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47 assert nx.diameter(self.G) == 6 |
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48 |
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49 def test_radius(self): |
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50 assert nx.radius(self.G) == 4 |
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51 |
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52 def test_periphery(self): |
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53 assert set(nx.periphery(self.G)) == {1, 4, 13, 16} |
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54 |
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55 def test_center(self): |
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56 assert set(nx.center(self.G)) == {6, 7, 10, 11} |
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57 |
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58 def test_bound_diameter(self): |
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59 assert nx.diameter(self.G, usebounds=True) == 6 |
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60 |
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61 def test_bound_radius(self): |
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62 assert nx.radius(self.G, usebounds=True) == 4 |
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63 |
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64 def test_bound_periphery(self): |
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65 result = {1, 4, 13, 16} |
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66 assert set(nx.periphery(self.G, usebounds=True)) == result |
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67 |
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68 def test_bound_center(self): |
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69 result = {6, 7, 10, 11} |
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70 assert set(nx.center(self.G, usebounds=True)) == result |
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71 |
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72 def test_radius_exception(self): |
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73 G = nx.Graph() |
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74 G.add_edge(1, 2) |
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75 G.add_edge(3, 4) |
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76 pytest.raises(nx.NetworkXError, nx.diameter, G) |
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77 |
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78 def test_eccentricity_infinite(self): |
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79 with pytest.raises(nx.NetworkXError): |
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80 G = nx.Graph([(1, 2), (3, 4)]) |
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81 e = nx.eccentricity(G) |
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82 |
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83 def test_eccentricity_undirected_not_connected(self): |
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84 with pytest.raises(nx.NetworkXError): |
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85 G = nx.Graph([(1, 2), (3, 4)]) |
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86 e = nx.eccentricity(G, sp=1) |
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87 |
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88 def test_eccentricity_directed_weakly_connected(self): |
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89 with pytest.raises(nx.NetworkXError): |
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90 DG = nx.DiGraph([(1, 2), (1, 3)]) |
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91 nx.eccentricity(DG) |
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92 |
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93 |
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94 class TestResistanceDistance: |
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95 @classmethod |
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96 def setup_class(cls): |
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97 global np |
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98 global sp_sparse |
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99 np = pytest.importorskip("numpy") |
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100 scipy = pytest.importorskip("scipy") |
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101 sp_sparse = pytest.importorskip("scipy.sparse") |
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102 |
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103 def setup_method(self): |
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104 G = nx.Graph() |
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105 G.add_edge(1, 2, weight=2) |
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106 G.add_edge(2, 3, weight=4) |
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107 G.add_edge(3, 4, weight=1) |
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108 G.add_edge(1, 4, weight=3) |
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109 self.G = G |
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110 |
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111 def test_laplacian_submatrix(self): |
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112 from networkx.algorithms.distance_measures import _laplacian_submatrix |
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113 |
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114 M = sp_sparse.csr_matrix([[1, 2, 3], [4, 5, 6], [7, 8, 9]], dtype=np.float32) |
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115 N = sp_sparse.csr_matrix([[5, 6], [8, 9]], dtype=np.float32) |
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116 Mn, Mn_nodelist = _laplacian_submatrix(1, M, [1, 2, 3]) |
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117 assert Mn_nodelist == [2, 3] |
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118 assert np.allclose(Mn.toarray(), N.toarray()) |
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119 |
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120 def test_laplacian_submatrix_square(self): |
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121 with pytest.raises(nx.NetworkXError): |
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122 from networkx.algorithms.distance_measures import _laplacian_submatrix |
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123 |
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124 M = sp_sparse.csr_matrix([[1, 2], [4, 5], [7, 8]], dtype=np.float32) |
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125 _laplacian_submatrix(1, M, [1, 2, 3]) |
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126 |
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127 def test_laplacian_submatrix_matrix_node_dim(self): |
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128 with pytest.raises(nx.NetworkXError): |
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129 from networkx.algorithms.distance_measures import _laplacian_submatrix |
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130 |
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131 M = sp_sparse.csr_matrix( |
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132 [[1, 2, 3], [4, 5, 6], [7, 8, 9]], dtype=np.float32 |
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133 ) |
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134 _laplacian_submatrix(1, M, [1, 2, 3, 4]) |
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135 |
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136 def test_resistance_distance(self): |
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137 rd = nx.resistance_distance(self.G, 1, 3, "weight", True) |
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138 test_data = 1 / (1 / (2 + 4) + 1 / (1 + 3)) |
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139 assert round(rd, 5) == round(test_data, 5) |
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140 |
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141 def test_resistance_distance_noinv(self): |
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142 rd = nx.resistance_distance(self.G, 1, 3, "weight", False) |
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143 test_data = 1 / (1 / (1 / 2 + 1 / 4) + 1 / (1 / 1 + 1 / 3)) |
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144 assert round(rd, 5) == round(test_data, 5) |
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145 |
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146 def test_resistance_distance_no_weight(self): |
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147 rd = nx.resistance_distance(self.G, 1, 3) |
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148 assert round(rd, 5) == 1 |
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149 |
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150 def test_resistance_distance_neg_weight(self): |
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151 self.G[2][3]["weight"] = -4 |
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152 rd = nx.resistance_distance(self.G, 1, 3, "weight", True) |
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153 test_data = 1 / (1 / (2 + -4) + 1 / (1 + 3)) |
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154 assert round(rd, 5) == round(test_data, 5) |
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155 |
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156 def test_multigraph(self): |
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157 G = nx.MultiGraph() |
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158 G.add_edge(1, 2, weight=2) |
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159 G.add_edge(2, 3, weight=4) |
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160 G.add_edge(3, 4, weight=1) |
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161 G.add_edge(1, 4, weight=3) |
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162 rd = nx.resistance_distance(G, 1, 3, "weight", True) |
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163 assert np.isclose(rd, 1 / (1 / (2 + 4) + 1 / (1 + 3))) |
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164 |
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165 def test_resistance_distance_div0(self): |
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166 with pytest.raises(ZeroDivisionError): |
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167 self.G[1][2]["weight"] = 0 |
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168 nx.resistance_distance(self.G, 1, 3, "weight") |
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169 |
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170 def test_resistance_distance_not_connected(self): |
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171 with pytest.raises(nx.NetworkXError): |
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172 self.G.add_node(5) |
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173 nx.resistance_distance(self.G, 1, 5) |
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174 |
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175 def test_resistance_distance_same_node(self): |
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176 with pytest.raises(nx.NetworkXError): |
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177 nx.resistance_distance(self.G, 1, 1) |
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178 |
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179 def test_resistance_distance_nodeA_not_in_graph(self): |
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180 with pytest.raises(nx.NetworkXError): |
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181 nx.resistance_distance(self.G, 9, 1) |
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182 |
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183 def test_resistance_distance_nodeB_not_in_graph(self): |
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184 with pytest.raises(nx.NetworkXError): |
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185 nx.resistance_distance(self.G, 1, 9) |
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186 |
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187 |
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188 class TestBarycenter: |
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189 """Test :func:`networkx.algorithms.distance_measures.barycenter`.""" |
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190 |
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191 def barycenter_as_subgraph(self, g, **kwargs): |
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192 """Return the subgraph induced on the barycenter of g""" |
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193 b = nx.barycenter(g, **kwargs) |
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194 assert isinstance(b, list) |
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195 assert set(b) <= set(g) |
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196 return g.subgraph(b) |
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197 |
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198 def test_must_be_connected(self): |
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199 pytest.raises(nx.NetworkXNoPath, nx.barycenter, nx.empty_graph(5)) |
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200 |
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201 def test_sp_kwarg(self): |
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202 # Complete graph K_5. Normally it works... |
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203 K_5 = nx.complete_graph(5) |
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204 sp = dict(nx.shortest_path_length(K_5)) |
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205 assert nx.barycenter(K_5, sp=sp) == list(K_5) |
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206 |
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207 # ...but not with the weight argument |
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208 for u, v, data in K_5.edges.data(): |
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209 data["weight"] = 1 |
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210 pytest.raises(ValueError, nx.barycenter, K_5, sp=sp, weight="weight") |
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211 |
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212 # ...and a corrupted sp can make it seem like K_5 is disconnected |
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213 del sp[0][1] |
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214 pytest.raises(nx.NetworkXNoPath, nx.barycenter, K_5, sp=sp) |
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215 |
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216 def test_trees(self): |
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217 """The barycenter of a tree is a single vertex or an edge. |
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218 |
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219 See [West01]_, p. 78. |
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220 """ |
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221 prng = Random(0xDEADBEEF) |
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222 for i in range(50): |
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223 RT = nx.random_tree(prng.randint(1, 75), prng) |
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224 b = self.barycenter_as_subgraph(RT) |
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225 if len(b) == 2: |
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226 assert b.size() == 1 |
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227 else: |
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228 assert len(b) == 1 |
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229 assert b.size() == 0 |
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230 |
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231 def test_this_one_specific_tree(self): |
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232 """Test the tree pictured at the bottom of [West01]_, p. 78.""" |
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233 g = nx.Graph( |
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234 { |
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235 "a": ["b"], |
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236 "b": ["a", "x"], |
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237 "x": ["b", "y"], |
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238 "y": ["x", "z"], |
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239 "z": ["y", 0, 1, 2, 3, 4], |
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240 0: ["z"], |
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241 1: ["z"], |
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242 2: ["z"], |
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243 3: ["z"], |
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244 4: ["z"], |
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245 } |
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246 ) |
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247 b = self.barycenter_as_subgraph(g, attr="barycentricity") |
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248 assert list(b) == ["z"] |
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249 assert not b.edges |
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250 expected_barycentricity = { |
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251 0: 23, |
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252 1: 23, |
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253 2: 23, |
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254 3: 23, |
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255 4: 23, |
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256 "a": 35, |
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257 "b": 27, |
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258 "x": 21, |
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259 "y": 17, |
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260 "z": 15, |
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261 } |
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262 for node, barycentricity in expected_barycentricity.items(): |
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263 assert g.nodes[node]["barycentricity"] == barycentricity |
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264 |
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265 # Doubling weights should do nothing but double the barycentricities |
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266 for edge in g.edges: |
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267 g.edges[edge]["weight"] = 2 |
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268 b = self.barycenter_as_subgraph(g, weight="weight", attr="barycentricity2") |
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269 assert list(b) == ["z"] |
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270 assert not b.edges |
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271 for node, barycentricity in expected_barycentricity.items(): |
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272 assert g.nodes[node]["barycentricity2"] == barycentricity * 2 |