Mercurial > repos > shellac > sam_consensus_v3
annotate env/lib/python3.9/site-packages/networkx/algorithms/bipartite/tests/test_centrality.py @ 0:4f3585e2f14b draft default tip
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author | shellac |
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date | Mon, 22 Mar 2021 18:12:50 +0000 |
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1 import networkx as nx |
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2 from networkx.algorithms import bipartite |
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3 from networkx.testing import almost_equal |
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4 |
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5 |
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6 class TestBipartiteCentrality: |
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7 @classmethod |
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8 def setup_class(cls): |
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9 cls.P4 = nx.path_graph(4) |
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10 cls.K3 = nx.complete_bipartite_graph(3, 3) |
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11 cls.C4 = nx.cycle_graph(4) |
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12 cls.davis = nx.davis_southern_women_graph() |
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13 cls.top_nodes = [ |
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14 n for n, d in cls.davis.nodes(data=True) if d["bipartite"] == 0 |
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15 ] |
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16 |
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17 def test_degree_centrality(self): |
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18 d = bipartite.degree_centrality(self.P4, [1, 3]) |
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19 answer = {0: 0.5, 1: 1.0, 2: 1.0, 3: 0.5} |
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20 assert d == answer |
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21 d = bipartite.degree_centrality(self.K3, [0, 1, 2]) |
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22 answer = {0: 1.0, 1: 1.0, 2: 1.0, 3: 1.0, 4: 1.0, 5: 1.0} |
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23 assert d == answer |
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24 d = bipartite.degree_centrality(self.C4, [0, 2]) |
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25 answer = {0: 1.0, 1: 1.0, 2: 1.0, 3: 1.0} |
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26 assert d == answer |
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27 |
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28 def test_betweenness_centrality(self): |
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29 c = bipartite.betweenness_centrality(self.P4, [1, 3]) |
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30 answer = {0: 0.0, 1: 1.0, 2: 1.0, 3: 0.0} |
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31 assert c == answer |
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32 c = bipartite.betweenness_centrality(self.K3, [0, 1, 2]) |
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33 answer = {0: 0.125, 1: 0.125, 2: 0.125, 3: 0.125, 4: 0.125, 5: 0.125} |
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34 assert c == answer |
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35 c = bipartite.betweenness_centrality(self.C4, [0, 2]) |
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36 answer = {0: 0.25, 1: 0.25, 2: 0.25, 3: 0.25} |
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37 assert c == answer |
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38 |
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39 def test_closeness_centrality(self): |
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40 c = bipartite.closeness_centrality(self.P4, [1, 3]) |
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41 answer = {0: 2.0 / 3, 1: 1.0, 2: 1.0, 3: 2.0 / 3} |
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42 assert c == answer |
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43 c = bipartite.closeness_centrality(self.K3, [0, 1, 2]) |
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44 answer = {0: 1.0, 1: 1.0, 2: 1.0, 3: 1.0, 4: 1.0, 5: 1.0} |
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45 assert c == answer |
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46 c = bipartite.closeness_centrality(self.C4, [0, 2]) |
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47 answer = {0: 1.0, 1: 1.0, 2: 1.0, 3: 1.0} |
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48 assert c == answer |
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49 G = nx.Graph() |
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50 G.add_node(0) |
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51 G.add_node(1) |
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52 c = bipartite.closeness_centrality(G, [0]) |
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53 assert c == {1: 0.0} |
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54 c = bipartite.closeness_centrality(G, [1]) |
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55 assert c == {1: 0.0} |
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56 |
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57 def test_davis_degree_centrality(self): |
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58 G = self.davis |
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59 deg = bipartite.degree_centrality(G, self.top_nodes) |
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60 answer = { |
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61 "E8": 0.78, |
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62 "E9": 0.67, |
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63 "E7": 0.56, |
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64 "Nora Fayette": 0.57, |
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65 "Evelyn Jefferson": 0.57, |
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66 "Theresa Anderson": 0.57, |
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67 "E6": 0.44, |
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68 "Sylvia Avondale": 0.50, |
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69 "Laura Mandeville": 0.50, |
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70 "Brenda Rogers": 0.50, |
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71 "Katherina Rogers": 0.43, |
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72 "E5": 0.44, |
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73 "Helen Lloyd": 0.36, |
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74 "E3": 0.33, |
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75 "Ruth DeSand": 0.29, |
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76 "Verne Sanderson": 0.29, |
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77 "E12": 0.33, |
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78 "Myra Liddel": 0.29, |
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79 "E11": 0.22, |
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80 "Eleanor Nye": 0.29, |
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81 "Frances Anderson": 0.29, |
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82 "Pearl Oglethorpe": 0.21, |
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83 "E4": 0.22, |
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84 "Charlotte McDowd": 0.29, |
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85 "E10": 0.28, |
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86 "Olivia Carleton": 0.14, |
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87 "Flora Price": 0.14, |
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88 "E2": 0.17, |
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89 "E1": 0.17, |
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90 "Dorothy Murchison": 0.14, |
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91 "E13": 0.17, |
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92 "E14": 0.17, |
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93 } |
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94 for node, value in answer.items(): |
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95 assert almost_equal(value, deg[node], places=2) |
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96 |
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97 def test_davis_betweenness_centrality(self): |
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98 G = self.davis |
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99 bet = bipartite.betweenness_centrality(G, self.top_nodes) |
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100 answer = { |
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101 "E8": 0.24, |
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102 "E9": 0.23, |
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103 "E7": 0.13, |
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104 "Nora Fayette": 0.11, |
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105 "Evelyn Jefferson": 0.10, |
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106 "Theresa Anderson": 0.09, |
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107 "E6": 0.07, |
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108 "Sylvia Avondale": 0.07, |
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109 "Laura Mandeville": 0.05, |
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110 "Brenda Rogers": 0.05, |
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111 "Katherina Rogers": 0.05, |
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112 "E5": 0.04, |
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113 "Helen Lloyd": 0.04, |
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114 "E3": 0.02, |
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115 "Ruth DeSand": 0.02, |
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116 "Verne Sanderson": 0.02, |
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117 "E12": 0.02, |
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118 "Myra Liddel": 0.02, |
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119 "E11": 0.02, |
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120 "Eleanor Nye": 0.01, |
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121 "Frances Anderson": 0.01, |
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122 "Pearl Oglethorpe": 0.01, |
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123 "E4": 0.01, |
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124 "Charlotte McDowd": 0.01, |
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125 "E10": 0.01, |
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126 "Olivia Carleton": 0.01, |
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127 "Flora Price": 0.01, |
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128 "E2": 0.00, |
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129 "E1": 0.00, |
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130 "Dorothy Murchison": 0.00, |
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131 "E13": 0.00, |
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132 "E14": 0.00, |
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133 } |
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134 for node, value in answer.items(): |
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135 assert almost_equal(value, bet[node], places=2) |
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136 |
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137 def test_davis_closeness_centrality(self): |
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138 G = self.davis |
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139 clos = bipartite.closeness_centrality(G, self.top_nodes) |
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140 answer = { |
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141 "E8": 0.85, |
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142 "E9": 0.79, |
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143 "E7": 0.73, |
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144 "Nora Fayette": 0.80, |
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145 "Evelyn Jefferson": 0.80, |
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146 "Theresa Anderson": 0.80, |
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147 "E6": 0.69, |
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148 "Sylvia Avondale": 0.77, |
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149 "Laura Mandeville": 0.73, |
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150 "Brenda Rogers": 0.73, |
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151 "Katherina Rogers": 0.73, |
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152 "E5": 0.59, |
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153 "Helen Lloyd": 0.73, |
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154 "E3": 0.56, |
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155 "Ruth DeSand": 0.71, |
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156 "Verne Sanderson": 0.71, |
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157 "E12": 0.56, |
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158 "Myra Liddel": 0.69, |
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159 "E11": 0.54, |
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160 "Eleanor Nye": 0.67, |
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161 "Frances Anderson": 0.67, |
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162 "Pearl Oglethorpe": 0.67, |
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163 "E4": 0.54, |
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164 "Charlotte McDowd": 0.60, |
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165 "E10": 0.55, |
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166 "Olivia Carleton": 0.59, |
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167 "Flora Price": 0.59, |
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168 "E2": 0.52, |
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169 "E1": 0.52, |
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170 "Dorothy Murchison": 0.65, |
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171 "E13": 0.52, |
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172 "E14": 0.52, |
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173 } |
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174 for node, value in answer.items(): |
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175 assert almost_equal(value, clos[node], places=2) |