Mercurial > repos > shellac > sam_consensus_v3
annotate env/lib/python3.9/site-packages/networkx/algorithms/approximation/tests/test_connectivity.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 pytest |
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2 |
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3 import networkx as nx |
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4 from networkx.algorithms import approximation as approx |
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5 |
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6 |
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7 def test_global_node_connectivity(): |
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8 # Figure 1 chapter on Connectivity |
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9 G = nx.Graph() |
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10 G.add_edges_from( |
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11 [ |
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31 ] |
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32 ) |
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33 assert 2 == approx.local_node_connectivity(G, 1, 11) |
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34 assert 2 == approx.node_connectivity(G) |
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35 assert 2 == approx.node_connectivity(G, 1, 11) |
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36 |
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37 |
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38 def test_white_harary1(): |
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39 # Figure 1b white and harary (2001) |
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40 # A graph with high adhesion (edge connectivity) and low cohesion |
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41 # (node connectivity) |
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42 G = nx.disjoint_union(nx.complete_graph(4), nx.complete_graph(4)) |
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43 G.remove_node(7) |
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44 for i in range(4, 7): |
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45 G.add_edge(0, i) |
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46 G = nx.disjoint_union(G, nx.complete_graph(4)) |
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47 G.remove_node(G.order() - 1) |
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48 for i in range(7, 10): |
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49 G.add_edge(0, i) |
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50 assert 1 == approx.node_connectivity(G) |
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51 |
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52 |
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53 def test_complete_graphs(): |
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54 for n in range(5, 25, 5): |
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55 G = nx.complete_graph(n) |
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56 assert n - 1 == approx.node_connectivity(G) |
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57 assert n - 1 == approx.node_connectivity(G, 0, 3) |
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58 |
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59 |
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60 def test_empty_graphs(): |
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61 for k in range(5, 25, 5): |
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62 G = nx.empty_graph(k) |
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63 assert 0 == approx.node_connectivity(G) |
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64 assert 0 == approx.node_connectivity(G, 0, 3) |
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65 |
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66 |
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67 def test_petersen(): |
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68 G = nx.petersen_graph() |
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69 assert 3 == approx.node_connectivity(G) |
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70 assert 3 == approx.node_connectivity(G, 0, 5) |
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71 |
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72 |
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73 # Approximation fails with tutte graph |
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74 # def test_tutte(): |
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75 # G = nx.tutte_graph() |
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76 # assert_equal(3, approx.node_connectivity(G)) |
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77 |
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78 |
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79 def test_dodecahedral(): |
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80 G = nx.dodecahedral_graph() |
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81 assert 3 == approx.node_connectivity(G) |
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82 assert 3 == approx.node_connectivity(G, 0, 5) |
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83 |
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84 |
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85 def test_octahedral(): |
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86 G = nx.octahedral_graph() |
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87 assert 4 == approx.node_connectivity(G) |
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88 assert 4 == approx.node_connectivity(G, 0, 5) |
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89 |
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90 |
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91 # Approximation can fail with icosahedral graph depending |
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92 # on iteration order. |
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93 # def test_icosahedral(): |
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94 # G=nx.icosahedral_graph() |
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95 # assert_equal(5, approx.node_connectivity(G)) |
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96 # assert_equal(5, approx.node_connectivity(G, 0, 5)) |
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97 |
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98 |
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99 def test_only_source(): |
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100 G = nx.complete_graph(5) |
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101 pytest.raises(nx.NetworkXError, approx.node_connectivity, G, s=0) |
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102 |
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103 |
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104 def test_only_target(): |
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105 G = nx.complete_graph(5) |
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106 pytest.raises(nx.NetworkXError, approx.node_connectivity, G, t=0) |
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107 |
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108 |
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109 def test_missing_source(): |
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110 G = nx.path_graph(4) |
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111 pytest.raises(nx.NetworkXError, approx.node_connectivity, G, 10, 1) |
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112 |
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113 |
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114 def test_missing_target(): |
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115 G = nx.path_graph(4) |
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116 pytest.raises(nx.NetworkXError, approx.node_connectivity, G, 1, 10) |
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117 |
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118 |
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119 def test_source_equals_target(): |
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120 G = nx.complete_graph(5) |
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121 pytest.raises(nx.NetworkXError, approx.local_node_connectivity, G, 0, 0) |
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122 |
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123 |
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124 def test_directed_node_connectivity(): |
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125 G = nx.cycle_graph(10, create_using=nx.DiGraph()) # only one direction |
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126 D = nx.cycle_graph(10).to_directed() # 2 reciprocal edges |
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127 assert 1 == approx.node_connectivity(G) |
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128 assert 1 == approx.node_connectivity(G, 1, 4) |
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129 assert 2 == approx.node_connectivity(D) |
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130 assert 2 == approx.node_connectivity(D, 1, 4) |
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131 |
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132 |
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133 class TestAllPairsNodeConnectivityApprox: |
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134 @classmethod |
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135 def setup_class(cls): |
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136 cls.path = nx.path_graph(7) |
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137 cls.directed_path = nx.path_graph(7, create_using=nx.DiGraph()) |
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138 cls.cycle = nx.cycle_graph(7) |
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139 cls.directed_cycle = nx.cycle_graph(7, create_using=nx.DiGraph()) |
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140 cls.gnp = nx.gnp_random_graph(30, 0.1) |
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141 cls.directed_gnp = nx.gnp_random_graph(30, 0.1, directed=True) |
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142 cls.K20 = nx.complete_graph(20) |
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143 cls.K10 = nx.complete_graph(10) |
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144 cls.K5 = nx.complete_graph(5) |
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145 cls.G_list = [ |
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146 cls.path, |
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147 cls.directed_path, |
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148 cls.cycle, |
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149 cls.directed_cycle, |
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150 cls.gnp, |
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151 cls.directed_gnp, |
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152 cls.K10, |
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153 cls.K5, |
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154 cls.K20, |
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155 ] |
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156 |
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157 def test_cycles(self): |
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158 K_undir = approx.all_pairs_node_connectivity(self.cycle) |
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159 for source in K_undir: |
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160 for target, k in K_undir[source].items(): |
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161 assert k == 2 |
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162 K_dir = approx.all_pairs_node_connectivity(self.directed_cycle) |
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163 for source in K_dir: |
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164 for target, k in K_dir[source].items(): |
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165 assert k == 1 |
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166 |
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167 def test_complete(self): |
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168 for G in [self.K10, self.K5, self.K20]: |
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169 K = approx.all_pairs_node_connectivity(G) |
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170 for source in K: |
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171 for target, k in K[source].items(): |
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172 assert k == len(G) - 1 |
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173 |
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174 def test_paths(self): |
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175 K_undir = approx.all_pairs_node_connectivity(self.path) |
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176 for source in K_undir: |
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177 for target, k in K_undir[source].items(): |
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178 assert k == 1 |
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179 K_dir = approx.all_pairs_node_connectivity(self.directed_path) |
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180 for source in K_dir: |
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181 for target, k in K_dir[source].items(): |
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182 if source < target: |
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183 assert k == 1 |
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184 else: |
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185 assert k == 0 |
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186 |
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187 def test_cutoff(self): |
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188 for G in [self.K10, self.K5, self.K20]: |
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189 for mp in [2, 3, 4]: |
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190 paths = approx.all_pairs_node_connectivity(G, cutoff=mp) |
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191 for source in paths: |
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192 for target, K in paths[source].items(): |
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193 assert K == mp |
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194 |
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195 def test_all_pairs_connectivity_nbunch(self): |
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196 G = nx.complete_graph(5) |
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197 nbunch = [0, 2, 3] |
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198 C = approx.all_pairs_node_connectivity(G, nbunch=nbunch) |
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199 assert len(C) == len(nbunch) |