Mercurial > repos > guerler > springsuite
annotate planemo/lib/python3.7/site-packages/networkx/algorithms/planarity.py @ 1:56ad4e20f292 draft
"planemo upload commit 6eee67778febed82ddd413c3ca40b3183a3898f1"
author | guerler |
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date | Fri, 31 Jul 2020 00:32:28 -0400 |
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1 from collections import defaultdict |
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2 import networkx as nx |
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3 |
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4 __all__ = ["check_planarity", "PlanarEmbedding"] |
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5 |
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6 |
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7 def check_planarity(G, counterexample=False): |
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8 """Check if a graph is planar and return a counterexample or an embedding. |
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9 |
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10 A graph is planar iff it can be drawn in a plane without |
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11 any edge intersections. |
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12 |
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13 Parameters |
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14 ---------- |
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15 G : NetworkX graph |
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16 counterexample : bool |
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17 A Kuratowski subgraph (to proof non planarity) is only returned if set |
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18 to true. |
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19 |
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20 Returns |
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21 ------- |
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22 (is_planar, certificate) : (bool, NetworkX graph) tuple |
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23 is_planar is true if the graph is planar. |
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24 If the graph is planar `certificate` is a PlanarEmbedding |
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25 otherwise it is a Kuratowski subgraph. |
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26 |
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27 Notes |
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28 ----- |
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29 A (combinatorial) embedding consists of cyclic orderings of the incident |
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30 edges at each vertex. Given such an embedding there are multiple approaches |
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31 discussed in literature to drawing the graph (subject to various |
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32 constraints, e.g. integer coordinates), see e.g. [2]. |
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33 |
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34 The planarity check algorithm and extraction of the combinatorial embedding |
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35 is based on the Left-Right Planarity Test [1]. |
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36 |
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37 A counterexample is only generated if the corresponding parameter is set, |
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38 because the complexity of the counterexample generation is higher. |
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39 |
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40 References |
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41 ---------- |
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42 .. [1] Ulrik Brandes: |
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43 The Left-Right Planarity Test |
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44 2009 |
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45 http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.217.9208 |
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46 .. [2] Takao Nishizeki, Md Saidur Rahman: |
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47 Planar graph drawing |
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48 Lecture Notes Series on Computing: Volume 12 |
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49 2004 |
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50 """ |
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51 |
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52 planarity_state = LRPlanarity(G) |
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53 embedding = planarity_state.lr_planarity() |
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54 if embedding is None: |
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55 # graph is not planar |
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56 if counterexample: |
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57 return False, get_counterexample(G) |
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58 else: |
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59 return False, None |
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60 else: |
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61 # graph is planar |
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62 return True, embedding |
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63 |
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64 |
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65 def check_planarity_recursive(G, counterexample=False): |
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66 """Recursive version of :meth:`check_planarity`.""" |
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67 planarity_state = LRPlanarity(G) |
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68 embedding = planarity_state.lr_planarity_recursive() |
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69 if embedding is None: |
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70 # graph is not planar |
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71 if counterexample: |
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72 return False, get_counterexample_recursive(G) |
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73 else: |
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74 return False, None |
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75 else: |
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76 # graph is planar |
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77 return True, embedding |
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78 |
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79 |
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80 def get_counterexample(G): |
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81 """Obtains a Kuratowski subgraph. |
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82 |
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83 Raises nx.NetworkXException if G is planar. |
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84 |
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85 The function removes edges such that the graph is still not planar. |
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86 At some point the removal of any edge would make the graph planar. |
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87 This subgraph must be a Kuratowski subgraph. |
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88 |
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89 Parameters |
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90 ---------- |
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91 G : NetworkX graph |
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92 |
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93 Returns |
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94 ------- |
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95 subgraph : NetworkX graph |
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96 A Kuratowski subgraph that proves that G is not planar. |
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97 |
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98 """ |
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99 # copy graph |
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100 G = nx.Graph(G) |
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101 |
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102 if check_planarity(G)[0]: |
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103 raise nx.NetworkXException("G is planar - no counter example.") |
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104 |
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105 # find Kuratowski subgraph |
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106 subgraph = nx.Graph() |
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107 for u in G: |
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108 nbrs = list(G[u]) |
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109 for v in nbrs: |
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110 G.remove_edge(u, v) |
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111 if check_planarity(G)[0]: |
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112 G.add_edge(u, v) |
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113 subgraph.add_edge(u, v) |
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114 |
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115 return subgraph |
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116 |
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117 |
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118 def get_counterexample_recursive(G): |
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119 """Recursive version of :meth:`get_counterexample`. |
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120 """ |
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121 |
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122 # copy graph |
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123 G = nx.Graph(G) |
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124 |
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125 if check_planarity_recursive(G)[0]: |
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126 raise nx.NetworkXException("G is planar - no counter example.") |
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127 |
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128 # find Kuratowski subgraph |
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129 subgraph = nx.Graph() |
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130 for u in G: |
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131 nbrs = list(G[u]) |
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132 for v in nbrs: |
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133 G.remove_edge(u, v) |
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134 if check_planarity_recursive(G)[0]: |
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135 G.add_edge(u, v) |
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136 subgraph.add_edge(u, v) |
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137 |
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138 return subgraph |
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139 |
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140 |
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141 class Interval(object): |
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142 """Represents a set of return edges. |
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143 |
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144 All return edges in an interval induce a same constraint on the contained |
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145 edges, which means that all edges must either have a left orientation or |
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146 all edges must have a right orientation. |
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147 """ |
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148 |
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149 def __init__(self, low=None, high=None): |
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150 self.low = low |
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151 self.high = high |
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152 |
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153 def empty(self): |
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154 """Check if the interval is empty""" |
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155 return self.low is None and self.high is None |
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156 |
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157 def copy(self): |
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158 """Returns a copy of this interval""" |
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159 return Interval(self.low, self.high) |
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160 |
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161 def conflicting(self, b, planarity_state): |
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162 """Returns True if interval I conflicts with edge b""" |
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163 return (not self.empty() and |
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164 planarity_state.lowpt[self.high] > planarity_state.lowpt[b]) |
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165 |
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166 |
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167 class ConflictPair(object): |
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168 """Represents a different constraint between two intervals. |
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169 |
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170 The edges in the left interval must have a different orientation than |
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171 the one in the right interval. |
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172 """ |
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173 |
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174 def __init__(self, left=Interval(), right=Interval()): |
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175 self.left = left |
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176 self.right = right |
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177 |
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178 def swap(self): |
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179 """Swap left and right intervals""" |
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180 temp = self.left |
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181 self.left = self.right |
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182 self.right = temp |
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183 |
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184 def lowest(self, planarity_state): |
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185 """Returns the lowest lowpoint of a conflict pair""" |
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186 if self.left.empty(): |
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187 return planarity_state.lowpt[self.right.low] |
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188 if self.right.empty(): |
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189 return planarity_state.lowpt[self.left.low] |
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190 return min(planarity_state.lowpt[self.left.low], |
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191 planarity_state.lowpt[self.right.low]) |
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192 |
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193 |
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194 def top_of_stack(l): |
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195 """Returns the element on top of the stack.""" |
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196 if not l: |
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197 return None |
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198 return l[-1] |
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199 |
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200 |
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201 class LRPlanarity(object): |
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202 """A class to maintain the state during planarity check.""" |
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203 __slots__ = [ |
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204 'G', 'roots', 'height', 'lowpt', 'lowpt2', 'nesting_depth', |
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205 'parent_edge', 'DG', 'adjs', 'ordered_adjs', 'ref', 'side', 'S', |
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206 'stack_bottom', 'lowpt_edge', 'left_ref', 'right_ref', 'embedding' |
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207 ] |
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208 |
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209 def __init__(self, G): |
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210 # copy G without adding self-loops |
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211 self.G = nx.Graph() |
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212 self.G.add_nodes_from(G.nodes) |
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213 for e in G.edges: |
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214 if e[0] != e[1]: |
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215 self.G.add_edge(e[0], e[1]) |
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216 |
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217 self.roots = [] |
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218 |
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219 # distance from tree root |
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220 self.height = defaultdict(lambda: None) |
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221 |
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222 self.lowpt = {} # height of lowest return point of an edge |
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223 self.lowpt2 = {} # height of second lowest return point |
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224 self.nesting_depth = {} # for nesting order |
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225 |
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226 # None -> missing edge |
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227 self.parent_edge = defaultdict(lambda: None) |
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228 |
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229 # oriented DFS graph |
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230 self.DG = nx.DiGraph() |
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231 self.DG.add_nodes_from(G.nodes) |
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232 |
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233 self.adjs = {} |
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234 self.ordered_adjs = {} |
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235 |
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236 self.ref = defaultdict(lambda: None) |
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237 self.side = defaultdict(lambda: 1) |
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238 |
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239 # stack of conflict pairs |
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240 self.S = [] |
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241 self.stack_bottom = {} |
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242 self.lowpt_edge = {} |
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243 |
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244 self.left_ref = {} |
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245 self.right_ref = {} |
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246 |
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247 self.embedding = PlanarEmbedding() |
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248 |
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249 def lr_planarity(self): |
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250 """Execute the LR planarity test. |
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251 |
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252 Returns |
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253 ------- |
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254 embedding : dict |
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255 If the graph is planar an embedding is returned. Otherwise None. |
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256 """ |
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257 if self.G.order() > 2 and self.G.size() > 3 * self.G.order() - 6: |
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258 # graph is not planar |
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259 return None |
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260 |
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261 # make adjacency lists for dfs |
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262 for v in self.G: |
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263 self.adjs[v] = list(self.G[v]) |
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264 |
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265 # orientation of the graph by depth first search traversal |
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266 for v in self.G: |
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267 if self.height[v] is None: |
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268 self.height[v] = 0 |
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269 self.roots.append(v) |
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270 self.dfs_orientation(v) |
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271 |
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272 # Free no longer used variables |
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273 self.G = None |
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274 self.lowpt2 = None |
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275 self.adjs = None |
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276 |
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277 # testing |
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278 for v in self.DG: # sort the adjacency lists by nesting depth |
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279 # note: this sorting leads to non linear time |
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280 self.ordered_adjs[v] = sorted( |
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281 self.DG[v], key=lambda x: self.nesting_depth[(v, x)]) |
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282 for v in self.roots: |
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283 if not self.dfs_testing(v): |
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284 return None |
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285 |
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286 # Free no longer used variables |
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287 self.height = None |
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288 self.lowpt = None |
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289 self.S = None |
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290 self.stack_bottom = None |
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291 self.lowpt_edge = None |
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292 |
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293 for e in self.DG.edges: |
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294 self.nesting_depth[e] = self.sign(e) * self.nesting_depth[e] |
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295 |
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296 self.embedding.add_nodes_from(self.DG.nodes) |
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297 for v in self.DG: |
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298 # sort the adjacency lists again |
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299 self.ordered_adjs[v] = sorted( |
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300 self.DG[v], key=lambda x: self.nesting_depth[(v, x)]) |
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301 # initialize the embedding |
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302 previous_node = None |
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303 for w in self.ordered_adjs[v]: |
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304 self.embedding.add_half_edge_cw(v, w, previous_node) |
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305 previous_node = w |
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306 |
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307 # Free no longer used variables |
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308 self.DG = None |
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309 self.nesting_depth = None |
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310 self.ref = None |
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311 |
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312 # compute the complete embedding |
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313 for v in self.roots: |
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314 self.dfs_embedding(v) |
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315 |
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316 # Free no longer used variables |
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317 self.roots = None |
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318 self.parent_edge = None |
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319 self.ordered_adjs = None |
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320 self.left_ref = None |
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321 self.right_ref = None |
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322 self.side = None |
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323 |
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324 return self.embedding |
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325 |
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326 def lr_planarity_recursive(self): |
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327 """Recursive version of :meth:`lr_planarity`.""" |
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328 if self.G.order() > 2 and self.G.size() > 3 * self.G.order() - 6: |
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329 # graph is not planar |
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330 return None |
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331 |
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332 # orientation of the graph by depth first search traversal |
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333 for v in self.G: |
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334 if self.height[v] is None: |
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335 self.height[v] = 0 |
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336 self.roots.append(v) |
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337 self.dfs_orientation_recursive(v) |
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338 |
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339 # Free no longer used variable |
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340 self.G = None |
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341 |
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342 # testing |
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343 for v in self.DG: # sort the adjacency lists by nesting depth |
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344 # note: this sorting leads to non linear time |
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345 self.ordered_adjs[v] = sorted( |
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346 self.DG[v], key=lambda x: self.nesting_depth[(v, x)]) |
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347 for v in self.roots: |
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348 if not self.dfs_testing_recursive(v): |
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349 return None |
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350 |
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351 for e in self.DG.edges: |
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352 self.nesting_depth[e] = (self.sign_recursive(e) * |
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353 self.nesting_depth[e]) |
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354 |
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355 self.embedding.add_nodes_from(self.DG.nodes) |
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356 for v in self.DG: |
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357 # sort the adjacency lists again |
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358 self.ordered_adjs[v] = sorted( |
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359 self.DG[v], key=lambda x: self.nesting_depth[(v, x)]) |
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360 # initialize the embedding |
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361 previous_node = None |
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362 for w in self.ordered_adjs[v]: |
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363 self.embedding.add_half_edge_cw(v, w, previous_node) |
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364 previous_node = w |
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365 |
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366 # compute the complete embedding |
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367 for v in self.roots: |
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368 self.dfs_embedding_recursive(v) |
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369 |
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370 return self.embedding |
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371 |
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372 def dfs_orientation(self, v): |
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373 """Orient the graph by DFS, compute lowpoints and nesting order. |
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374 """ |
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375 # the recursion stack |
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376 dfs_stack = [v] |
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377 # index of next edge to handle in adjacency list of each node |
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378 ind = defaultdict(lambda: 0) |
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379 # boolean to indicate whether to skip the initial work for an edge |
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380 skip_init = defaultdict(lambda: False) |
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381 |
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382 while dfs_stack: |
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383 v = dfs_stack.pop() |
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384 e = self.parent_edge[v] |
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385 |
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386 for w in self.adjs[v][ind[v]:]: |
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387 vw = (v, w) |
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388 |
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389 if not skip_init[vw]: |
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390 if (v, w) in self.DG.edges or (w, v) in self.DG.edges: |
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391 ind[v] += 1 |
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392 continue # the edge was already oriented |
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393 |
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394 self.DG.add_edge(v, w) # orient the edge |
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395 |
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396 self.lowpt[vw] = self.height[v] |
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397 self.lowpt2[vw] = self.height[v] |
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398 if self.height[w] is None: # (v, w) is a tree edge |
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399 self.parent_edge[w] = vw |
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400 self.height[w] = self.height[v] + 1 |
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401 |
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402 dfs_stack.append(v) # revisit v after finishing w |
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403 dfs_stack.append(w) # visit w next |
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404 skip_init[vw] = True # don't redo this block |
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405 break # handle next node in dfs_stack (i.e. w) |
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406 else: # (v, w) is a back edge |
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407 self.lowpt[vw] = self.height[w] |
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408 |
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409 # determine nesting graph |
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410 self.nesting_depth[vw] = 2 * self.lowpt[vw] |
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411 if self.lowpt2[vw] < self.height[v]: # chordal |
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412 self.nesting_depth[vw] += 1 |
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413 |
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414 # update lowpoints of parent edge e |
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415 if e is not None: |
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416 if self.lowpt[vw] < self.lowpt[e]: |
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417 self.lowpt2[e] = min(self.lowpt[e], self.lowpt2[vw]) |
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418 self.lowpt[e] = self.lowpt[vw] |
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419 elif self.lowpt[vw] > self.lowpt[e]: |
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420 self.lowpt2[e] = min(self.lowpt2[e], self.lowpt[vw]) |
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421 else: |
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422 self.lowpt2[e] = min(self.lowpt2[e], self.lowpt2[vw]) |
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423 |
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424 ind[v] += 1 |
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425 |
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426 def dfs_orientation_recursive(self, v): |
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427 """Recursive version of :meth:`dfs_orientation`.""" |
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428 e = self.parent_edge[v] |
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429 for w in self.G[v]: |
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430 if (v, w) in self.DG.edges or (w, v) in self.DG.edges: |
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431 continue # the edge was already oriented |
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432 vw = (v, w) |
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433 self.DG.add_edge(v, w) # orient the edge |
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434 |
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435 self.lowpt[vw] = self.height[v] |
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436 self.lowpt2[vw] = self.height[v] |
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437 if self.height[w] is None: # (v, w) is a tree edge |
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438 self.parent_edge[w] = vw |
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439 self.height[w] = self.height[v] + 1 |
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440 self.dfs_orientation_recursive(w) |
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441 else: # (v, w) is a back edge |
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442 self.lowpt[vw] = self.height[w] |
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443 |
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444 # determine nesting graph |
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445 self.nesting_depth[vw] = 2 * self.lowpt[vw] |
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446 if self.lowpt2[vw] < self.height[v]: # chordal |
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447 self.nesting_depth[vw] += 1 |
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448 |
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449 # update lowpoints of parent edge e |
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450 if e is not None: |
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451 if self.lowpt[vw] < self.lowpt[e]: |
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452 self.lowpt2[e] = min(self.lowpt[e], self.lowpt2[vw]) |
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453 self.lowpt[e] = self.lowpt[vw] |
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454 elif self.lowpt[vw] > self.lowpt[e]: |
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455 self.lowpt2[e] = min(self.lowpt2[e], self.lowpt[vw]) |
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456 else: |
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457 self.lowpt2[e] = min(self.lowpt2[e], self.lowpt2[vw]) |
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458 |
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459 def dfs_testing(self, v): |
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460 """Test for LR partition.""" |
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461 # the recursion stack |
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462 dfs_stack = [v] |
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463 # index of next edge to handle in adjacency list of each node |
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464 ind = defaultdict(lambda: 0) |
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465 # boolean to indicate whether to skip the initial work for an edge |
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466 skip_init = defaultdict(lambda: False) |
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467 |
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468 while dfs_stack: |
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469 v = dfs_stack.pop() |
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470 e = self.parent_edge[v] |
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471 # to indicate whether to skip the final block after the for loop |
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472 skip_final = False |
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473 |
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474 for w in self.ordered_adjs[v][ind[v]:]: |
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475 ei = (v, w) |
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476 |
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477 if not skip_init[ei]: |
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478 self.stack_bottom[ei] = top_of_stack(self.S) |
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479 |
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480 if ei == self.parent_edge[w]: # tree edge |
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481 dfs_stack.append(v) # revisit v after finishing w |
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482 dfs_stack.append(w) # visit w next |
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483 skip_init[ei] = True # don't redo this block |
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484 skip_final = True # skip final work after breaking |
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485 break # handle next node in dfs_stack (i.e. w) |
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486 else: # back edge |
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487 self.lowpt_edge[ei] = ei |
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488 self.S.append(ConflictPair(right=Interval(ei, ei))) |
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489 |
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490 # integrate new return edges |
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491 if self.lowpt[ei] < self.height[v]: |
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492 if w == self.ordered_adjs[v][0]: # e_i has return edge |
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493 self.lowpt_edge[e] = self.lowpt_edge[ei] |
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494 else: # add constraints of e_i |
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495 if not self.add_constraints(ei, e): |
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496 # graph is not planar |
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497 return False |
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498 |
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499 ind[v] += 1 |
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500 |
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501 if not skip_final: |
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502 # remove back edges returning to parent |
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503 if e is not None: # v isn't root |
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504 self.remove_back_edges(e) |
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505 |
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506 return True |
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507 |
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508 def dfs_testing_recursive(self, v): |
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509 """Recursive version of :meth:`dfs_testing`.""" |
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510 e = self.parent_edge[v] |
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511 for w in self.ordered_adjs[v]: |
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512 ei = (v, w) |
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513 self.stack_bottom[ei] = top_of_stack(self.S) |
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514 if ei == self.parent_edge[w]: # tree edge |
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515 if not self.dfs_testing_recursive(w): |
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516 return False |
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517 else: # back edge |
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518 self.lowpt_edge[ei] = ei |
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519 self.S.append(ConflictPair(right=Interval(ei, ei))) |
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520 |
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521 # integrate new return edges |
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522 if self.lowpt[ei] < self.height[v]: |
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523 if w == self.ordered_adjs[v][0]: # e_i has return edge |
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524 self.lowpt_edge[e] = self.lowpt_edge[ei] |
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525 else: # add constraints of e_i |
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526 if not self.add_constraints(ei, e): |
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527 # graph is not planar |
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528 return False |
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529 |
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530 # remove back edges returning to parent |
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531 if e is not None: # v isn't root |
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532 self.remove_back_edges(e) |
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533 return True |
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534 |
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535 def add_constraints(self, ei, e): |
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536 P = ConflictPair() |
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537 # merge return edges of e_i into P.right |
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538 while True: |
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539 Q = self.S.pop() |
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540 if not Q.left.empty(): |
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541 Q.swap() |
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542 if not Q.left.empty(): # not planar |
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543 return False |
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544 if self.lowpt[Q.right.low] > self.lowpt[e]: |
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545 # merge intervals |
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546 if P.right.empty(): # topmost interval |
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547 P.right = Q.right.copy() |
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548 else: |
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549 self.ref[P.right.low] = Q.right.high |
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550 P.right.low = Q.right.low |
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551 else: # align |
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552 self.ref[Q.right.low] = self.lowpt_edge[e] |
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553 if top_of_stack(self.S) == self.stack_bottom[ei]: |
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554 break |
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555 # merge conflicting return edges of e_1,...,e_i-1 into P.L |
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556 while (top_of_stack(self.S).left.conflicting(ei, self) or |
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557 top_of_stack(self.S).right.conflicting(ei, self)): |
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558 Q = self.S.pop() |
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559 if Q.right.conflicting(ei, self): |
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560 Q.swap() |
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561 if Q.right.conflicting(ei, self): # not planar |
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562 return False |
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563 # merge interval below lowpt(e_i) into P.R |
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564 self.ref[P.right.low] = Q.right.high |
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565 if Q.right.low is not None: |
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566 P.right.low = Q.right.low |
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567 |
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568 if P.left.empty(): # topmost interval |
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569 P.left = Q.left.copy() |
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570 else: |
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571 self.ref[P.left.low] = Q.left.high |
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572 P.left.low = Q.left.low |
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573 |
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574 if not (P.left.empty() and P.right.empty()): |
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575 self.S.append(P) |
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576 return True |
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577 |
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578 def remove_back_edges(self, e): |
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579 u = e[0] |
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580 # trim back edges ending at parent u |
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581 # drop entire conflict pairs |
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582 while self.S and top_of_stack(self.S).lowest(self) == self.height[u]: |
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583 P = self.S.pop() |
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584 if P.left.low is not None: |
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585 self.side[P.left.low] = -1 |
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586 |
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587 if self.S: # one more conflict pair to consider |
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588 P = self.S.pop() |
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589 # trim left interval |
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590 while P.left.high is not None and P.left.high[1] == u: |
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591 P.left.high = self.ref[P.left.high] |
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592 if P.left.high is None and P.left.low is not None: |
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593 # just emptied |
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594 self.ref[P.left.low] = P.right.low |
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595 self.side[P.left.low] = -1 |
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596 P.left.low = None |
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597 # trim right interval |
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598 while P.right.high is not None and P.right.high[1] == u: |
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599 P.right.high = self.ref[P.right.high] |
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600 if P.right.high is None and P.right.low is not None: |
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601 # just emptied |
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602 self.ref[P.right.low] = P.left.low |
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603 self.side[P.right.low] = -1 |
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604 P.right.low = None |
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605 self.S.append(P) |
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606 |
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607 # side of e is side of a highest return edge |
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608 if self.lowpt[e] < self.height[u]: # e has return edge |
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609 hl = top_of_stack(self.S).left.high |
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610 hr = top_of_stack(self.S).right.high |
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611 |
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612 if hl is not None and ( |
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613 hr is None or self.lowpt[hl] > self.lowpt[hr]): |
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614 self.ref[e] = hl |
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615 else: |
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616 self.ref[e] = hr |
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617 |
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618 def dfs_embedding(self, v): |
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619 """Completes the embedding.""" |
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620 # the recursion stack |
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621 dfs_stack = [v] |
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622 # index of next edge to handle in adjacency list of each node |
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623 ind = defaultdict(lambda: 0) |
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624 |
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625 while dfs_stack: |
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626 v = dfs_stack.pop() |
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627 |
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628 for w in self.ordered_adjs[v][ind[v]:]: |
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629 ind[v] += 1 |
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630 ei = (v, w) |
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631 |
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632 if ei == self.parent_edge[w]: # tree edge |
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633 self.embedding.add_half_edge_first(w, v) |
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634 self.left_ref[v] = w |
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635 self.right_ref[v] = w |
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636 |
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637 dfs_stack.append(v) # revisit v after finishing w |
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638 dfs_stack.append(w) # visit w next |
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639 break # handle next node in dfs_stack (i.e. w) |
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640 else: # back edge |
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641 if self.side[ei] == 1: |
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642 self.embedding.add_half_edge_cw(w, v, |
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643 self.right_ref[w]) |
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644 else: |
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645 self.embedding.add_half_edge_ccw(w, v, |
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646 self.left_ref[w]) |
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647 self.left_ref[w] = v |
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648 |
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649 def dfs_embedding_recursive(self, v): |
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650 """Recursive version of :meth:`dfs_embedding`.""" |
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651 for w in self.ordered_adjs[v]: |
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652 ei = (v, w) |
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653 if ei == self.parent_edge[w]: # tree edge |
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654 self.embedding.add_half_edge_first(w, v) |
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655 self.left_ref[v] = w |
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656 self.right_ref[v] = w |
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657 self.dfs_embedding_recursive(w) |
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658 else: # back edge |
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659 if self.side[ei] == 1: |
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660 # place v directly after right_ref[w] in embed. list of w |
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661 self.embedding.add_half_edge_cw(w, v, self.right_ref[w]) |
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662 else: |
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663 # place v directly before left_ref[w] in embed. list of w |
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664 self.embedding.add_half_edge_ccw(w, v, self.left_ref[w]) |
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665 self.left_ref[w] = v |
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666 |
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667 def sign(self, e): |
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668 """Resolve the relative side of an edge to the absolute side.""" |
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669 # the recursion stack |
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670 dfs_stack = [e] |
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671 # dict to remember reference edges |
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672 old_ref = defaultdict(lambda: None) |
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673 |
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674 while dfs_stack: |
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675 e = dfs_stack.pop() |
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676 |
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677 if self.ref[e] is not None: |
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678 dfs_stack.append(e) # revisit e after finishing self.ref[e] |
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679 dfs_stack.append(self.ref[e]) # visit self.ref[e] next |
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680 old_ref[e] = self.ref[e] # remember value of self.ref[e] |
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681 self.ref[e] = None |
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682 else: |
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683 self.side[e] *= self.side[old_ref[e]] |
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684 |
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685 return self.side[e] |
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686 |
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687 def sign_recursive(self, e): |
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688 """Recursive version of :meth:`sign`.""" |
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689 if self.ref[e] is not None: |
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690 self.side[e] = self.side[e] * self.sign_recursive(self.ref[e]) |
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691 self.ref[e] = None |
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692 return self.side[e] |
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693 |
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694 |
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695 class PlanarEmbedding(nx.DiGraph): |
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696 """Represents a planar graph with its planar embedding. |
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697 |
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698 The planar embedding is given by a `combinatorial embedding |
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699 <https://en.wikipedia.org/wiki/Graph_embedding#Combinatorial_embedding>`_. |
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700 |
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701 **Neighbor ordering:** |
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702 |
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703 In comparison to a usual graph structure, the embedding also stores the |
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704 order of all neighbors for every vertex. |
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705 The order of the neighbors can be given in clockwise (cw) direction or |
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706 counterclockwise (ccw) direction. This order is stored as edge attributes |
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707 in the underlying directed graph. For the edge (u, v) the edge attribute |
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708 'cw' is set to the neighbor of u that follows immediately after v in |
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709 clockwise direction. |
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710 |
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711 In order for a PlanarEmbedding to be valid it must fulfill multiple |
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712 conditions. It is possible to check if these conditions are fulfilled with |
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713 the method :meth:`check_structure`. |
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714 The conditions are: |
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715 |
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716 * Edges must go in both directions (because the edge attributes differ) |
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717 * Every edge must have a 'cw' and 'ccw' attribute which corresponds to a |
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718 correct planar embedding. |
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719 * A node with non zero degree must have a node attribute 'first_nbr'. |
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720 |
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721 As long as a PlanarEmbedding is invalid only the following methods should |
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722 be called: |
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723 |
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724 * :meth:`add_half_edge_ccw` |
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725 * :meth:`add_half_edge_cw` |
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726 * :meth:`connect_components` |
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727 * :meth:`add_half_edge_first` |
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728 |
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729 Even though the graph is a subclass of nx.DiGraph, it can still be used |
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730 for algorithms that require undirected graphs, because the method |
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731 :meth:`is_directed` is overridden. This is possible, because a valid |
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732 PlanarGraph must have edges in both directions. |
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733 |
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734 **Half edges:** |
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735 |
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736 In methods like `add_half_edge_ccw` the term "half-edge" is used, which is |
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737 a term that is used in `doubly connected edge lists |
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738 <https://en.wikipedia.org/wiki/Doubly_connected_edge_list>`_. It is used |
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739 to emphasize that the edge is only in one direction and there exists |
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740 another half-edge in the opposite direction. |
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741 While conventional edges always have two faces (including outer face) next |
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742 to them, it is possible to assign each half-edge *exactly one* face. |
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743 For a half-edge (u, v) that is orientated such that u is below v then the |
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744 face that belongs to (u, v) is to the right of this half-edge. |
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745 |
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746 Examples |
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747 -------- |
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748 |
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749 Create an embedding of a star graph (compare `nx.star_graph(3)`): |
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750 |
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751 >>> G = nx.PlanarEmbedding() |
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752 >>> G.add_half_edge_cw(0, 1, None) |
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753 >>> G.add_half_edge_cw(0, 2, 1) |
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754 >>> G.add_half_edge_cw(0, 3, 2) |
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755 >>> G.add_half_edge_cw(1, 0, None) |
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756 >>> G.add_half_edge_cw(2, 0, None) |
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757 >>> G.add_half_edge_cw(3, 0, None) |
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758 |
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759 Alternatively the same embedding can also be defined in counterclockwise |
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760 orientation. The following results in exactly the same PlanarEmbedding: |
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761 |
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762 >>> G = nx.PlanarEmbedding() |
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763 >>> G.add_half_edge_ccw(0, 1, None) |
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764 >>> G.add_half_edge_ccw(0, 3, 1) |
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765 >>> G.add_half_edge_ccw(0, 2, 3) |
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766 >>> G.add_half_edge_ccw(1, 0, None) |
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767 >>> G.add_half_edge_ccw(2, 0, None) |
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768 >>> G.add_half_edge_ccw(3, 0, None) |
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769 |
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770 After creating a graph, it is possible to validate that the PlanarEmbedding |
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771 object is correct: |
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772 |
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773 >>> G.check_structure() |
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774 |
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775 """ |
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776 |
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777 def get_data(self): |
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778 """Converts the adjacency structure into a better readable structure. |
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779 |
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780 Returns |
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781 ------- |
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782 embedding : dict |
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783 A dict mapping all nodes to a list of neighbors sorted in |
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784 clockwise order. |
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785 |
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786 See Also |
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787 -------- |
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788 set_data |
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789 |
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790 """ |
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791 embedding = dict() |
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792 for v in self: |
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793 embedding[v] = list(self.neighbors_cw_order(v)) |
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794 return embedding |
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795 |
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796 def set_data(self, data): |
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797 """Inserts edges according to given sorted neighbor list. |
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798 |
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799 The input format is the same as the output format of get_data(). |
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800 |
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801 Parameters |
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802 ---------- |
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803 data : dict |
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804 A dict mapping all nodes to a list of neighbors sorted in |
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805 clockwise order. |
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806 |
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807 See Also |
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808 -------- |
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809 get_data |
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810 |
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811 """ |
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812 for v in data: |
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813 for w in reversed(data[v]): |
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814 self.add_half_edge_first(v, w) |
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815 |
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816 def neighbors_cw_order(self, v): |
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817 """Generator for the neighbors of v in clockwise order. |
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818 |
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819 Parameters |
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820 ---------- |
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821 v : node |
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822 |
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823 Yields |
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824 ------ |
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825 node |
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826 |
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827 """ |
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828 if len(self[v]) == 0: |
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829 # v has no neighbors |
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830 return |
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831 start_node = self.nodes[v]['first_nbr'] |
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832 yield start_node |
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833 current_node = self[v][start_node]['cw'] |
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834 while start_node != current_node: |
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835 yield current_node |
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836 current_node = self[v][current_node]['cw'] |
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837 |
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838 def check_structure(self): |
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839 """Runs without exceptions if this object is valid. |
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840 |
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841 Checks that the following properties are fulfilled: |
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842 |
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843 * Edges go in both directions (because the edge attributes differ). |
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844 * Every edge has a 'cw' and 'ccw' attribute which corresponds to a |
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845 correct planar embedding. |
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846 * A node with a degree larger than 0 has a node attribute 'first_nbr'. |
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847 |
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848 Running this method verifies that the underlying Graph must be planar. |
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849 |
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850 Raises |
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851 ------ |
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852 nx.NetworkXException |
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853 This exception is raised with a short explanation if the |
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854 PlanarEmbedding is invalid. |
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855 """ |
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856 # Check fundamental structure |
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857 for v in self: |
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858 try: |
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859 sorted_nbrs = set(self.neighbors_cw_order(v)) |
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860 except KeyError: |
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861 msg = "Bad embedding. " \ |
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862 "Missing orientation for a neighbor of {}".format(v) |
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863 raise nx.NetworkXException(msg) |
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864 |
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865 unsorted_nbrs = set(self[v]) |
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866 if sorted_nbrs != unsorted_nbrs: |
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867 msg = "Bad embedding. Edge orientations not set correctly." |
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868 raise nx.NetworkXException(msg) |
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869 for w in self[v]: |
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870 # Check if opposite half-edge exists |
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871 if not self.has_edge(w, v): |
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872 msg = "Bad embedding. Opposite half-edge is missing." |
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873 raise nx.NetworkXException(msg) |
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874 |
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875 # Check planarity |
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876 counted_half_edges = set() |
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877 for component in nx.connected_components(self): |
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878 if len(component) == 1: |
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879 # Don't need to check single node component |
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880 continue |
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881 num_nodes = len(component) |
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882 num_half_edges = 0 |
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883 num_faces = 0 |
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884 for v in component: |
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885 for w in self.neighbors_cw_order(v): |
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886 num_half_edges += 1 |
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887 if (v, w) not in counted_half_edges: |
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888 # We encountered a new face |
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889 num_faces += 1 |
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890 # Mark all half-edges belonging to this face |
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891 self.traverse_face(v, w, counted_half_edges) |
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892 num_edges = num_half_edges // 2 # num_half_edges is even |
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893 if num_nodes - num_edges + num_faces != 2: |
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894 # The result does not match Euler's formula |
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895 msg = "Bad embedding. The graph does not match Euler's formula" |
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896 raise nx.NetworkXException(msg) |
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897 |
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898 def add_half_edge_ccw(self, start_node, end_node, reference_neighbor): |
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899 """Adds a half-edge from start_node to end_node. |
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900 |
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901 The half-edge is added counter clockwise next to the existing half-edge |
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902 (start_node, reference_neighbor). |
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903 |
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904 Parameters |
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905 ---------- |
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906 start_node : node |
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907 Start node of inserted edge. |
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908 end_node : node |
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909 End node of inserted edge. |
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910 reference_neighbor: node |
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911 End node of reference edge. |
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912 |
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913 Raises |
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914 ------ |
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915 nx.NetworkXException |
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916 If the reference_neighbor does not exist. |
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917 |
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918 See Also |
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919 -------- |
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920 add_half_edge_cw |
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921 connect_components |
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922 add_half_edge_first |
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923 |
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924 """ |
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925 if reference_neighbor is None: |
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926 # The start node has no neighbors |
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927 self.add_edge(start_node, end_node) # Add edge to graph |
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928 self[start_node][end_node]['cw'] = end_node |
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929 self[start_node][end_node]['ccw'] = end_node |
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930 self.nodes[start_node]['first_nbr'] = end_node |
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931 else: |
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932 ccw_reference = self[start_node][reference_neighbor]['ccw'] |
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933 self.add_half_edge_cw(start_node, end_node, ccw_reference) |
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934 |
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935 if reference_neighbor == self.nodes[start_node].get('first_nbr', |
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936 None): |
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937 # Update first neighbor |
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938 self.nodes[start_node]['first_nbr'] = end_node |
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939 |
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940 def add_half_edge_cw(self, start_node, end_node, reference_neighbor): |
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941 """Adds a half-edge from start_node to end_node. |
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942 |
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943 The half-edge is added clockwise next to the existing half-edge |
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944 (start_node, reference_neighbor). |
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945 |
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946 Parameters |
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947 ---------- |
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948 start_node : node |
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949 Start node of inserted edge. |
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950 end_node : node |
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951 End node of inserted edge. |
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952 reference_neighbor: node |
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953 End node of reference edge. |
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954 |
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955 Raises |
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956 ------ |
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957 nx.NetworkXException |
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958 If the reference_neighbor does not exist. |
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959 |
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960 See Also |
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961 -------- |
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962 add_half_edge_ccw |
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963 connect_components |
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964 add_half_edge_first |
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965 """ |
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966 self.add_edge(start_node, end_node) # Add edge to graph |
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967 |
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968 if reference_neighbor is None: |
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969 # The start node has no neighbors |
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970 self[start_node][end_node]['cw'] = end_node |
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971 self[start_node][end_node]['ccw'] = end_node |
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972 self.nodes[start_node]['first_nbr'] = end_node |
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973 return |
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974 |
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975 if reference_neighbor not in self[start_node]: |
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976 raise nx.NetworkXException( |
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977 "Cannot add edge. Reference neighbor does not exist") |
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978 |
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979 # Get half-edge at the other side |
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980 cw_reference = self[start_node][reference_neighbor]['cw'] |
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981 # Alter half-edge data structures |
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982 self[start_node][reference_neighbor]['cw'] = end_node |
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983 self[start_node][end_node]['cw'] = cw_reference |
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984 self[start_node][cw_reference]['ccw'] = end_node |
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985 self[start_node][end_node]['ccw'] = reference_neighbor |
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986 |
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987 def connect_components(self, v, w): |
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988 """Adds half-edges for (v, w) and (w, v) at some position. |
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989 |
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990 This method should only be called if v and w are in different |
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991 components, or it might break the embedding. |
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992 This especially means that if `connect_components(v, w)` |
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993 is called it is not allowed to call `connect_components(w, v)` |
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994 afterwards. The neighbor orientations in both directions are |
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995 all set correctly after the first call. |
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996 |
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997 Parameters |
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998 ---------- |
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999 v : node |
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1000 w : node |
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1001 |
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1002 See Also |
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1003 -------- |
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1004 add_half_edge_ccw |
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1005 add_half_edge_cw |
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1006 add_half_edge_first |
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1007 """ |
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1008 self.add_half_edge_first(v, w) |
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1009 self.add_half_edge_first(w, v) |
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1010 |
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1011 def add_half_edge_first(self, start_node, end_node): |
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1012 """The added half-edge is inserted at the first position in the order. |
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1013 |
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1014 Parameters |
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1015 ---------- |
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1016 start_node : node |
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1017 end_node : node |
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1018 |
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1019 See Also |
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1020 -------- |
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1021 add_half_edge_ccw |
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1022 add_half_edge_cw |
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1023 connect_components |
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1024 """ |
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1025 if start_node in self and 'first_nbr' in self.nodes[start_node]: |
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1026 reference = self.nodes[start_node]['first_nbr'] |
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1027 else: |
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1028 reference = None |
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1029 self.add_half_edge_ccw(start_node, end_node, reference) |
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1030 |
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1031 def next_face_half_edge(self, v, w): |
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1032 """Returns the following half-edge left of a face. |
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1033 |
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1034 Parameters |
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1035 ---------- |
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1036 v : node |
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1037 w : node |
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1038 |
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1039 Returns |
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1040 ------- |
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1041 half-edge : tuple |
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1042 """ |
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1043 new_node = self[w][v]['ccw'] |
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1044 return w, new_node |
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1045 |
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1046 def traverse_face(self, v, w, mark_half_edges=None): |
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1047 """Returns nodes on the face that belong to the half-edge (v, w). |
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1048 |
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1049 The face that is traversed lies to the right of the half-edge (in an |
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1050 orientation where v is below w). |
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1051 |
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1052 Optionally it is possible to pass a set to which all encountered half |
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1053 edges are added. Before calling this method, this set must not include |
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1054 any half-edges that belong to the face. |
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1055 |
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1056 Parameters |
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1057 ---------- |
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1058 v : node |
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1059 Start node of half-edge. |
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1060 w : node |
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1061 End node of half-edge. |
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1062 mark_half_edges: set, optional |
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1063 Set to which all encountered half-edges are added. |
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1064 |
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1065 Returns |
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1066 ------- |
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1067 face : list |
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1068 A list of nodes that lie on this face. |
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1069 """ |
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1070 if mark_half_edges is None: |
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1071 mark_half_edges = set() |
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1072 |
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1073 face_nodes = [v] |
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1074 mark_half_edges.add((v, w)) |
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1075 prev_node = v |
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1076 cur_node = w |
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1077 # Last half-edge is (incoming_node, v) |
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1078 incoming_node = self[v][w]['cw'] |
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1079 |
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1080 while cur_node != v or prev_node != incoming_node: |
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1081 face_nodes.append(cur_node) |
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1082 prev_node, cur_node = self.next_face_half_edge(prev_node, cur_node) |
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1083 if (prev_node, cur_node) in mark_half_edges: |
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1084 raise nx.NetworkXException( |
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1085 "Bad planar embedding. Impossible face.") |
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1086 mark_half_edges.add((prev_node, cur_node)) |
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1087 |
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1088 return face_nodes |
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1089 |
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1090 def is_directed(self): |
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1091 """A valid PlanarEmbedding is undirected. |
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1092 |
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1093 All reverse edges are contained, i.e. for every existing |
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1094 half-edge (v, w) the half-edge in the opposite direction (w, v) is also |
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1095 contained. |
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1096 """ |
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1097 return False |