Mercurial > repos > shellac > sam_consensus_v3
annotate env/lib/python3.9/sitepackages/networkx/algorithms/tests/test_planar_drawing.py @ 0:4f3585e2f14b draft default tip
"planemo upload commit 60cee0fc7c0cda8592644e1aad72851dec82c959"
author  shellac 

date  Mon, 22 Mar 2021 18:12:50 +0000 
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rev  line source 

0
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1 import pytest 
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2 import networkx as nx 
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3 from networkx.algorithms.planar_drawing import triangulate_embedding 
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4 import math 
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5 
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6 
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7 def test_graph1(): 
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8 embedding_data = {0: [1, 2, 3], 1: [2, 0], 2: [3, 0, 1], 3: [2, 0]} 
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9 check_embedding_data(embedding_data) 
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10 
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11 
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12 def test_graph2(): 
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13 embedding_data = { 
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14 0: [8, 6], 
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15 1: [2, 6, 9], 
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16 2: [8, 1, 7, 9, 6, 4], 
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17 3: [9], 
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18 4: [2], 
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19 5: [6, 8], 
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20 6: [9, 1, 0, 5, 2], 
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21 7: [9, 2], 
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22 8: [0, 2, 5], 
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23 9: [1, 6, 2, 7, 3], 
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24 } 
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25 check_embedding_data(embedding_data) 
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26 
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27 
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28 def test_circle_graph(): 
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29 embedding_data = { 
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30 0: [1, 9], 
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31 1: [0, 2], 
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32 2: [1, 3], 
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33 3: [2, 4], 
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34 4: [3, 5], 
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35 5: [4, 6], 
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36 6: [5, 7], 
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37 7: [6, 8], 
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38 8: [7, 9], 
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39 9: [8, 0], 
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40 } 
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41 check_embedding_data(embedding_data) 
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42 
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43 
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44 def test_grid_graph(): 
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45 embedding_data = { 
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46 (0, 1): [(0, 0), (1, 1), (0, 2)], 
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47 (1, 2): [(1, 1), (2, 2), (0, 2)], 
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48 (0, 0): [(0, 1), (1, 0)], 
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49 (2, 1): [(2, 0), (2, 2), (1, 1)], 
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50 (1, 1): [(2, 1), (1, 2), (0, 1), (1, 0)], 
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51 (2, 0): [(1, 0), (2, 1)], 
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52 (2, 2): [(1, 2), (2, 1)], 
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53 (1, 0): [(0, 0), (2, 0), (1, 1)], 
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54 (0, 2): [(1, 2), (0, 1)], 
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55 } 
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56 check_embedding_data(embedding_data) 
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57 
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58 
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59 def test_one_node_graph(): 
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60 embedding_data = {0: []} 
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61 check_embedding_data(embedding_data) 
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62 
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63 
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64 def test_two_node_graph(): 
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65 embedding_data = {0: [1], 1: [0]} 
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66 check_embedding_data(embedding_data) 
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67 
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68 
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69 def test_three_node_graph(): 
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70 embedding_data = {0: [1, 2], 1: [0, 2], 2: [0, 1]} 
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71 check_embedding_data(embedding_data) 
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72 
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73 
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74 def test_multiple_component_graph1(): 
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75 embedding_data = {0: [], 1: []} 
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76 check_embedding_data(embedding_data) 
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77 
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78 
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79 def test_multiple_component_graph2(): 
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80 embedding_data = {0: [1, 2], 1: [0, 2], 2: [0, 1], 3: [4, 5], 4: [3, 5], 5: [3, 4]} 
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81 check_embedding_data(embedding_data) 
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82 
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83 
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84 def test_invalid_half_edge(): 
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85 with pytest.raises(nx.NetworkXException): 
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86 embedding_data = {1: [2, 3, 4], 2: [1, 3, 4], 3: [1, 2, 4], 4: [1, 2, 3]} 
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87 embedding = nx.PlanarEmbedding() 
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88 embedding.set_data(embedding_data) 
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89 nx.combinatorial_embedding_to_pos(embedding) 
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90 
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91 
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92 def test_triangulate_embedding1(): 
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93 embedding = nx.PlanarEmbedding() 
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94 embedding.add_node(1) 
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95 expected_embedding = {1: []} 
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96 check_triangulation(embedding, expected_embedding) 
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97 
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98 
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99 def test_triangulate_embedding2(): 
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100 embedding = nx.PlanarEmbedding() 
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101 embedding.connect_components(1, 2) 
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102 expected_embedding = {1: [2], 2: [1]} 
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103 check_triangulation(embedding, expected_embedding) 
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104 
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105 
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106 def check_triangulation(embedding, expected_embedding): 
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107 res_embedding, _ = triangulate_embedding(embedding, True) 
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108 assert ( 
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109 res_embedding.get_data() == expected_embedding 
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110 ), "Expected embedding incorrect" 
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111 res_embedding, _ = triangulate_embedding(embedding, False) 
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112 assert ( 
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113 res_embedding.get_data() == expected_embedding 
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114 ), "Expected embedding incorrect" 
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115 
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116 
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117 def check_embedding_data(embedding_data): 
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118 """Checks that the planar embedding of the input is correct""" 
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119 embedding = nx.PlanarEmbedding() 
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120 embedding.set_data(embedding_data) 
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121 pos_fully = nx.combinatorial_embedding_to_pos(embedding, False) 
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122 msg = "Planar drawing does not conform to the embedding (fully " "triangulation)" 
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123 assert planar_drawing_conforms_to_embedding(embedding, pos_fully), msg 
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124 check_edge_intersections(embedding, pos_fully) 
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125 pos_internally = nx.combinatorial_embedding_to_pos(embedding, True) 
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126 msg = "Planar drawing does not conform to the embedding (internal " "triangulation)" 
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127 assert planar_drawing_conforms_to_embedding(embedding, pos_internally), msg 
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128 check_edge_intersections(embedding, pos_internally) 
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129 
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130 
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131 def is_close(a, b, rel_tol=1e09, abs_tol=0.0): 
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132 # Check if float numbers are basically equal, for python >=3.5 there is 
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133 # function for that in the standard library 
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134 return abs(a  b) <= max(rel_tol * max(abs(a), abs(b)), abs_tol) 
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135 
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136 
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137 def point_in_between(a, b, p): 
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138 # checks if p is on the line between a and b 
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139 x1, y1 = a 
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140 x2, y2 = b 
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141 px, py = p 
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142 dist_1_2 = math.sqrt((x1  x2) ** 2 + (y1  y2) ** 2) 
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143 dist_1_p = math.sqrt((x1  px) ** 2 + (y1  py) ** 2) 
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144 dist_2_p = math.sqrt((x2  px) ** 2 + (y2  py) ** 2) 
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145 return is_close(dist_1_p + dist_2_p, dist_1_2) 
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146 
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147 
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148 def check_edge_intersections(G, pos): 
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149 """Check all edges in G for intersections. 
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150 
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151 Raises an exception if an intersection is found. 
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152 
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153 Parameters 
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154  
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155 G : NetworkX graph 
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156 pos : dict 
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157 Maps every node to a tuple (x, y) representing its position 
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158 
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159 """ 
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160 for a, b in G.edges(): 
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161 for c, d in G.edges(): 
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162 # Check if end points are different 
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163 if a != c and b != d and b != c and a != d: 
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164 x1, y1 = pos[a] 
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165 x2, y2 = pos[b] 
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166 x3, y3 = pos[c] 
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167 x4, y4 = pos[d] 
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168 determinant = (x1  x2) * (y3  y4)  (y1  y2) * (x3  x4) 
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169 if determinant != 0: # the lines are not parallel 
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170 # calculate intersection point, see: 
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171 # https://en.wikipedia.org/wiki/Line%E2%80%93line_intersection 
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172 px = (x1 * y2  y1 * x2) * (x3  x4)  (x1  x2) * ( 
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173 x3 * y4  y3 * x4 
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174 ) / float(determinant) 
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175 py = (x1 * y2  y1 * x2) * (y3  y4)  (y1  y2) * ( 
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176 x3 * y4  y3 * x4 
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177 ) / float(determinant) 
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178 
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179 # Check if intersection lies between the points 
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180 if point_in_between(pos[a], pos[b], (px, py)) and point_in_between( 
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181 pos[c], pos[d], (px, py) 
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182 ): 
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183 msg = f"There is an intersection at {px},{py}" 
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184 raise nx.NetworkXException(msg) 
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185 
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186 # Check overlap 
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187 msg = "A node lies on a edge connecting two other nodes" 
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188 if ( 
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189 point_in_between(pos[a], pos[b], pos[c]) 
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190 or point_in_between(pos[a], pos[b], pos[d]) 
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191 or point_in_between(pos[c], pos[d], pos[a]) 
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192 or point_in_between(pos[c], pos[d], pos[b]) 
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193 ): 
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194 raise nx.NetworkXException(msg) 
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195 # No edge intersection found 
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196 
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197 
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198 class Vector: 
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199 """Compare vectors by their angle without loss of precision 
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200 
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201 All vectors in direction [0, 1] are the smallest. 
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202 The vectors grow in clockwise direction. 
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203 """ 
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204 
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205 __slots__ = ["x", "y", "node", "quadrant"] 
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206 
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207 def __init__(self, x, y, node): 
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208 self.x = x 
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209 self.y = y 
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210 self.node = node 
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211 if self.x >= 0 and self.y > 0: 
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212 self.quadrant = 1 
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213 elif self.x > 0 and self.y <= 0: 
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214 self.quadrant = 2 
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215 elif self.x <= 0 and self.y < 0: 
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216 self.quadrant = 3 
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217 else: 
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218 self.quadrant = 4 
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219 
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220 def __eq__(self, other): 
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221 return self.quadrant == other.quadrant and self.x * other.y == self.y * other.x 
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222 
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223 def __lt__(self, other): 
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224 if self.quadrant < other.quadrant: 
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225 return True 
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226 elif self.quadrant > other.quadrant: 
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227 return False 
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228 else: 
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229 return self.x * other.y < self.y * other.x 
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230 
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231 def __ne__(self, other): 
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232 return not self == other 
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233 
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234 def __le__(self, other): 
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235 return not other < self 
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236 
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237 def __gt__(self, other): 
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238 return other < self 
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239 
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240 def __ge__(self, other): 
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241 return not self < other 
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242 
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243 
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244 def planar_drawing_conforms_to_embedding(embedding, pos): 
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245 """Checks if pos conforms to the planar embedding 
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246 
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247 Returns true iff the neighbors are actually oriented in the orientation 
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248 specified of the embedding 
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249 """ 
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250 for v in embedding: 
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251 nbr_vectors = [] 
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252 v_pos = pos[v] 
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253 for nbr in embedding[v]: 
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254 new_vector = Vector(pos[nbr][0]  v_pos[0], pos[nbr][1]  v_pos[1], nbr) 
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255 nbr_vectors.append(new_vector) 
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256 # Sort neighbors according to their phi angle 
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257 nbr_vectors.sort() 
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258 for idx, nbr_vector in enumerate(nbr_vectors): 
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259 cw_vector = nbr_vectors[(idx + 1) % len(nbr_vectors)] 
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260 ccw_vector = nbr_vectors[idx  1] 
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261 if ( 
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262 embedding[v][nbr_vector.node]["cw"] != cw_vector.node 
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263 or embedding[v][nbr_vector.node]["ccw"] != ccw_vector.node 
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264 ): 
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265 return False 
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266 if cw_vector.node != nbr_vector.node and cw_vector == nbr_vector: 
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267 # Lines overlap 
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268 return False 
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269 if ccw_vector.node != nbr_vector.node and ccw_vector == nbr_vector: 
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270 # Lines overlap 
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271 return False 
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272 return True 