Mercurial > repos > shellac > guppy_basecaller

annotate env/lib/python3.7/site-packages/networkx/relabel.py @ 0:26e78fe6e8c4 draft

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"planemo upload commit c699937486c35866861690329de38ec1a5d9f783"
author shellac
date Sat, 02 May 2020 07:14:21 -0400
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1 # Copyright (C) 2006-2019 by
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2 # Aric Hagberg <hagberg@lanl.gov>
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3 # Dan Schult <dschult@colgate.edu>
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4 # Pieter Swart <swart@lanl.gov>
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5 # All rights reserved.
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6 # BSD license.
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7 import networkx as nx
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8
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9 __all__ = ['convert_node_labels_to_integers', 'relabel_nodes']
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10
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11
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12 def relabel_nodes(G, mapping, copy=True):
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13 """Relabel the nodes of the graph G.
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14
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15 Parameters
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16 ----------
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17 G : graph
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18 A NetworkX graph
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19
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20 mapping : dictionary
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21 A dictionary with the old labels as keys and new labels as values.
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22 A partial mapping is allowed.
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23
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24 copy : bool (optional, default=True)
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25 If True return a copy, or if False relabel the nodes in place.
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26
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27 Examples
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28 --------
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29 To create a new graph with nodes relabeled according to a given
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30 dictionary:
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31
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32 >>> G = nx.path_graph(3)
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33 >>> sorted(G)
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34 [0, 1, 2]
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35 >>> mapping = {0: 'a', 1: 'b', 2: 'c'}
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36 >>> H = nx.relabel_nodes(G, mapping)
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37 >>> sorted(H)
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38 ['a', 'b', 'c']
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39
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40 Nodes can be relabeled with any hashable object, including numbers
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41 and strings:
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42
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43 >>> import string
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44 >>> G = nx.path_graph(26) # nodes are integers 0 through 25
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45 >>> sorted(G)[:3]
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46 [0, 1, 2]
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47 >>> mapping = dict(zip(G, string.ascii_lowercase))
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48 >>> G = nx.relabel_nodes(G, mapping) # nodes are characters a through z
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49 >>> sorted(G)[:3]
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50 ['a', 'b', 'c']
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51 >>> mapping = dict(zip(G, range(1, 27)))
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52 >>> G = nx.relabel_nodes(G, mapping) # nodes are integers 1 through 26
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53 >>> sorted(G)[:3]
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54 [1, 2, 3]
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55
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56 To perform a partial in-place relabeling, provide a dictionary
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57 mapping only a subset of the nodes, and set the `copy` keyword
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58 argument to False:
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59
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60 >>> G = nx.path_graph(3) # nodes 0-1-2
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61 >>> mapping = {0: 'a', 1: 'b'} # 0->'a' and 1->'b'
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62 >>> G = nx.relabel_nodes(G, mapping, copy=False)
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63 >>> sorted(G, key=str)
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64 [2, 'a', 'b']
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65
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66 A mapping can also be given as a function:
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67
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68 >>> G = nx.path_graph(3)
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69 >>> H = nx.relabel_nodes(G, lambda x: x ** 2)
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70 >>> list(H)
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71 [0, 1, 4]
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72
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73 Notes
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74 -----
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75 Only the nodes specified in the mapping will be relabeled.
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76
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77 The keyword setting copy=False modifies the graph in place.
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78 Relabel_nodes avoids naming collisions by building a
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79 directed graph from ``mapping`` which specifies the order of
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80 relabelings. Naming collisions, such as a->b, b->c, are ordered
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81 such that "b" gets renamed to "c" before "a" gets renamed "b".
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82 In cases of circular mappings (e.g. a->b, b->a), modifying the
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83 graph is not possible in-place and an exception is raised.
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84 In that case, use copy=True.
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85
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86 See Also
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87 --------
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88 convert_node_labels_to_integers
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89 """
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90 # you can pass a function f(old_label)->new_label
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91 # but we'll just make a dictionary here regardless
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92 if not hasattr(mapping, "__getitem__"):
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93 m = {n: mapping(n) for n in G}
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94 else:
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95 m = mapping
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96 if copy:
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97 return _relabel_copy(G, m)
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98 else:
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99 return _relabel_inplace(G, m)
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100
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101
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102 def _relabel_inplace(G, mapping):
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103 old_labels = set(mapping.keys())
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104 new_labels = set(mapping.values())
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105 if len(old_labels & new_labels) > 0:
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106 # labels sets overlap
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107 # can we topological sort and still do the relabeling?
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108 D = nx.DiGraph(list(mapping.items()))
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109 D.remove_edges_from(nx.selfloop_edges(D))
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110 try:
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111 nodes = reversed(list(nx.topological_sort(D)))
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112 except nx.NetworkXUnfeasible:
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113 raise nx.NetworkXUnfeasible('The node label sets are overlapping '
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114 'and no ordering can resolve the '
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115 'mapping. Use copy=True.')
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116 else:
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117 # non-overlapping label sets
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118 nodes = old_labels
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119
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120 multigraph = G.is_multigraph()
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121 directed = G.is_directed()
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122
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123 for old in nodes:
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124 try:
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125 new = mapping[old]
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126 except KeyError:
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127 continue
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128 if new == old:
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129 continue
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130 try:
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131 G.add_node(new, **G.nodes[old])
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132 except KeyError:
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133 raise KeyError("Node %s is not in the graph" % old)
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134 if multigraph:
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135 new_edges = [(new, new if old == target else target, key, data)
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136 for (_, target, key, data)
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137 in G.edges(old, data=True, keys=True)]
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138 if directed:
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139 new_edges += [(new if old == source else source, new, key, data)
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140 for (source, _, key, data)
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141 in G.in_edges(old, data=True, keys=True)]
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142 else:
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143 new_edges = [(new, new if old == target else target, data)
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144 for (_, target, data) in G.edges(old, data=True)]
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145 if directed:
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146 new_edges += [(new if old == source else source, new, data)
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147 for (source, _, data) in G.in_edges(old, data=True)]
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148 G.remove_node(old)
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149 G.add_edges_from(new_edges)
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150 return G
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151
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152
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153 def _relabel_copy(G, mapping):
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154 H = G.__class__()
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155 H.add_nodes_from(mapping.get(n, n) for n in G)
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156 H._node.update((mapping.get(n, n), d.copy()) for n, d in G.nodes.items())
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157 if G.is_multigraph():
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158 H.add_edges_from((mapping.get(n1, n1), mapping.get(n2, n2), k, d.copy())
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159 for (n1, n2, k, d) in G.edges(keys=True, data=True))
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160 else:
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161 H.add_edges_from((mapping.get(n1, n1), mapping.get(n2, n2), d.copy())
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162 for (n1, n2, d) in G.edges(data=True))
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163 H.graph.update(G.graph)
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164 return H
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165
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166
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167 def convert_node_labels_to_integers(G, first_label=0, ordering="default",
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168 label_attribute=None):
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169 """Returns a copy of the graph G with the nodes relabeled using
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170 consecutive integers.
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171
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172 Parameters
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173 ----------
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174 G : graph
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175 A NetworkX graph
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176
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177 first_label : int, optional (default=0)
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178 An integer specifying the starting offset in numbering nodes.
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179 The new integer labels are numbered first_label, ..., n-1+first_label.
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180
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181 ordering : string
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182 "default" : inherit node ordering from G.nodes()
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183 "sorted" : inherit node ordering from sorted(G.nodes())
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184 "increasing degree" : nodes are sorted by increasing degree
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185 "decreasing degree" : nodes are sorted by decreasing degree
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186
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187 label_attribute : string, optional (default=None)
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188 Name of node attribute to store old label. If None no attribute
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189 is created.
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190
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191 Notes
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192 -----
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193 Node and edge attribute data are copied to the new (relabeled) graph.
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194
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195 There is no guarantee that the relabeling of nodes to integers will
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196 give the same two integers for two (even identical graphs).
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197 Use the `ordering` argument to try to preserve the order.
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198
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199 See Also
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200 --------
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201 relabel_nodes
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202 """
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203 N = G.number_of_nodes() + first_label
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204 if ordering == "default":
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205 mapping = dict(zip(G.nodes(), range(first_label, N)))
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206 elif ordering == "sorted":
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207 nlist = sorted(G.nodes())
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208 mapping = dict(zip(nlist, range(first_label, N)))
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209 elif ordering == "increasing degree":
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210 dv_pairs = [(d, n) for (n, d) in G.degree()]
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211 dv_pairs.sort() # in-place sort from lowest to highest degree
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212 mapping = dict(zip([n for d, n in dv_pairs], range(first_label, N)))
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213 elif ordering == "decreasing degree":
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214 dv_pairs = [(d, n) for (n, d) in G.degree()]
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215 dv_pairs.sort() # in-place sort from lowest to highest degree
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216 dv_pairs.reverse()
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217 mapping = dict(zip([n for d, n in dv_pairs], range(first_label, N)))
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218 else:
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219 raise nx.NetworkXError('Unknown node ordering: %s' % ordering)
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220 H = relabel_nodes(G, mapping)
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221 # create node attribute with the old label
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222 if label_attribute is not None:
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223 nx.set_node_attributes(H, {v: k for k, v in mapping.items()},
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224 label_attribute)
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225 return H