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annotate planemo/lib/python3.7/site-packages/networkx/algorithms/dominance.py @ 1:56ad4e20f292 draft

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"planemo upload commit 6eee67778febed82ddd413c3ca40b3183a3898f1"
author guerler
date Fri, 31 Jul 2020 00:32:28 -0400
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1 # Copyright (C) 2014-2019 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 #
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8 # Authors: ysitu (ysitu@users.noreply.github.com)
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9 """
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10 Dominance algorithms.
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11 """
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12
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13 from functools import reduce
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14 import networkx as nx
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15 from networkx.utils import not_implemented_for
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16
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17 __all__ = ['immediate_dominators', 'dominance_frontiers']
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18
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19
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20 @not_implemented_for('undirected')
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21 def immediate_dominators(G, start):
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22 """Returns the immediate dominators of all nodes of a directed graph.
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23
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24 Parameters
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25 ----------
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26 G : a DiGraph or MultiDiGraph
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27 The graph where dominance is to be computed.
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28
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29 start : node
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30 The start node of dominance computation.
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31
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32 Returns
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33 -------
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34 idom : dict keyed by nodes
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35 A dict containing the immediate dominators of each node reachable from
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36 `start`.
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37
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38 Raises
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39 ------
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40 NetworkXNotImplemented
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41 If `G` is undirected.
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42
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43 NetworkXError
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44 If `start` is not in `G`.
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45
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46 Notes
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47 -----
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48 Except for `start`, the immediate dominators are the parents of their
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49 corresponding nodes in the dominator tree.
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50
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51 Examples
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52 --------
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53 >>> G = nx.DiGraph([(1, 2), (1, 3), (2, 5), (3, 4), (4, 5)])
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54 >>> sorted(nx.immediate_dominators(G, 1).items())
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55 [(1, 1), (2, 1), (3, 1), (4, 3), (5, 1)]
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56
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57 References
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58 ----------
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59 .. [1] K. D. Cooper, T. J. Harvey, and K. Kennedy.
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60 A simple, fast dominance algorithm.
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61 Software Practice & Experience, 4:110, 2001.
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62 """
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63 if start not in G:
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64 raise nx.NetworkXError('start is not in G')
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65
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66 idom = {start: start}
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67
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68 order = list(nx.dfs_postorder_nodes(G, start))
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69 dfn = {u: i for i, u in enumerate(order)}
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70 order.pop()
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71 order.reverse()
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72
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73 def intersect(u, v):
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74 while u != v:
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75 while dfn[u] < dfn[v]:
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76 u = idom[u]
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77 while dfn[u] > dfn[v]:
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78 v = idom[v]
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79 return u
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80
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81 changed = True
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82 while changed:
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83 changed = False
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84 for u in order:
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85 new_idom = reduce(intersect, (v for v in G.pred[u] if v in idom))
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86 if u not in idom or idom[u] != new_idom:
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87 idom[u] = new_idom
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88 changed = True
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89
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90 return idom
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91
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92
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93 def dominance_frontiers(G, start):
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94 """Returns the dominance frontiers of all nodes of a directed graph.
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95
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96 Parameters
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97 ----------
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98 G : a DiGraph or MultiDiGraph
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99 The graph where dominance is to be computed.
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100
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101 start : node
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102 The start node of dominance computation.
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103
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104 Returns
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105 -------
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106 df : dict keyed by nodes
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107 A dict containing the dominance frontiers of each node reachable from
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108 `start` as lists.
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109
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110 Raises
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111 ------
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112 NetworkXNotImplemented
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113 If `G` is undirected.
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114
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115 NetworkXError
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116 If `start` is not in `G`.
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117
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118 Examples
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119 --------
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120 >>> G = nx.DiGraph([(1, 2), (1, 3), (2, 5), (3, 4), (4, 5)])
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121 >>> sorted((u, sorted(df)) for u, df in nx.dominance_frontiers(G, 1).items())
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122 [(1, []), (2, [5]), (3, [5]), (4, [5]), (5, [])]
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123
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124 References
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125 ----------
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126 .. [1] K. D. Cooper, T. J. Harvey, and K. Kennedy.
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127 A simple, fast dominance algorithm.
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128 Software Practice & Experience, 4:110, 2001.
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129 """
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130 idom = nx.immediate_dominators(G, start)
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131
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132 df = {u: set() for u in idom}
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133 for u in idom:
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134 if len(G.pred[u]) >= 2:
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135 for v in G.pred[u]:
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136 if v in idom:
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137 while v != idom[u]:
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138 df[v].add(u)
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139 v = idom[v]
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140 return df