Mercurial > repos > shellac > sam_consensus_v3
annotate env/lib/python3.9/site-packages/networkx/algorithms/dominance.py @ 0:4f3585e2f14b draft default tip
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author | shellac |
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date | Mon, 22 Mar 2021 18:12:50 +0000 |
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1 """ |
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2 Dominance algorithms. |
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3 """ |
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4 |
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5 from functools import reduce |
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6 import networkx as nx |
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7 from networkx.utils import not_implemented_for |
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8 |
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9 __all__ = ["immediate_dominators", "dominance_frontiers"] |
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10 |
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11 |
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12 @not_implemented_for("undirected") |
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13 def immediate_dominators(G, start): |
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14 """Returns the immediate dominators of all nodes of a directed graph. |
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15 |
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16 Parameters |
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17 ---------- |
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18 G : a DiGraph or MultiDiGraph |
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19 The graph where dominance is to be computed. |
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20 |
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21 start : node |
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22 The start node of dominance computation. |
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23 |
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24 Returns |
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25 ------- |
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26 idom : dict keyed by nodes |
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27 A dict containing the immediate dominators of each node reachable from |
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28 `start`. |
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29 |
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30 Raises |
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31 ------ |
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32 NetworkXNotImplemented |
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33 If `G` is undirected. |
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34 |
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35 NetworkXError |
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36 If `start` is not in `G`. |
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37 |
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38 Notes |
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39 ----- |
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40 Except for `start`, the immediate dominators are the parents of their |
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41 corresponding nodes in the dominator tree. |
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42 |
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43 Examples |
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44 -------- |
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45 >>> G = nx.DiGraph([(1, 2), (1, 3), (2, 5), (3, 4), (4, 5)]) |
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46 >>> sorted(nx.immediate_dominators(G, 1).items()) |
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47 [(1, 1), (2, 1), (3, 1), (4, 3), (5, 1)] |
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48 |
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49 References |
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50 ---------- |
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51 .. [1] K. D. Cooper, T. J. Harvey, and K. Kennedy. |
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52 A simple, fast dominance algorithm. |
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53 Software Practice & Experience, 4:110, 2001. |
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54 """ |
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55 if start not in G: |
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56 raise nx.NetworkXError("start is not in G") |
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57 |
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58 idom = {start: start} |
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59 |
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60 order = list(nx.dfs_postorder_nodes(G, start)) |
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61 dfn = {u: i for i, u in enumerate(order)} |
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62 order.pop() |
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63 order.reverse() |
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64 |
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65 def intersect(u, v): |
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66 while u != v: |
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67 while dfn[u] < dfn[v]: |
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68 u = idom[u] |
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69 while dfn[u] > dfn[v]: |
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70 v = idom[v] |
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71 return u |
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72 |
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73 changed = True |
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74 while changed: |
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75 changed = False |
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76 for u in order: |
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77 new_idom = reduce(intersect, (v for v in G.pred[u] if v in idom)) |
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78 if u not in idom or idom[u] != new_idom: |
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79 idom[u] = new_idom |
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80 changed = True |
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81 |
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82 return idom |
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83 |
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84 |
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85 def dominance_frontiers(G, start): |
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86 """Returns the dominance frontiers of all nodes of a directed graph. |
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87 |
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88 Parameters |
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89 ---------- |
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90 G : a DiGraph or MultiDiGraph |
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91 The graph where dominance is to be computed. |
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92 |
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93 start : node |
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94 The start node of dominance computation. |
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95 |
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96 Returns |
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97 ------- |
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98 df : dict keyed by nodes |
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99 A dict containing the dominance frontiers of each node reachable from |
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100 `start` as lists. |
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101 |
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102 Raises |
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103 ------ |
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104 NetworkXNotImplemented |
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105 If `G` is undirected. |
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106 |
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107 NetworkXError |
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108 If `start` is not in `G`. |
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109 |
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110 Examples |
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111 -------- |
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112 >>> G = nx.DiGraph([(1, 2), (1, 3), (2, 5), (3, 4), (4, 5)]) |
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113 >>> sorted((u, sorted(df)) for u, df in nx.dominance_frontiers(G, 1).items()) |
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114 [(1, []), (2, [5]), (3, [5]), (4, [5]), (5, [])] |
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115 |
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116 References |
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117 ---------- |
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118 .. [1] K. D. Cooper, T. J. Harvey, and K. Kennedy. |
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119 A simple, fast dominance algorithm. |
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120 Software Practice & Experience, 4:110, 2001. |
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121 """ |
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122 idom = nx.immediate_dominators(G, start) |
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123 |
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124 df = {u: set() for u in idom} |
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125 for u in idom: |
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126 if len(G.pred[u]) >= 2: |
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127 for v in G.pred[u]: |
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128 if v in idom: |
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129 while v != idom[u]: |
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130 df[v].add(u) |
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131 v = idom[v] |
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132 return df |