1 | #region License Information
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2 | /* HeuristicLab
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3 | * Copyright (C) 2002-2013 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
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4 | *
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5 | * This file is part of HeuristicLab.
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6 | *
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7 | * HeuristicLab is free software: you can redistribute it and/or modify
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8 | * it under the terms of the GNU General Public License as published by
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9 | * the Free Software Foundation, either version 3 of the License, or
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10 | * (at your option) any later version.
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11 | *
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12 | * HeuristicLab is distributed in the hope that it will be useful,
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13 | * but WITHOUT ANY WARRANTY; without even the implied warranty of
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14 | * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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15 | * GNU General Public License for more details.
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16 | *
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17 | * You should have received a copy of the GNU General Public License
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18 | * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
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19 | */
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20 | #endregion
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21 |
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22 | using System;
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23 | using System.Collections.Generic;
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24 | using System.Globalization;
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25 | using System.IO;
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26 | using System.Linq;
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27 | using System.Text;
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28 | using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
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29 | using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding.Views;
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30 | using HeuristicLab.EvolutionTracking;
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31 |
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32 | namespace HeuristicLab.Problems.DataAnalysis.Symbolic {
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33 | public static class BottomUpDistanceCalculator {
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34 | private static Dictionary<ISymbolicExpressionTreeNode, IVertex> Compact(ISymbolicExpressionTree t1, ISymbolicExpressionTree t2) {
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35 | var G = new DirectedGraph();
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36 | var K = new Dictionary<ISymbolicExpressionTreeNode, IVertex>();
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37 | var F = new DisjointUnion(t1, t2);
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38 | var Children = new Dictionary<ISymbolicExpressionTreeNode, int>();
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39 | var L = new Dictionary<string, IVertex>();
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40 | foreach (var l in F.Nodes.Where(x => x.SubtreeCount == 0)) {
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41 | var z = new Vertex { Content = l, Label = Label(l) };
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42 | z.Weight = Height(l); // might be necessary
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43 | L[z.Label] = z;
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44 | G.AddVertex(z);
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45 | }
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46 | var Q = new Queue<ISymbolicExpressionTreeNode>();
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47 | foreach (var v in F.Nodes) {
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48 | Children[v] = v.SubtreeCount;
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49 | if (v.SubtreeCount == 0) {
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50 | Q.Enqueue(v);
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51 | }
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52 | }
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53 | do {
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54 | var v = Q.Dequeue();
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55 | if (v.SubtreeCount == 0) {
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56 | K[v] = L[Label(v)]; // 18
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57 | } else {
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58 | bool found = false;
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59 |
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60 | foreach (var w in G.Vertices.Reverse()) {
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61 | if (Height(v) != Height(w) || v.SubtreeCount != w.OutDegree || Label(v) != w.Label)
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62 | break;
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63 | // sort the lists before comparison, as required when dealing with unordered trees
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64 | var V = v.Subtrees.OrderBy(Label).Select(s => K[s]);
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65 | var W = w.OutArcs.Select(x => x.Target).OrderBy(x => x.Label);
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66 | if (V.SequenceEqual(W)) {
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67 | K[v] = w;
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68 | found = true;
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69 | break;
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70 | }
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71 | } // 32: end for
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72 |
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73 | if (!found) {
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74 | var w = new Vertex { Content = v, Label = Label(v), Weight = Height(v) };
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75 | K[v] = w;
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76 |
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77 | foreach (var u in v.Subtrees) {
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78 | G.AddArc(w, K[u]);
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79 | } // 40: end for
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80 | } // 41: end if
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81 | } // 42: end if
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82 |
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83 | if (!F.IsRoot(v)) {
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84 | Children[v.Parent] = Children[v.Parent] - 1;
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85 | if (Children[v.Parent] == 0) {
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86 | Q.Enqueue(v.Parent);
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87 | } // 47: end if
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88 | } // 48: end if
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89 | } while (Q.Count != 0);
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90 | return K;
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91 | }
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92 |
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93 | private static Dictionary<ISymbolicExpressionTreeNode, ISymbolicExpressionTreeNode> Mapping(ISymbolicExpressionTree t1, ISymbolicExpressionTree t2, Dictionary<ISymbolicExpressionTreeNode, IVertex> K) {
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94 | var M = new Dictionary<ISymbolicExpressionTreeNode, ISymbolicExpressionTreeNode>(); // nodes of t1 => nodes of t2
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95 | var M_ = new Dictionary<ISymbolicExpressionTreeNode, ISymbolicExpressionTreeNode>(); // nodes of t2 => nodes of t1
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96 | //var plist1 = t1.IterateNodesPrefix().ToList();
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97 | var plist2 = t2.IterateNodesPrefix().ToList();
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98 | foreach (var v in t1.IterateNodesBreadth()) {
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99 | if (!M.ContainsKey(v)) {
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100 | var w = plist2.Last();
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101 | foreach (var u in plist2.Where(x => K[x] == K[v])) {
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102 | if (!M_.ContainsKey(u)) {
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103 | if (plist2.IndexOf(u) < plist2.IndexOf(w)) {
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104 | w = u;
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105 | }
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106 | }
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107 | }
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108 | if (K[v] == K[w]) {
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109 | // simultaneous preorder traversal of the two subtrees
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110 | var nodesV = v.IterateNodesPrefix().ToList();
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111 | var nodesW = w.IterateNodesPrefix().ToList();
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112 | for (int i = 0; i < Math.Min(nodesV.Count, nodesW.Count); ++i) {
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113 | var s = nodesV[i];
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114 | var t = nodesW[i];
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115 | M[s] = t;
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116 | M_[t] = s;
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117 | }
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118 | // var e1 = v.IterateNodesPrefix().GetEnumerator();
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119 | // var e2 = w.IterateNodesPrefix().GetEnumerator();
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120 | // while (e1.MoveNext() && e2.MoveNext()) {
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121 | // M[e1.Current] = e2.Current;
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122 | // M_[e2.Current] = e1.Current;
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123 | // }
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124 | }
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125 | }
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126 | }
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127 | return M;
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128 | }
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129 |
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130 | public static double CalculateDistance(ISymbolicExpressionTree t1, ISymbolicExpressionTree t2, double p = 1, double q = 1, double r = 1) {
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131 | var K = Compact(t1, t2);
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132 | var M = Mapping(t1, t2, K);
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133 | int d = t1.Length - M.Count;
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134 | int s = M.Count(x => !Label(x.Key).Equals(Label(x.Value)));
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135 | int i = t2.Length - M.Count;
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136 |
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137 | double distance = s * p + i * q + d * r;
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138 |
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139 | if (distance / (t1.Length + t2.Length) > 0.5 && M.Count > 0) {
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140 | using (var file = new StreamWriter(Path.Combine(Environment.GetFolderPath(Environment.SpecialFolder.MyDocuments), "map.txt"))) {
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141 | var str = FormatMapping(t1, t2, M);
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142 | file.WriteLine(str);
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143 | }
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144 | }
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145 |
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146 | return distance;
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147 | }
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148 |
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149 | private static string Label(ISymbolicExpressionTreeNode n) {
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150 | return n.ToString();
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151 | }
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152 |
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153 | private static int Height(IVertex v) {
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154 | return (int)Math.Round(v.Weight); // use the vertex weight as height in this particular context
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155 | }
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156 |
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157 | private static int Height(ISymbolicExpressionTreeNode n) {
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158 | var p = n;
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159 | while (p.Parent != null)
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160 | p = p.Parent;
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161 | return p.GetBranchLevel(n);
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162 | }
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163 |
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164 | private class DisjointUnion : Tuple<ISymbolicExpressionTree, ISymbolicExpressionTree> {
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165 | public DisjointUnion(ISymbolicExpressionTree t1, ISymbolicExpressionTree t2)
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166 | : base(t1, t2) {
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167 | }
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168 |
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169 | public IEnumerable<ISymbolicExpressionTreeNode> Nodes {
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170 | get { return Item1.IterateNodesPrefix().Concat(Item2.IterateNodesPrefix()); }
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171 | }
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172 |
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173 | public bool IsRoot(ISymbolicExpressionTreeNode n) {
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174 | return (n == Item1.Root || n == Item2.Root);
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175 | }
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176 | }
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177 |
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178 | // draw the mapping between t1 and t2
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179 | private static string FormatMapping(ISymbolicExpressionTree t1, ISymbolicExpressionTree t2, Dictionary<ISymbolicExpressionTreeNode, ISymbolicExpressionTreeNode> map) {
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180 | var formatter = new SymbolicExpressionTreeLatexFormatter();
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181 | var sb = new StringBuilder();
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182 |
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183 | string s1, s2;
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184 | var m1 = formatter.Format(t1, out s1);
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185 | var m2 = formatter.Format(t2, out s2, 20);
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186 |
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187 | sb.Append(s1);
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188 | sb.Append(s2);
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189 |
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190 | foreach (var p in map) {
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191 | var id1 = m1[p.Key];
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192 | var id2 = m2[p.Value];
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193 |
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194 | sb.Append(string.Format(CultureInfo.InvariantCulture, "\\path[draw,->] ({0}) edge[bend left,dashed] ({1});", id1, id2));
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195 | }
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196 |
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197 | return sb.ToString();
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198 | }
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199 | }
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200 | }
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