[11015] | 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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[11016] | 42 | // z.Weight = Height(l); // might be necessary (although not specified in the paper)
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| 43 | // if (!L.ContainsKey(z.Label))
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| 44 | L[z.Label] = z; // will overwrite key values, possible bug
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[11015] | 45 | G.AddVertex(z);
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| 46 | }
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| 47 | var Q = new Queue<ISymbolicExpressionTreeNode>();
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| 48 | foreach (var v in F.Nodes) {
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| 49 | Children[v] = v.SubtreeCount;
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| 50 | if (v.SubtreeCount == 0) {
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| 51 | Q.Enqueue(v);
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| 52 | }
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| 53 | }
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[11016] | 54 | while (Q.Any()) {
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[11015] | 55 | var v = Q.Dequeue();
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| 56 | if (v.SubtreeCount == 0) {
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| 57 | K[v] = L[Label(v)]; // 18
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| 58 | } else {
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| 59 | bool found = false;
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| 60 |
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| 61 | foreach (var w in G.Vertices.Reverse()) {
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| 62 | if (Height(v) != Height(w) || v.SubtreeCount != w.OutDegree || Label(v) != w.Label)
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| 63 | break;
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[11016] | 64 |
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[11015] | 65 | // sort the lists before comparison, as required when dealing with unordered trees
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[11016] | 66 | var V = v.Subtrees.Select(s => K[s]).OrderBy(x => x.Label);
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[11015] | 67 | var W = w.OutArcs.Select(x => x.Target).OrderBy(x => x.Label);
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| 68 | if (V.SequenceEqual(W)) {
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| 69 | K[v] = w;
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| 70 | found = true;
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| 71 | break;
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| 72 | }
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| 73 | } // 32: end for
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| 74 |
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| 75 | if (!found) {
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| 76 | var w = new Vertex { Content = v, Label = Label(v), Weight = Height(v) };
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[11016] | 77 | G.AddVertex(w);
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[11015] | 78 | K[v] = w;
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| 79 |
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| 80 | foreach (var u in v.Subtrees) {
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| 81 | G.AddArc(w, K[u]);
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| 82 | } // 40: end for
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| 83 | } // 41: end if
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| 84 | } // 42: end if
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| 85 |
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| 86 | if (!F.IsRoot(v)) {
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| 87 | Children[v.Parent] = Children[v.Parent] - 1;
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| 88 | if (Children[v.Parent] == 0) {
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| 89 | Q.Enqueue(v.Parent);
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| 90 | } // 47: end if
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| 91 | } // 48: end if
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[11016] | 92 | };
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[11015] | 93 | return K;
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| 94 | }
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| 95 |
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| 96 | private static Dictionary<ISymbolicExpressionTreeNode, ISymbolicExpressionTreeNode> Mapping(ISymbolicExpressionTree t1, ISymbolicExpressionTree t2, Dictionary<ISymbolicExpressionTreeNode, IVertex> K) {
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| 97 | var M = new Dictionary<ISymbolicExpressionTreeNode, ISymbolicExpressionTreeNode>(); // nodes of t1 => nodes of t2
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| 98 | var M_ = new Dictionary<ISymbolicExpressionTreeNode, ISymbolicExpressionTreeNode>(); // nodes of t2 => nodes of t1
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| 99 | //var plist1 = t1.IterateNodesPrefix().ToList();
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| 100 | var plist2 = t2.IterateNodesPrefix().ToList();
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| 101 | foreach (var v in t1.IterateNodesBreadth()) {
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| 102 | if (!M.ContainsKey(v)) {
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| 103 | var w = plist2.Last();
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| 104 | foreach (var u in plist2.Where(x => K[x] == K[v])) {
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| 105 | if (!M_.ContainsKey(u)) {
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| 106 | if (plist2.IndexOf(u) < plist2.IndexOf(w)) {
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| 107 | w = u;
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| 108 | }
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| 109 | }
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| 110 | }
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| 111 | if (K[v] == K[w]) {
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| 112 | // simultaneous preorder traversal of the two subtrees
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| 113 | var nodesV = v.IterateNodesPrefix().ToList();
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| 114 | var nodesW = w.IterateNodesPrefix().ToList();
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| 115 | for (int i = 0; i < Math.Min(nodesV.Count, nodesW.Count); ++i) {
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| 116 | var s = nodesV[i];
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| 117 | var t = nodesW[i];
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| 118 | M[s] = t;
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| 119 | M_[t] = s;
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| 120 | }
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| 121 | // var e1 = v.IterateNodesPrefix().GetEnumerator();
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| 122 | // var e2 = w.IterateNodesPrefix().GetEnumerator();
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| 123 | // while (e1.MoveNext() && e2.MoveNext()) {
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| 124 | // M[e1.Current] = e2.Current;
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| 125 | // M_[e2.Current] = e1.Current;
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| 126 | // }
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| 127 | }
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| 128 | }
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| 129 | }
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| 130 | return M;
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| 131 | }
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| 132 |
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| 133 | public static double CalculateDistance(ISymbolicExpressionTree t1, ISymbolicExpressionTree t2, double p = 1, double q = 1, double r = 1) {
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| 134 | var K = Compact(t1, t2);
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| 135 | var M = Mapping(t1, t2, K);
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| 136 | int d = t1.Length - M.Count;
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| 137 | int s = M.Count(x => !Label(x.Key).Equals(Label(x.Value)));
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| 138 | int i = t2.Length - M.Count;
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| 139 |
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| 140 | double distance = s * p + i * q + d * r;
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| 141 |
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| 142 | if (distance / (t1.Length + t2.Length) > 0.5 && M.Count > 0) {
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| 143 | using (var file = new StreamWriter(Path.Combine(Environment.GetFolderPath(Environment.SpecialFolder.MyDocuments), "map.txt"))) {
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| 144 | var str = FormatMapping(t1, t2, M);
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| 145 | file.WriteLine(str);
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| 146 | }
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| 147 | }
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| 148 |
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| 149 | return distance;
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| 150 | }
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| 151 |
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| 152 | private static string Label(ISymbolicExpressionTreeNode n) {
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| 153 | return n.ToString();
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| 154 | }
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| 155 |
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| 156 | private static int Height(IVertex v) {
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| 157 | return (int)Math.Round(v.Weight); // use the vertex weight as height in this particular context
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| 158 | }
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| 159 |
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| 160 | private static int Height(ISymbolicExpressionTreeNode n) {
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| 161 | var p = n;
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| 162 | while (p.Parent != null)
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| 163 | p = p.Parent;
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| 164 | return p.GetBranchLevel(n);
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| 165 | }
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| 166 |
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| 167 | private class DisjointUnion : Tuple<ISymbolicExpressionTree, ISymbolicExpressionTree> {
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| 168 | public DisjointUnion(ISymbolicExpressionTree t1, ISymbolicExpressionTree t2)
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| 169 | : base(t1, t2) {
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| 170 | }
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| 171 |
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| 172 | public IEnumerable<ISymbolicExpressionTreeNode> Nodes {
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[11016] | 173 | get {
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| 174 | var nodes1 = Item1.Root.IterateNodesBreadth().Reverse();
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| 175 | var nodes2 = Item2.Root.IterateNodesBreadth().Reverse();
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| 176 |
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| 177 | return nodes1.Concat(nodes2);
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| 178 |
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| 179 | // var nodes =
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| 180 | // nodes1.Select(n => new { Node = n, Height = Item1.Root.GetBranchLevel(n) })
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| 181 | // .Concat(nodes2.Select(n => new { Node = n, Height = Item2.Root.GetBranchLevel(n) }))
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| 182 | // .OrderByDescending(x => x.Height)
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| 183 | // .Select(x => x.Node);
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| 184 | //
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| 185 | // return nodes;
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| 186 | // // var list = new List<ISymbolicExpressionTreeNode> { Item1.Root, Item2.Root };
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| 187 | // // int i = 0;
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| 188 | // // while (i != list.Count) {
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| 189 | // // var node = list[i];
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| 190 | // // if (node.SubtreeCount > 0) {
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| 191 | // // list.AddRange(node.Subtrees);
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| 192 | // // }
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| 193 | // // ++i;
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| 194 | // // }
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| 195 | // // list.Reverse(); // return nodes in order of decreasing height
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| 196 | // // return list;
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| 197 | }
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[11015] | 198 | }
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| 199 |
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| 200 | public bool IsRoot(ISymbolicExpressionTreeNode n) {
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| 201 | return (n == Item1.Root || n == Item2.Root);
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| 202 | }
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| 203 | }
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| 204 |
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| 205 | // draw the mapping between t1 and t2
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| 206 | private static string FormatMapping(ISymbolicExpressionTree t1, ISymbolicExpressionTree t2, Dictionary<ISymbolicExpressionTreeNode, ISymbolicExpressionTreeNode> map) {
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| 207 | var formatter = new SymbolicExpressionTreeLatexFormatter();
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| 208 | var sb = new StringBuilder();
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| 209 |
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| 210 | string s1, s2;
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| 211 | var m1 = formatter.Format(t1, out s1);
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| 212 | var m2 = formatter.Format(t2, out s2, 20);
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| 213 |
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| 214 | sb.Append(s1);
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| 215 | sb.Append(s2);
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| 216 |
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| 217 | foreach (var p in map) {
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| 218 | var id1 = m1[p.Key];
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| 219 | var id2 = m2[p.Value];
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| 220 |
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| 221 | sb.Append(string.Format(CultureInfo.InvariantCulture, "\\path[draw,->] ({0}) edge[bend left,dashed] ({1});", id1, id2));
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| 222 | }
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| 223 |
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| 224 | return sb.ToString();
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| 225 | }
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| 226 | }
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| 227 | }
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