1 | #region License Information
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2 | /* HeuristicLab
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3 | * Copyright (C) 2002-2010 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.Linq;
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25 | using System.Text;
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26 | using HeuristicLab.Core;
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27 | using HeuristicLab.Data;
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28 | using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding.ArchitectureManipulators;
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29 | using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding.Symbols;
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30 | using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
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31 |
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32 | namespace HeuristicLab.Encodings.SymbolicExpressionTreeEncoding.Creators {
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33 | [StorableClass]
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34 | [Item("ProbabilisticTreeCreator", "An operator that creates new symbolic expression trees with uniformly distributed size")]
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35 | public class ProbabilisticTreeCreator : SymbolicExpressionTreeCreator {
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36 | private const int MAX_TRIES = 100;
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37 |
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38 | public ProbabilisticTreeCreator()
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39 | : base() {
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40 | }
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41 |
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42 | protected override SymbolicExpressionTree Create(
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43 | IRandom random,
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44 | ISymbolicExpressionGrammar grammar,
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45 | IntValue maxTreeSize, IntValue maxTreeHeight,
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46 | IntValue maxFunctionDefinitions, IntValue maxFunctionArguments) {
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47 | return Create(random, grammar, maxTreeSize.Value, maxTreeHeight.Value, maxFunctionDefinitions.Value, maxFunctionArguments.Value);
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48 | }
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49 |
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50 | public static SymbolicExpressionTree Create(IRandom random, ISymbolicExpressionGrammar grammar,
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51 | int maxTreeSize, int maxTreeHeight,
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52 | int maxFunctionDefinitions, int maxFunctionArguments
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53 | ) {
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54 | SymbolicExpressionTree tree = new SymbolicExpressionTree();
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55 | var rootNode = (SymbolicExpressionTreeTopLevelNode)grammar.StartSymbol.CreateTreeNode();
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56 | if (rootNode.HasLocalParameters) rootNode.ResetLocalParameters(random);
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57 | rootNode.SetGrammar(new SymbolicExpressionTreeGrammar(grammar));
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58 | tree.Root = PTC2(random, rootNode, maxTreeSize, maxTreeHeight, maxFunctionDefinitions, maxFunctionArguments);
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59 | return tree;
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60 | }
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61 |
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62 | private class TreeExtensionPoint {
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63 | public SymbolicExpressionTreeNode Parent { get; set; }
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64 | public int ChildIndex { get; set; }
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65 | public int ExtensionPointDepth { get; set; }
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66 | }
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67 |
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68 | public static SymbolicExpressionTreeNode PTC2(IRandom random, SymbolicExpressionTreeNode seedNode,
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69 | int maxTreeSize, int maxDepth, int maxFunctionDefinitions, int maxFunctionArguments) {
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70 | // tree size is limited by the grammar and by the explicit size constraints
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71 | int allowedMinSize = seedNode.Grammar.GetMinExpressionLength(seedNode.Symbol);
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72 | int allowedMaxSize = Math.Min(maxTreeSize, seedNode.Grammar.GetMaxExpressionLength(seedNode.Symbol));
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73 | int tries = 0;
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74 | while (tries++ < MAX_TRIES) {
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75 | // select a target tree size uniformly in the possible range (as determined by explicit limits and limits of the grammar)
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76 | int treeSize = random.Next(allowedMinSize, allowedMaxSize + 1);
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77 | if (treeSize <= 1 || maxDepth <= 1) return seedNode;
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78 |
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79 | bool success = CreateFullTreeFromSeed(random, seedNode, seedNode.Grammar, treeSize, maxDepth, maxFunctionDefinitions, maxFunctionArguments);
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80 |
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81 | // if successful => check constraints and return the tree if everything looks ok
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82 | if (success && seedNode.GetSize() <= maxTreeSize && seedNode.GetHeight() <= maxDepth) {
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83 | return seedNode;
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84 | } else {
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85 | // clean seedNode
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86 | while (seedNode.SubTrees.Count > 0) seedNode.RemoveSubTree(0);
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87 | }
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88 | // try a different size MAX_TRIES times
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89 | }
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90 | throw new ArgumentException("Couldn't create a random valid tree.");
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91 | }
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92 |
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93 | private static bool CreateFullTreeFromSeed(IRandom random, SymbolicExpressionTreeNode root, ISymbolicExpressionGrammar globalGrammar,
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94 | int size, int maxDepth, int maxFunctionDefinitions, int maxFunctionArguments) {
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95 | try {
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96 | TryCreateFullTreeFromSeed(random, root, globalGrammar, size, maxDepth, maxFunctionDefinitions, maxFunctionArguments);
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97 | return true;
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98 | }
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99 | catch (ArgumentException) { return false; }
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100 | }
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101 |
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102 | private static void TryCreateFullTreeFromSeed(IRandom random, SymbolicExpressionTreeNode root, ISymbolicExpressionGrammar globalGrammar,
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103 | int size, int maxDepth, int maxFunctionDefinitions, int maxFunctionArguments) {
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104 | List<TreeExtensionPoint> extensionPoints = new List<TreeExtensionPoint>();
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105 | int currentSize = 1;
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106 | int totalListMinSize = globalGrammar.GetMinExpressionLength(root.Symbol) - 1;
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107 | int actualArity = SampleArity(random, root, size);
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108 | for (int i = 0; i < actualArity; i++) {
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109 | // insert a dummy sub-tree and add the pending extension to the list
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110 | var dummy = new SymbolicExpressionTreeNode();
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111 | root.AddSubTree(dummy);
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112 | extensionPoints.Add(new TreeExtensionPoint { Parent = root, ChildIndex = i, ExtensionPointDepth = 0 });
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113 | }
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114 | // while there are pending extension points and we have not reached the limit of adding new extension points
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115 | while (extensionPoints.Count > 0 && totalListMinSize + currentSize < size) {
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116 | int randomIndex = random.Next(extensionPoints.Count);
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117 | TreeExtensionPoint nextExtension = extensionPoints[randomIndex];
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118 | extensionPoints.RemoveAt(randomIndex);
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119 | SymbolicExpressionTreeNode parent = nextExtension.Parent;
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120 | int argumentIndex = nextExtension.ChildIndex;
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121 | int extensionDepth = nextExtension.ExtensionPointDepth;
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122 | if (extensionDepth + parent.Grammar.GetMinExpressionDepth(parent.Symbol) >= maxDepth) {
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123 | ReplaceWithMinimalTree(random, root, parent, argumentIndex, maxFunctionDefinitions, maxFunctionArguments);
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124 | } else {
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125 | var allowedSymbols = from s in parent.Grammar.Symbols
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126 | where parent.Grammar.IsAllowedChild(parent.Symbol, s, argumentIndex)
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127 | where parent.Grammar.GetMinExpressionDepth(s) + extensionDepth - 1 < maxDepth
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128 | where parent.Grammar.GetMaxExpressionLength(s) > size - totalListMinSize - currentSize
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129 | select s;
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130 | Symbol selectedSymbol = SelectRandomSymbol(random, allowedSymbols);
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131 | SymbolicExpressionTreeNode newTree = selectedSymbol.CreateTreeNode();
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132 | if (newTree.HasLocalParameters) newTree.ResetLocalParameters(random);
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133 | parent.RemoveSubTree(argumentIndex);
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134 | parent.InsertSubTree(argumentIndex, newTree);
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135 |
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136 | InitializeNewTreeNode(random, root, newTree, maxFunctionDefinitions, maxFunctionArguments);
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137 |
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138 | currentSize++;
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139 | totalListMinSize--;
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140 |
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141 | actualArity = SampleArity(random, newTree, size - currentSize);
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142 | for (int i = 0; i < actualArity; i++) {
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143 | // insert a dummy sub-tree and add the pending extension to the list
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144 | var dummy = new SymbolicExpressionTreeNode();
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145 | newTree.AddSubTree(dummy);
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146 | extensionPoints.Add(new TreeExtensionPoint { Parent = newTree, ChildIndex = i, ExtensionPointDepth = extensionDepth + 1 });
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147 | }
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148 | totalListMinSize += newTree.Grammar.GetMinExpressionLength(newTree.Symbol);
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149 | }
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150 | }
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151 | // fill all pending extension points
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152 | while (extensionPoints.Count > 0) {
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153 | int randomIndex = random.Next(extensionPoints.Count);
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154 | TreeExtensionPoint nextExtension = extensionPoints[randomIndex];
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155 | extensionPoints.RemoveAt(randomIndex);
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156 | SymbolicExpressionTreeNode parent = nextExtension.Parent;
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157 | int a = nextExtension.ChildIndex;
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158 | int d = nextExtension.ExtensionPointDepth;
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159 | ReplaceWithMinimalTree(random, root, parent, a, maxFunctionDefinitions, maxFunctionArguments);
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160 | }
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161 | }
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162 |
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163 | private static void ReplaceWithMinimalTree(IRandom random, SymbolicExpressionTreeNode root, SymbolicExpressionTreeNode parent, int argumentIndex, int maxFunctionDefinitions, int maxFunctionArguments) {
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164 | // determine possible symbols that will lead to the smallest possible tree
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165 | var possibleSymbols = (from s in parent.GetAllowedSymbols(argumentIndex)
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166 | group s by parent.Grammar.GetMinExpressionLength(s) into g
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167 | orderby g.Key
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168 | select g).First();
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169 | var selectedSymbol = SelectRandomSymbol(random, possibleSymbols);
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170 | var tree = selectedSymbol.CreateTreeNode();
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171 | if (tree.HasLocalParameters) tree.ResetLocalParameters(random);
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172 | parent.RemoveSubTree(argumentIndex);
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173 | parent.InsertSubTree(argumentIndex, tree);
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174 | InitializeNewTreeNode(random, root, tree, maxFunctionDefinitions, maxFunctionArguments);
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175 | for (int i = 0; i < tree.GetMinSubtreeCount(); i++) {
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176 | // insert a dummy sub-tree and add the pending extension to the list
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177 | var dummy = new SymbolicExpressionTreeNode();
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178 | tree.AddSubTree(dummy);
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179 | // replace the just inserted dummy by recursive application
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180 | ReplaceWithMinimalTree(random, root, tree, i, maxFunctionDefinitions, maxFunctionArguments);
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181 | }
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182 | }
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183 |
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184 | private static void InitializeNewTreeNode(IRandom random, SymbolicExpressionTreeNode root, SymbolicExpressionTreeNode newTree, int maxFunctionDefinitions, int maxFunctionArguments) {
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185 | // NB it is assumed that defuns are only allowed as children of root and nowhere else
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186 | // also assumes that newTree is already attached to root somewhere
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187 | if (IsTopLevelBranch(root, newTree)) {
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188 | ((SymbolicExpressionTreeTopLevelNode)newTree).SetGrammar((ISymbolicExpressionGrammar)root.Grammar.Clone());
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189 |
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190 | // allow invokes of existing ADFs with higher index
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191 | int argIndex = root.SubTrees.IndexOf(newTree);
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192 | for (int i = argIndex + 1; i < root.SubTrees.Count; i++) {
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193 | var otherDefunNode = root.SubTrees[i] as DefunTreeNode;
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194 | if (otherDefunNode != null) {
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195 | GrammarModifier.AddDynamicSymbol(newTree.Grammar, newTree.Symbol, otherDefunNode.FunctionName, otherDefunNode.NumberOfArguments);
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196 | }
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197 | }
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198 | }
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199 | if (newTree.Symbol is Defun) {
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200 | var defunTree = newTree as DefunTreeNode;
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201 | string formatString = new StringBuilder().Append('0', (int)Math.Log10(maxFunctionDefinitions * 10 - 1)).ToString(); // >= 100 functions => ###
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202 | var allowedNames = from index in Enumerable.Range(0, maxFunctionDefinitions)
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203 | select "ADF" + index.ToString(formatString);
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204 | var takenNames = (from node in root.IterateNodesPrefix().OfType<DefunTreeNode>()
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205 | select node.FunctionName).Distinct();
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206 | var remainingNames = allowedNames.Except(takenNames).ToList();
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207 | string functionName = remainingNames[random.Next(remainingNames.Count)];
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208 | // set name and number of arguments of the ADF
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209 | int nArgs = random.Next(maxFunctionArguments);
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210 | defunTree.FunctionName = functionName;
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211 | defunTree.NumberOfArguments = nArgs;
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212 | if (nArgs > 0) {
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213 | GrammarModifier.AddDynamicArguments(defunTree.Grammar, defunTree.Symbol, Enumerable.Range(0, nArgs));
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214 | }
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215 | // in existing branches with smaller index allow invoke of current function
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216 | int argIndex = root.SubTrees.IndexOf(newTree);
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217 | for (int i = 0; i < argIndex; i++) {
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218 | // if not dummy node
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219 | if (root.SubTrees[i].Symbol != null) {
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220 | var existingBranch = root.SubTrees[i];
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221 | GrammarModifier.AddDynamicSymbol(existingBranch.Grammar, existingBranch.Symbol, functionName, nArgs);
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222 | }
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223 | }
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224 | }
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225 | }
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226 |
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227 | private static bool IsTopLevelBranch(SymbolicExpressionTreeNode root, SymbolicExpressionTreeNode branch) {
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228 | return branch is SymbolicExpressionTreeTopLevelNode;
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229 | }
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230 |
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231 | private static Symbol SelectRandomSymbol(IRandom random, IEnumerable<Symbol> symbols) {
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232 | var symbolList = symbols.ToList();
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233 | var ticketsSum = symbolList.Select(x => x.InitialFrequency).Sum();
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234 | if (ticketsSum == 0.0) throw new ArgumentException("The initial frequency of all allowed symbols is zero.");
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235 | var r = random.NextDouble() * ticketsSum;
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236 | double aggregatedTickets = 0;
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237 | for (int i = 0; i < symbolList.Count; i++) {
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238 | aggregatedTickets += symbolList[i].InitialFrequency;
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239 | if (aggregatedTickets > r) {
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240 | return symbolList[i];
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241 | }
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242 | }
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243 | // this should never happen
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244 | throw new ArgumentException("There is a problem with the initial frequency setting of allowed symbols.");
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245 | }
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246 |
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247 | private static int SampleArity(IRandom random, SymbolicExpressionTreeNode node, int targetSize) {
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248 | // select actualArity randomly with the constraint that the sub-trees in the minimal arity can become large enough
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249 | int minArity = node.GetMinSubtreeCount();
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250 | int maxArity = node.GetMaxSubtreeCount();
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251 | if (maxArity > targetSize) {
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252 | maxArity = targetSize;
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253 | }
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254 | // the min number of sub-trees has to be set to a value that is large enough so that the largest possible tree is at least tree size
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255 | // if 1..3 trees are possible and the largest possible first sub-tree is smaller larger than the target size then minArity should be at least 2
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256 | long aggregatedLongestExpressionLength = 0;
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257 | for (int i = 0; i < maxArity; i++) {
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258 | aggregatedLongestExpressionLength += (from s in node.GetAllowedSymbols(i)
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259 | select node.Grammar.GetMaxExpressionLength(s)).Max();
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260 | if (aggregatedLongestExpressionLength < targetSize) minArity = i;
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261 | else break;
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262 | }
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263 |
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264 | // the max number of sub-trees has to be set to a value that is small enough so that the smallest possible tree is at most tree size
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265 | // if 1..3 trees are possible and the smallest possible first sub-tree is already larger than the target size then maxArity should be at most 0
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266 | long aggregatedShortestExpressionLength = 0;
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267 | for (int i = 0; i < maxArity; i++) {
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268 | aggregatedShortestExpressionLength += (from s in node.GetAllowedSymbols(i)
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269 | select node.Grammar.GetMinExpressionLength(s)).Min();
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270 | if (aggregatedShortestExpressionLength > targetSize) {
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271 | maxArity = i;
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272 | break;
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273 | }
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274 | }
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275 | if (minArity > maxArity) throw new ArgumentException();
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276 | return random.Next(minArity, maxArity + 1);
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277 | }
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278 | }
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279 | } |
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