1 | #region License Information
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2 | /* HeuristicLab
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3 | * Copyright (C) 2002-2012 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 HeuristicLab.Common;
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26 | using HeuristicLab.Core;
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27 | using HeuristicLab.Data;
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28 | using HeuristicLab.Parameters;
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29 | using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
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30 | using HeuristicLab.PluginInfrastructure;
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31 |
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32 | namespace HeuristicLab.Encodings.SymbolicExpressionTreeEncoding {
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33 | [NonDiscoverableType]
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34 | [StorableClass]
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35 | [Item("ProbabilisticTreeCreator", "An operator that creates new symbolic expression trees with uniformly distributed length")]
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36 | public class ProbabilisticTreeCreator : SymbolicExpressionTreeCreator,
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37 | ISymbolicExpressionTreeSizeConstraintOperator, ISymbolicExpressionTreeGrammarBasedOperator {
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38 | private const int MAX_TRIES = 100;
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39 | private const string MaximumSymbolicExpressionTreeLengthParameterName = "MaximumSymbolicExpressionTreeLength";
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40 | private const string MaximumSymbolicExpressionTreeDepthParameterName = "MaximumSymbolicExpressionTreeDepth";
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41 | private const string SymbolicExpressionTreeGrammarParameterName = "SymbolicExpressionTreeGrammar";
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42 | private const string ClonedSymbolicExpressionTreeGrammarParameterName = "ClonedSymbolicExpressionTreeGrammar";
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43 | #region Parameter Properties
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44 | public IValueLookupParameter<IntValue> MaximumSymbolicExpressionTreeLengthParameter {
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45 | get { return (IValueLookupParameter<IntValue>)Parameters[MaximumSymbolicExpressionTreeLengthParameterName]; }
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46 | }
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47 | public IValueLookupParameter<IntValue> MaximumSymbolicExpressionTreeDepthParameter {
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48 | get { return (IValueLookupParameter<IntValue>)Parameters[MaximumSymbolicExpressionTreeDepthParameterName]; }
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49 | }
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50 | public IValueLookupParameter<ISymbolicExpressionGrammar> SymbolicExpressionTreeGrammarParameter {
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51 | get { return (IValueLookupParameter<ISymbolicExpressionGrammar>)Parameters[SymbolicExpressionTreeGrammarParameterName]; }
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52 | }
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53 | public ILookupParameter<ISymbolicExpressionGrammar> ClonedSymbolicExpressionTreeGrammarParameter {
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54 | get { return (ILookupParameter<ISymbolicExpressionGrammar>)Parameters[ClonedSymbolicExpressionTreeGrammarParameterName]; }
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55 | }
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56 | #endregion
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57 | #region Properties
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58 | public IntValue MaximumSymbolicExpressionTreeLength {
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59 | get { return MaximumSymbolicExpressionTreeLengthParameter.ActualValue; }
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60 | }
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61 | public IntValue MaximumSymbolicExpressionTreeDepth {
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62 | get { return MaximumSymbolicExpressionTreeDepthParameter.ActualValue; }
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63 | }
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64 | public ISymbolicExpressionGrammar SymbolicExpressionTreeGrammar {
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65 | get { return ClonedSymbolicExpressionTreeGrammarParameter.ActualValue; }
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66 | }
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67 | #endregion
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68 |
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69 | [StorableConstructor]
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70 | protected ProbabilisticTreeCreator(bool deserializing) : base(deserializing) { }
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71 | protected ProbabilisticTreeCreator(ProbabilisticTreeCreator original, Cloner cloner) : base(original, cloner) { }
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72 | public ProbabilisticTreeCreator()
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73 | : base() {
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74 | Parameters.Add(new ValueLookupParameter<IntValue>(MaximumSymbolicExpressionTreeLengthParameterName, "The maximal length (number of nodes) of the symbolic expression tree."));
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75 | Parameters.Add(new ValueLookupParameter<IntValue>(MaximumSymbolicExpressionTreeDepthParameterName, "The maximal depth of the symbolic expression tree (a tree with one node has depth = 0)."));
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76 | Parameters.Add(new ValueLookupParameter<ISymbolicExpressionGrammar>(SymbolicExpressionTreeGrammarParameterName, "The tree grammar that defines the correct syntax of symbolic expression trees that should be created."));
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77 | Parameters.Add(new LookupParameter<ISymbolicExpressionGrammar>(ClonedSymbolicExpressionTreeGrammarParameterName, "An immutable clone of the concrete grammar that is actually used to create and manipulate trees."));
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78 | }
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79 |
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80 | public override IDeepCloneable Clone(Cloner cloner) {
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81 | return new ProbabilisticTreeCreator(this, cloner);
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82 | }
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83 | [StorableHook(HookType.AfterDeserialization)]
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84 | private void AfterDeserialization() {
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85 | if (!Parameters.ContainsKey(ClonedSymbolicExpressionTreeGrammarParameterName))
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86 | Parameters.Add(new LookupParameter<ISymbolicExpressionGrammar>(ClonedSymbolicExpressionTreeGrammarParameterName, "An immutable clone of the concrete grammar that is actually used to create and manipulate trees."));
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87 | }
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88 |
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89 | public override IOperation Apply() {
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90 | if (ClonedSymbolicExpressionTreeGrammarParameter.ActualValue == null) {
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91 | SymbolicExpressionTreeGrammarParameter.ActualValue.ReadOnly = true;
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92 | IScope globalScope = ExecutionContext.Scope;
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93 | while (globalScope.Parent != null)
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94 | globalScope = globalScope.Parent;
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95 |
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96 | globalScope.Variables.Add(new Variable(ClonedSymbolicExpressionTreeGrammarParameterName, (ISymbolicExpressionGrammar)SymbolicExpressionTreeGrammarParameter.ActualValue.Clone()));
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97 | }
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98 | return base.Apply();
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99 | }
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100 |
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101 | protected override ISymbolicExpressionTree Create(IRandom random) {
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102 | return Create(random, SymbolicExpressionTreeGrammar, MaximumSymbolicExpressionTreeLength.Value, MaximumSymbolicExpressionTreeDepth.Value);
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103 | }
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104 |
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105 | public override ISymbolicExpressionTree CreateTree(IRandom random, ISymbolicExpressionGrammar grammar, int maxTreeLength, int maxTreeDepth) {
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106 | return Create(random, grammar, maxTreeLength, maxTreeDepth);
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107 | }
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108 |
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109 | public static ISymbolicExpressionTree Create(IRandom random, ISymbolicExpressionGrammar grammar, int maxTreeLength, int maxTreeDepth) {
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110 | SymbolicExpressionTree tree = new SymbolicExpressionTree();
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111 | var rootNode = (SymbolicExpressionTreeTopLevelNode)grammar.ProgramRootSymbol.CreateTreeNode();
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112 | if (rootNode.HasLocalParameters) rootNode.ResetLocalParameters(random);
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113 | rootNode.SetGrammar(new SymbolicExpressionTreeGrammar(grammar));
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114 | var startNode = (SymbolicExpressionTreeTopLevelNode)grammar.StartSymbol.CreateTreeNode();
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115 | startNode.SetGrammar(new SymbolicExpressionTreeGrammar(grammar));
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116 | if (startNode.HasLocalParameters) startNode.ResetLocalParameters(random);
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117 | rootNode.AddSubtree(startNode);
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118 | PTC2(random, startNode, maxTreeLength, maxTreeDepth);
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119 | tree.Root = rootNode;
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120 | return tree;
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121 | }
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122 |
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123 | private class TreeExtensionPoint {
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124 | public ISymbolicExpressionTreeNode Parent { get; set; }
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125 | public int ChildIndex { get; set; }
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126 | public int ExtensionPointDepth { get; set; }
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127 | public int MaximumExtensionLength { get; set; }
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128 | public int MinimumExtensionLength { get; set; }
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129 | }
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130 |
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131 | public static void PTC2(IRandom random, ISymbolicExpressionTreeNode seedNode,
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132 | int maxLength, int maxDepth) {
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133 | // make sure it is possible to create a trees smaller than maxLength and maxDepth
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134 | if (seedNode.Grammar.GetMinimumExpressionLength(seedNode.Symbol) > maxLength)
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135 | throw new ArgumentException("Cannot create trees of length " + maxLength + " or shorter because of grammar constraints.", "maxLength");
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136 | if (seedNode.Grammar.GetMinimumExpressionDepth(seedNode.Symbol) > maxDepth)
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137 | throw new ArgumentException("Cannot create trees of depth " + maxDepth + " or smaller because of grammar constraints.", "maxDepth");
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138 |
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139 | // tree length is limited by the grammar and by the explicit size constraints
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140 | int allowedMinLength = seedNode.Grammar.GetMinimumExpressionLength(seedNode.Symbol);
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141 | int allowedMaxLength = Math.Min(maxLength, seedNode.Grammar.GetMaximumExpressionLength(seedNode.Symbol, maxDepth));
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142 | int tries = 0;
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143 | while (tries++ < MAX_TRIES) {
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144 | // select a target tree length uniformly in the possible range (as determined by explicit limits and limits of the grammar)
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145 | int targetTreeLength;
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146 | targetTreeLength = random.Next(allowedMinLength, allowedMaxLength + 1);
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147 | if (targetTreeLength <= 1 || maxDepth <= 1) return;
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148 |
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149 | bool success = TryCreateFullTreeFromSeed(random, seedNode, targetTreeLength - 1, maxDepth - 1);
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150 |
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151 | // if successful => check constraints and return the tree if everything looks ok
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152 | if (success && seedNode.GetLength() <= maxLength && seedNode.GetDepth() <= maxDepth) {
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153 | return;
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154 | } else {
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155 | // clean seedNode
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156 | while (seedNode.Subtrees.Count() > 0) seedNode.RemoveSubtree(0);
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157 | }
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158 | // try a different length MAX_TRIES times
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159 | }
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160 | throw new ArgumentException("Couldn't create a random valid tree.");
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161 | }
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162 |
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163 | private static bool TryCreateFullTreeFromSeed(IRandom random, ISymbolicExpressionTreeNode root,
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164 | int targetLength, int maxDepth) {
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165 | List<TreeExtensionPoint> extensionPoints = new List<TreeExtensionPoint>();
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166 | int currentLength = 0;
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167 | int actualArity = SampleArity(random, root, targetLength, maxDepth);
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168 | if (actualArity < 0) return false;
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169 |
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170 | for (int i = 0; i < actualArity; i++) {
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171 | // insert a dummy sub-tree and add the pending extension to the list
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172 | var dummy = new SymbolicExpressionTreeNode();
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173 | root.AddSubtree(dummy);
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174 | var x = new TreeExtensionPoint { Parent = root, ChildIndex = i, ExtensionPointDepth = 0 };
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175 | FillExtensionLengths(x, maxDepth);
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176 | extensionPoints.Add(x);
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177 | }
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178 | //necessary to use long data type as the extension point length could be int.MaxValue
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179 | long minExtensionPointsLength = extensionPoints.Select(x => (long)x.MinimumExtensionLength).Sum();
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180 | long maxExtensionPointsLength = extensionPoints.Select(x => (long)x.MaximumExtensionLength).Sum();
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181 |
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182 | // while there are pending extension points and we have not reached the limit of adding new extension points
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183 | while (extensionPoints.Count > 0 && minExtensionPointsLength + currentLength <= targetLength) {
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184 | int randomIndex = random.Next(extensionPoints.Count);
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185 | TreeExtensionPoint nextExtension = extensionPoints[randomIndex];
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186 | extensionPoints.RemoveAt(randomIndex);
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187 | ISymbolicExpressionTreeNode parent = nextExtension.Parent;
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188 | int argumentIndex = nextExtension.ChildIndex;
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189 | int extensionDepth = nextExtension.ExtensionPointDepth;
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190 |
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191 | if (parent.Grammar.GetMinimumExpressionDepth(parent.Symbol) > maxDepth - extensionDepth) {
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192 | ReplaceWithMinimalTree(random, root, parent, argumentIndex);
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193 | int insertedTreeLength = parent.GetSubtree(argumentIndex).GetLength();
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194 | currentLength += insertedTreeLength;
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195 | minExtensionPointsLength -= insertedTreeLength;
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196 | maxExtensionPointsLength -= insertedTreeLength;
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197 | } else {
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198 | //remove currently chosen extension point from calculation
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199 | minExtensionPointsLength -= nextExtension.MinimumExtensionLength;
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200 | maxExtensionPointsLength -= nextExtension.MaximumExtensionLength;
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201 |
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202 | var symbols = from s in parent.Grammar.GetAllowedChildSymbols(parent.Symbol, argumentIndex)
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203 | where s.InitialFrequency > 0.0
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204 | where parent.Grammar.GetMinimumExpressionDepth(s) <= maxDepth - extensionDepth
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205 | where parent.Grammar.GetMinimumExpressionLength(s) <= targetLength - currentLength - minExtensionPointsLength
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206 | select s;
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207 | if (maxExtensionPointsLength < targetLength - currentLength)
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208 | symbols = from s in symbols
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209 | where parent.Grammar.GetMaximumExpressionLength(s, maxDepth - extensionDepth) >= targetLength - currentLength - maxExtensionPointsLength
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210 | select s;
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211 | var allowedSymbols = symbols.ToList();
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212 |
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213 | if (allowedSymbols.Count == 0) return false;
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214 | var weights = allowedSymbols.Select(x => x.InitialFrequency).ToList();
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215 | var selectedSymbol = allowedSymbols.SelectRandom(weights, random);
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216 | ISymbolicExpressionTreeNode newTree = selectedSymbol.CreateTreeNode();
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217 | if (newTree.HasLocalParameters) newTree.ResetLocalParameters(random);
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218 | parent.RemoveSubtree(argumentIndex);
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219 | parent.InsertSubtree(argumentIndex, newTree);
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220 |
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221 | var topLevelNode = newTree as SymbolicExpressionTreeTopLevelNode;
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222 | if (topLevelNode != null)
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223 | topLevelNode.SetGrammar((ISymbolicExpressionTreeGrammar)root.Grammar.Clone());
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224 |
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225 | currentLength++;
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226 | actualArity = SampleArity(random, newTree, targetLength - currentLength, maxDepth - extensionDepth);
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227 | if (actualArity < 0) return false;
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228 | for (int i = 0; i < actualArity; i++) {
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229 | // insert a dummy sub-tree and add the pending extension to the list
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230 | var dummy = new SymbolicExpressionTreeNode();
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231 | newTree.AddSubtree(dummy);
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232 | var x = new TreeExtensionPoint { Parent = newTree, ChildIndex = i, ExtensionPointDepth = extensionDepth + 1 };
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233 | FillExtensionLengths(x, maxDepth);
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234 | extensionPoints.Add(x);
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235 | maxExtensionPointsLength += x.MaximumExtensionLength;
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236 | minExtensionPointsLength += x.MinimumExtensionLength;
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237 | }
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238 | }
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239 | }
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240 | // fill all pending extension points
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241 | while (extensionPoints.Count > 0) {
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242 | int randomIndex = random.Next(extensionPoints.Count);
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243 | TreeExtensionPoint nextExtension = extensionPoints[randomIndex];
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244 | extensionPoints.RemoveAt(randomIndex);
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245 | ISymbolicExpressionTreeNode parent = nextExtension.Parent;
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246 | int a = nextExtension.ChildIndex;
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247 | ReplaceWithMinimalTree(random, root, parent, a);
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248 | }
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249 | return true;
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250 | }
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251 |
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252 | private static void ReplaceWithMinimalTree(IRandom random, ISymbolicExpressionTreeNode root, ISymbolicExpressionTreeNode parent,
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253 | int childIndex) {
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254 | // determine possible symbols that will lead to the smallest possible tree
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255 | var possibleSymbols = (from s in parent.Grammar.GetAllowedChildSymbols(parent.Symbol, childIndex)
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256 | where s.InitialFrequency > 0.0
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257 | group s by parent.Grammar.GetMinimumExpressionLength(s) into g
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258 | orderby g.Key
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259 | select g).First().ToList();
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260 | var weights = possibleSymbols.Select(x => x.InitialFrequency).ToList();
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261 | var selectedSymbol = possibleSymbols.SelectRandom(weights, random);
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262 | var tree = selectedSymbol.CreateTreeNode();
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263 | if (tree.HasLocalParameters) tree.ResetLocalParameters(random);
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264 | parent.RemoveSubtree(childIndex);
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265 | parent.InsertSubtree(childIndex, tree);
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266 |
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267 | var topLevelNode = tree as SymbolicExpressionTreeTopLevelNode;
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268 | if (topLevelNode != null)
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269 | topLevelNode.SetGrammar((ISymbolicExpressionTreeGrammar)root.Grammar.Clone());
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270 |
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271 | for (int i = 0; i < tree.Grammar.GetMinimumSubtreeCount(tree.Symbol); i++) {
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272 | // insert a dummy sub-tree and add the pending extension to the list
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273 | var dummy = new SymbolicExpressionTreeNode();
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274 | tree.AddSubtree(dummy);
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275 | // replace the just inserted dummy by recursive application
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276 | ReplaceWithMinimalTree(random, root, tree, i);
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277 | }
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278 | }
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279 |
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280 | private static void FillExtensionLengths(TreeExtensionPoint extension, int maxDepth) {
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281 | var grammar = extension.Parent.Grammar;
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282 | int maxLength = int.MinValue;
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283 | int minLength = int.MaxValue;
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284 | foreach (ISymbol s in grammar.GetAllowedChildSymbols(extension.Parent.Symbol, extension.ChildIndex)) {
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285 | if (s.InitialFrequency > 0.0) {
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286 | int max = grammar.GetMaximumExpressionLength(s, maxDepth - extension.ExtensionPointDepth);
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287 | maxLength = Math.Max(maxLength, max);
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288 | int min = grammar.GetMinimumExpressionLength(s);
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289 | minLength = Math.Min(minLength, min);
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290 | }
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291 | }
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292 |
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293 | extension.MaximumExtensionLength = maxLength;
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294 | extension.MinimumExtensionLength = minLength;
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295 | }
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296 |
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297 | private static int SampleArity(IRandom random, ISymbolicExpressionTreeNode node, int targetLength, int maxDepth) {
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298 | // select actualArity randomly with the constraint that the sub-trees in the minimal arity can become large enough
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299 | int minArity = node.Grammar.GetMinimumSubtreeCount(node.Symbol);
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300 | int maxArity = node.Grammar.GetMaximumSubtreeCount(node.Symbol);
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301 | if (maxArity > targetLength) {
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302 | maxArity = targetLength;
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303 | }
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304 | if (minArity == maxArity) return minArity;
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305 |
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306 | // 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 length
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307 | // if 1..3 trees are possible and the largest possible first sub-tree is smaller larger than the target length then minArity should be at least 2
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308 | long aggregatedLongestExpressionLength = 0;
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309 | for (int i = 0; i < maxArity; i++) {
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310 | aggregatedLongestExpressionLength += (from s in node.Grammar.GetAllowedChildSymbols(node.Symbol, i)
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311 | where s.InitialFrequency > 0.0
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312 | select node.Grammar.GetMaximumExpressionLength(s, maxDepth)).Max();
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313 | if (i > minArity && aggregatedLongestExpressionLength < targetLength) minArity = i + 1;
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314 | else break;
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315 | }
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316 |
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317 | // 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 length
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318 | // if 1..3 trees are possible and the smallest possible first sub-tree is already larger than the target length then maxArity should be at most 0
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319 | long aggregatedShortestExpressionLength = 0;
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320 | for (int i = 0; i < maxArity; i++) {
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321 | aggregatedShortestExpressionLength += (from s in node.Grammar.GetAllowedChildSymbols(node.Symbol, i)
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322 | where s.InitialFrequency > 0.0
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323 | select node.Grammar.GetMinimumExpressionLength(s)).Min();
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324 | if (aggregatedShortestExpressionLength > targetLength) {
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325 | maxArity = i;
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326 | break;
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327 | }
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328 | }
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329 | if (minArity > maxArity) return -1;
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330 | return random.Next(minArity, maxArity + 1);
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331 | }
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332 |
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333 | }
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334 | } |
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