[645] | 1 | #region License Information
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| 2 | /* HeuristicLab
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[5445] | 3 | * Copyright (C) 2002-2011 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
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[645] | 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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[3462] | 22 | using System;
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[4068] | 23 | using System.Collections.Generic;
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[3462] | 24 | using System.Linq;
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[4722] | 25 | using HeuristicLab.Common;
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[645] | 26 | using HeuristicLab.Core;
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| 27 | using HeuristicLab.Data;
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[5521] | 28 | using HeuristicLab.Parameters;
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[4068] | 29 | using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
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[645] | 30 |
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[5499] | 31 | namespace HeuristicLab.Encodings.SymbolicExpressionTreeEncoding {
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[3223] | 32 | [StorableClass]
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[5549] | 33 | [Item("ProbabilisticTreeCreator", "An operator that creates new symbolic expression trees with uniformly distributed length")]
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[5618] | 34 | public class ProbabilisticTreeCreator : SymbolicExpressionTreeCreator,
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[5686] | 35 | ISymbolicExpressionTreeSizeConstraintOperator, ISymbolicExpressionTreeGrammarBasedOperator {
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[3369] | 36 | private const int MAX_TRIES = 100;
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[5499] | 37 | private const string MaximumSymbolicExpressionTreeLengthParameterName = "MaximumSymbolicExpressionTreeLength";
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| 38 | private const string MaximumSymbolicExpressionTreeDepthParameterName = "MaximumSymbolicExpressionTreeDepth";
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| 39 | private const string SymbolicExpressionTreeGrammarParameterName = "SymbolicExpressionTreeGrammar";
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| 40 | #region Parameter Properties
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| 41 | public IValueLookupParameter<IntValue> MaximumSymbolicExpressionTreeLengthParameter {
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| 42 | get { return (IValueLookupParameter<IntValue>)Parameters[MaximumSymbolicExpressionTreeLengthParameterName]; }
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| 43 | }
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| 44 | public IValueLookupParameter<IntValue> MaximumSymbolicExpressionTreeDepthParameter {
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| 45 | get { return (IValueLookupParameter<IntValue>)Parameters[MaximumSymbolicExpressionTreeDepthParameterName]; }
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| 46 | }
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[5686] | 47 | public IValueLookupParameter<ISymbolicExpressionGrammar> SymbolicExpressionTreeGrammarParameter {
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| 48 | get { return (IValueLookupParameter<ISymbolicExpressionGrammar>)Parameters[SymbolicExpressionTreeGrammarParameterName]; }
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[5499] | 49 | }
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| 50 | #endregion
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| 51 | #region Properties
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| 52 | public IntValue MaximumSymbolicExpressionTreeLength {
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| 53 | get { return MaximumSymbolicExpressionTreeLengthParameter.ActualValue; }
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| 54 | }
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| 55 | public IntValue MaximumSymbolicExpressionTreeDepth {
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| 56 | get { return MaximumSymbolicExpressionTreeDepthParameter.ActualValue; }
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| 57 | }
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[5686] | 58 | public ISymbolicExpressionGrammar SymbolicExpressionTreeGrammar {
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[5499] | 59 | get { return SymbolicExpressionTreeGrammarParameter.ActualValue; }
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| 60 | }
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| 61 | #endregion
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| 62 |
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[4722] | 63 | [StorableConstructor]
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[5618] | 64 | protected ProbabilisticTreeCreator(bool deserializing) : base(deserializing) { }
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| 65 | protected ProbabilisticTreeCreator(ProbabilisticTreeCreator original, Cloner cloner) : base(original, cloner) { }
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[5499] | 66 | public ProbabilisticTreeCreator()
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| 67 | : base() {
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| 68 | Parameters.Add(new ValueLookupParameter<IntValue>(MaximumSymbolicExpressionTreeLengthParameterName, "The maximal length (number of nodes) of the symbolic expression tree."));
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| 69 | 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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[5686] | 70 | 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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[5499] | 71 | }
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[3338] | 72 |
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[4722] | 73 | public override IDeepCloneable Clone(Cloner cloner) {
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| 74 | return new ProbabilisticTreeCreator(this, cloner);
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[645] | 75 | }
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| 76 |
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[5510] | 77 | protected override ISymbolicExpressionTree Create(IRandom random) {
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[5686] | 78 | return Create(random, SymbolicExpressionTreeGrammar, MaximumSymbolicExpressionTreeLength.Value, MaximumSymbolicExpressionTreeDepth.Value);
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| 79 |
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[2447] | 80 | }
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| 81 |
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[5686] | 82 | public static ISymbolicExpressionTree Create(IRandom random, ISymbolicExpressionGrammar grammar,
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| 83 | int maxTreeLength, int maxTreeDepth) {
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[3223] | 84 | SymbolicExpressionTree tree = new SymbolicExpressionTree();
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[5686] | 85 | var rootNode = (SymbolicExpressionTreeTopLevelNode)grammar.ProgramRootSymbol.CreateTreeNode();
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[3442] | 86 | if (rootNode.HasLocalParameters) rootNode.ResetLocalParameters(random);
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[4249] | 87 | rootNode.SetGrammar(new SymbolicExpressionTreeGrammar(grammar));
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[5686] | 88 | var startNode = (SymbolicExpressionTreeTopLevelNode)grammar.StartSymbol.CreateTreeNode();
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| 89 | startNode.SetGrammar(new SymbolicExpressionTreeGrammar(grammar));
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| 90 | if (startNode.HasLocalParameters) startNode.ResetLocalParameters(random);
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[5733] | 91 | rootNode.AddSubtree(startNode);
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[5686] | 92 | PTC2(random, startNode, maxTreeLength, maxTreeDepth);
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| 93 | tree.Root = rootNode;
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[3223] | 94 | return tree;
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| 95 | }
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| 96 |
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[3338] | 97 | private class TreeExtensionPoint {
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[5499] | 98 | public ISymbolicExpressionTreeNode Parent { get; set; }
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[3338] | 99 | public int ChildIndex { get; set; }
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| 100 | public int ExtensionPointDepth { get; set; }
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[3223] | 101 | }
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[3360] | 102 |
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[5686] | 103 | public static void PTC2(IRandom random, ISymbolicExpressionTreeNode seedNode,
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| 104 | int maxLength, int maxDepth) {
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[6009] | 105 | // make sure it is possible to create a trees smaller than maxLength and maxDepth
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| 106 | if (seedNode.Grammar.GetMinimumExpressionLength(seedNode.Symbol) > maxLength)
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| 107 | throw new ArgumentException("Cannot create trees of length " + maxLength + " or shorter because of grammar constraints.", "maxLength");
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| 108 | if (seedNode.Grammar.GetMinimumExpressionDepth(seedNode.Symbol) > maxDepth)
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| 109 | throw new ArgumentException("Cannot create trees of depth " + maxDepth + " or smaller because of grammar constraints.", "maxDepth");
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| 110 |
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[5549] | 111 | // tree length is limited by the grammar and by the explicit size constraints
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[5686] | 112 | int allowedMinLength = seedNode.Grammar.GetMinimumExpressionLength(seedNode.Symbol);
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| 113 | int allowedMaxLength = Math.Min(maxLength, seedNode.Grammar.GetMaximumExpressionLength(seedNode.Symbol));
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[3369] | 114 | int tries = 0;
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| 115 | while (tries++ < MAX_TRIES) {
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[5549] | 116 | // select a target tree length uniformly in the possible range (as determined by explicit limits and limits of the grammar)
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| 117 | int targetTreeLength;
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| 118 | targetTreeLength = random.Next(allowedMinLength, allowedMaxLength + 1);
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[5686] | 119 | if (targetTreeLength <= 1 || maxDepth <= 1) return;
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[3369] | 120 |
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[5727] | 121 | bool success = TryCreateFullTreeFromSeed(random, seedNode, seedNode.Grammar, targetTreeLength, maxDepth);
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[3369] | 122 |
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[4189] | 123 | // if successful => check constraints and return the tree if everything looks ok
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[5549] | 124 | if (success && seedNode.GetLength() <= maxLength && seedNode.GetDepth() <= maxDepth) {
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[5686] | 125 | return;
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[3369] | 126 | } else {
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| 127 | // clean seedNode
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[5733] | 128 | while (seedNode.Subtrees.Count() > 0) seedNode.RemoveSubtree(0);
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[3360] | 129 | }
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[5549] | 130 | // try a different length MAX_TRIES times
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[3369] | 131 | }
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[3825] | 132 | throw new ArgumentException("Couldn't create a random valid tree.");
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[3338] | 133 | }
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| 134 |
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[5727] | 135 | private static bool TryCreateFullTreeFromSeed(IRandom random, ISymbolicExpressionTreeNode root, ISymbolicExpressionTreeGrammar globalGrammar,
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[5686] | 136 | int targetLength, int maxDepth) {
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[3338] | 137 | List<TreeExtensionPoint> extensionPoints = new List<TreeExtensionPoint>();
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[5549] | 138 | int currentLength = 1;
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[5686] | 139 | int totalListMinLength = globalGrammar.GetMinimumExpressionLength(root.Symbol) - 1;
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[5549] | 140 | int actualArity = SampleArity(random, root, targetLength);
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[5727] | 141 | if (actualArity < 0) return false;
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| 142 |
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[3223] | 143 | for (int i = 0; i < actualArity; i++) {
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| 144 | // insert a dummy sub-tree and add the pending extension to the list
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[3338] | 145 | var dummy = new SymbolicExpressionTreeNode();
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[5733] | 146 | root.AddSubtree(dummy);
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[4219] | 147 | extensionPoints.Add(new TreeExtensionPoint { Parent = root, ChildIndex = i, ExtensionPointDepth = 0 });
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[3223] | 148 | }
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| 149 | // while there are pending extension points and we have not reached the limit of adding new extension points
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[5549] | 150 | while (extensionPoints.Count > 0 && totalListMinLength + currentLength < targetLength) {
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[3294] | 151 | int randomIndex = random.Next(extensionPoints.Count);
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[3338] | 152 | TreeExtensionPoint nextExtension = extensionPoints[randomIndex];
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[3294] | 153 | extensionPoints.RemoveAt(randomIndex);
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[5499] | 154 | ISymbolicExpressionTreeNode parent = nextExtension.Parent;
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[3338] | 155 | int argumentIndex = nextExtension.ChildIndex;
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| 156 | int extensionDepth = nextExtension.ExtensionPointDepth;
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[6009] | 157 | if (parent.Grammar.GetMinimumExpressionDepth(parent.Symbol) >= maxDepth - extensionDepth) {
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[5686] | 158 | ReplaceWithMinimalTree(random, root, parent, argumentIndex);
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[3223] | 159 | } else {
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[5499] | 160 | var allowedSymbols = (from s in parent.Grammar.Symbols
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[5925] | 161 | where s.InitialFrequency > 0.0
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[5686] | 162 | where parent.Grammar.IsAllowedChildSymbol(parent.Symbol, s, argumentIndex)
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[6009] | 163 | where parent.Grammar.GetMinimumExpressionDepth(s) < maxDepth - extensionDepth + 1
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[5686] | 164 | where parent.Grammar.GetMaximumExpressionLength(s) > targetLength - totalListMinLength - currentLength
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[5499] | 165 | select s)
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| 166 | .ToList();
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| 167 | var weights = allowedSymbols.Select(x => x.InitialFrequency).ToList();
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| 168 | var selectedSymbol = allowedSymbols.SelectRandom(weights, random);
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| 169 | ISymbolicExpressionTreeNode newTree = selectedSymbol.CreateTreeNode();
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[3442] | 170 | if (newTree.HasLocalParameters) newTree.ResetLocalParameters(random);
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[5733] | 171 | parent.RemoveSubtree(argumentIndex);
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| 172 | parent.InsertSubtree(argumentIndex, newTree);
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[3338] | 173 |
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[5686] | 174 | var topLevelNode = newTree as SymbolicExpressionTreeTopLevelNode;
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| 175 | if (topLevelNode != null)
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| 176 | topLevelNode.SetGrammar((ISymbolicExpressionTreeGrammar)root.Grammar.Clone());
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[3338] | 177 |
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[5549] | 178 | currentLength++;
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| 179 | totalListMinLength--;
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[3223] | 180 |
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[5549] | 181 | actualArity = SampleArity(random, newTree, targetLength - currentLength);
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[5727] | 182 | if (actualArity < 0) return false;
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[3223] | 183 | for (int i = 0; i < actualArity; i++) {
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| 184 | // insert a dummy sub-tree and add the pending extension to the list
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[3338] | 185 | var dummy = new SymbolicExpressionTreeNode();
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[5733] | 186 | newTree.AddSubtree(dummy);
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[3338] | 187 | extensionPoints.Add(new TreeExtensionPoint { Parent = newTree, ChildIndex = i, ExtensionPointDepth = extensionDepth + 1 });
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[3223] | 188 | }
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[5686] | 189 | totalListMinLength += newTree.Grammar.GetMinimumExpressionLength(newTree.Symbol);
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[3223] | 190 | }
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| 191 | }
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| 192 | // fill all pending extension points
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[3294] | 193 | while (extensionPoints.Count > 0) {
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| 194 | int randomIndex = random.Next(extensionPoints.Count);
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[3338] | 195 | TreeExtensionPoint nextExtension = extensionPoints[randomIndex];
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[3294] | 196 | extensionPoints.RemoveAt(randomIndex);
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[5499] | 197 | ISymbolicExpressionTreeNode parent = nextExtension.Parent;
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[3338] | 198 | int a = nextExtension.ChildIndex;
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| 199 | int d = nextExtension.ExtensionPointDepth;
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[5686] | 200 | ReplaceWithMinimalTree(random, root, parent, a);
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[3223] | 201 | }
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[5727] | 202 | return true;
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[2210] | 203 | }
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[3223] | 204 |
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[5499] | 205 | private static void ReplaceWithMinimalTree(IRandom random, ISymbolicExpressionTreeNode root, ISymbolicExpressionTreeNode parent,
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[5686] | 206 | int childIndex) {
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[3338] | 207 | // determine possible symbols that will lead to the smallest possible tree
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[5686] | 208 | var possibleSymbols = (from s in parent.Grammar.GetAllowedChildSymbols(parent.Symbol, childIndex)
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[5925] | 209 | where s.InitialFrequency > 0.0
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[5686] | 210 | group s by parent.Grammar.GetMinimumExpressionLength(s) into g
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[3338] | 211 | orderby g.Key
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[5499] | 212 | select g).First().ToList();
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| 213 | var weights = possibleSymbols.Select(x => x.InitialFrequency).ToList();
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| 214 | var selectedSymbol = possibleSymbols.SelectRandom(weights, random);
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[3338] | 215 | var tree = selectedSymbol.CreateTreeNode();
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[3442] | 216 | if (tree.HasLocalParameters) tree.ResetLocalParameters(random);
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[5733] | 217 | parent.RemoveSubtree(childIndex);
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| 218 | parent.InsertSubtree(childIndex, tree);
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[5686] | 219 |
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| 220 | var topLevelNode = tree as SymbolicExpressionTreeTopLevelNode;
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| 221 | if (topLevelNode != null)
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| 222 | topLevelNode.SetGrammar((ISymbolicExpressionTreeGrammar)root.Grammar.Clone());
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| 223 |
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| 224 | for (int i = 0; i < tree.Grammar.GetMinimumSubtreeCount(tree.Symbol); i++) {
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[3338] | 225 | // insert a dummy sub-tree and add the pending extension to the list
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| 226 | var dummy = new SymbolicExpressionTreeNode();
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[5733] | 227 | tree.AddSubtree(dummy);
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[3338] | 228 | // replace the just inserted dummy by recursive application
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[5686] | 229 | ReplaceWithMinimalTree(random, root, tree, i);
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[3338] | 230 | }
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| 231 | }
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[3360] | 232 |
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[5499] | 233 | private static bool IsTopLevelBranch(ISymbolicExpressionTreeNode root, ISymbolicExpressionTreeNode branch) {
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[3369] | 234 | return branch is SymbolicExpressionTreeTopLevelNode;
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[3338] | 235 | }
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| 236 |
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[5549] | 237 | private static int SampleArity(IRandom random, ISymbolicExpressionTreeNode node, int targetLength) {
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[3223] | 238 | // select actualArity randomly with the constraint that the sub-trees in the minimal arity can become large enough
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[5686] | 239 | int minArity = node.Grammar.GetMinimumSubtreeCount(node.Symbol);
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| 240 | int maxArity = node.Grammar.GetMaximumSubtreeCount(node.Symbol);
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[5549] | 241 | if (maxArity > targetLength) {
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| 242 | maxArity = targetLength;
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[3223] | 243 | }
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[5549] | 244 | // 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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| 245 | // 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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[3237] | 246 | long aggregatedLongestExpressionLength = 0;
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[3223] | 247 | for (int i = 0; i < maxArity; i++) {
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[5686] | 248 | aggregatedLongestExpressionLength += (from s in node.Grammar.GetAllowedChildSymbols(node.Symbol, i)
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[5925] | 249 | where s.InitialFrequency > 0.0
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[5686] | 250 | select node.Grammar.GetMaximumExpressionLength(s)).Max();
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[5925] | 251 | if (aggregatedLongestExpressionLength < targetLength) minArity = i + 1;
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[3223] | 252 | else break;
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| 253 | }
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| 254 |
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[5549] | 255 | // 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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| 256 | // 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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[3237] | 257 | long aggregatedShortestExpressionLength = 0;
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[3223] | 258 | for (int i = 0; i < maxArity; i++) {
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[5686] | 259 | aggregatedShortestExpressionLength += (from s in node.Grammar.GetAllowedChildSymbols(node.Symbol, i)
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[5925] | 260 | where s.InitialFrequency > 0.0
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[5686] | 261 | select node.Grammar.GetMinimumExpressionLength(s)).Min();
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[5549] | 262 | if (aggregatedShortestExpressionLength > targetLength) {
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[3223] | 263 | maxArity = i;
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| 264 | break;
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| 265 | }
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| 266 | }
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[5727] | 267 | if (minArity > maxArity) return -1;
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[3223] | 268 | return random.Next(minArity, maxArity + 1);
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| 269 | }
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[2447] | 270 | }
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[645] | 271 | } |
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