[645] | 1 | #region License Information
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| 2 | /* HeuristicLab
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[3237] | 3 | * Copyright (C) 2002-2010 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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[4068] | 22 | using System;
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[645] | 23 | using System.Collections.Generic;
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[4068] | 24 | using System.Linq;
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[645] | 25 | using HeuristicLab.Core;
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[3237] | 26 | using HeuristicLab.Data;
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| 27 | using HeuristicLab.Parameters;
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[4068] | 28 | using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
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[645] | 29 |
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[3462] | 30 | namespace HeuristicLab.Encodings.SymbolicExpressionTreeEncoding.Crossovers {
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[3237] | 31 | /// <summary>
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| 32 | /// Takes two parent individuals P0 and P1 each. Selects a random node N0 of P0 and a random node N1 of P1.
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| 33 | /// And replaces the branch with root0 N0 in P0 with N1 from P1 if the tree-size limits are not violated.
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| 34 | /// When recombination with N0 and N1 would create a tree that is too large or invalid the operator randomly selects new N0 and N1
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| 35 | /// until a valid configuration is found.
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| 36 | /// </summary>
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| 37 | [Item("SubtreeCrossover", "An operator which performs subtree swapping crossover.")]
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| 38 | [StorableClass]
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| 39 | public class SubtreeCrossover : SymbolicExpressionTreeCrossover {
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| 40 | public IValueLookupParameter<PercentValue> InternalCrossoverPointProbabilityParameter {
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| 41 | get { return (IValueLookupParameter<PercentValue>)Parameters["InternalCrossoverPointProbability"]; }
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[645] | 42 | }
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| 43 |
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[3237] | 44 | public SubtreeCrossover()
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| 45 | : base() {
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| 46 | Parameters.Add(new ValueLookupParameter<PercentValue>("InternalCrossoverPointProbability", "The probability to select an internal crossover point (instead of a leaf node).", new PercentValue(0.9)));
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| 47 | }
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| 48 |
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[3338] | 49 | protected override SymbolicExpressionTree Cross(IRandom random,
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[3237] | 50 | SymbolicExpressionTree parent0, SymbolicExpressionTree parent1,
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[3294] | 51 | IntValue maxTreeSize, IntValue maxTreeHeight, out bool success) {
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[3338] | 52 | return Cross(random, parent0, parent1, InternalCrossoverPointProbabilityParameter.ActualValue.Value, maxTreeSize.Value, maxTreeHeight.Value, out success);
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[3237] | 53 | }
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| 54 |
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[3338] | 55 | public static SymbolicExpressionTree Cross(IRandom random,
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[3237] | 56 | SymbolicExpressionTree parent0, SymbolicExpressionTree parent1,
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[3294] | 57 | double internalCrossoverPointProbability, int maxTreeSize, int maxTreeHeight, out bool success) {
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| 58 | // select a random crossover point in the first parent
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| 59 | SymbolicExpressionTreeNode crossoverPoint0;
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| 60 | int replacedSubtreeIndex;
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[3369] | 61 | SelectCrossoverPoint(random, parent0, internalCrossoverPointProbability, maxTreeSize - 1, maxTreeHeight - 1, out crossoverPoint0, out replacedSubtreeIndex);
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[645] | 62 |
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[3294] | 63 | // calculate the max size and height that the inserted branch can have
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| 64 | int maxInsertedBranchSize = maxTreeSize - (parent0.Size - crossoverPoint0.SubTrees[replacedSubtreeIndex].GetSize());
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| 65 | int maxInsertedBranchHeight = maxTreeHeight - GetBranchLevel(parent0.Root, crossoverPoint0);
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[645] | 66 |
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[3997] | 67 | List<SymbolicExpressionTreeNode> allowedBranches = new List<SymbolicExpressionTreeNode>();
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| 68 | parent1.Root.ForEachNodePostfix((n) => {
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| 69 | if (n.GetSize() < maxInsertedBranchSize &&
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| 70 | n.GetHeight() < maxInsertedBranchHeight &&
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| 71 | IsMatchingPointType(crossoverPoint0, replacedSubtreeIndex, n))
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| 72 | allowedBranches.Add(n);
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| 73 | });
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[645] | 74 |
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[3997] | 75 | if (allowedBranches.Count == 0) {
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[3297] | 76 | success = false;
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| 77 | return parent0;
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| 78 | } else {
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[3294] | 79 | var selectedBranch = SelectRandomBranch(random, allowedBranches, internalCrossoverPointProbability);
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[645] | 80 |
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[3294] | 81 | // manipulate the tree of parent0 in place
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| 82 | // replace the branch in tree0 with the selected branch from tree1
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| 83 | crossoverPoint0.RemoveSubTree(replacedSubtreeIndex);
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| 84 | crossoverPoint0.InsertSubTree(replacedSubtreeIndex, selectedBranch);
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| 85 | success = true;
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| 86 | return parent0;
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[645] | 87 | }
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| 88 | }
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| 89 |
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[3338] | 90 | private static bool IsMatchingPointType(SymbolicExpressionTreeNode parent, int replacedSubtreeIndex, SymbolicExpressionTreeNode branch) {
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| 91 | // check syntax constraints of direct parent - child relation
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[4106] | 92 | if (!parent.Grammar.ContainsSymbol(branch.Symbol) ||
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| 93 | !parent.Grammar.IsAllowedChild(parent.Symbol, branch.Symbol, replacedSubtreeIndex)) return false;
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[3338] | 94 |
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[3997] | 95 | bool result = true;
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| 96 | // check point type for the whole branch
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| 97 | branch.ForEachNodePostfix((n) => {
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[3998] | 98 | result =
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| 99 | result &&
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[4106] | 100 | parent.Grammar.ContainsSymbol(n.Symbol) &&
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[3998] | 101 | n.SubTrees.Count >= parent.Grammar.GetMinSubtreeCount(n.Symbol) &&
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[4106] | 102 | n.SubTrees.Count <= parent.Grammar.GetMaxSubtreeCount(n.Symbol);
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[3997] | 103 | });
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| 104 | return result;
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[3294] | 105 | }
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| 106 |
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[3369] | 107 | private static void SelectCrossoverPoint(IRandom random, SymbolicExpressionTree parent0, double internalNodeProbability, int maxBranchSize, int maxBranchHeight, out SymbolicExpressionTreeNode crossoverPoint, out int subtreeIndex) {
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[3997] | 108 | if (internalNodeProbability < 0.0 || internalNodeProbability > 1.0) throw new ArgumentException("internalNodeProbability");
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| 109 | List<CrossoverPoint> internalCrossoverPoints = new List<CrossoverPoint>();
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| 110 | List<CrossoverPoint> leafCrossoverPoints = new List<CrossoverPoint>();
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| 111 | parent0.Root.ForEachNodePostfix((n) => {
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| 112 | if (n.SubTrees.Count > 0 &&
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| 113 | n.GetSize() < maxBranchSize &&
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| 114 | n.GetHeight() < maxBranchHeight &&
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| 115 | n != parent0.Root
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| 116 | ) {
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| 117 | foreach (var child in n.SubTrees) {
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| 118 | if (child.SubTrees.Count > 0)
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| 119 | internalCrossoverPoints.Add(new CrossoverPoint(n, child));
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| 120 | else
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| 121 | leafCrossoverPoints.Add(new CrossoverPoint(n, child));
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| 122 | }
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| 123 | }
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| 124 | });
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| 125 | if (random.NextDouble() < internalNodeProbability) {
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| 126 | // select from internal node if possible
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| 127 | if (internalCrossoverPoints.Count > 0) {
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| 128 | // select internal crossover point or leaf
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| 129 | var selectedCrossoverPoint = internalCrossoverPoints[random.Next(internalCrossoverPoints.Count)];
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| 130 | crossoverPoint = selectedCrossoverPoint.Parent;
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| 131 | subtreeIndex = selectedCrossoverPoint.SubtreeIndex;
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| 132 | } else {
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| 133 | // otherwise select external node
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| 134 | var selectedCrossoverPoint = leafCrossoverPoints[random.Next(leafCrossoverPoints.Count)];
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| 135 | crossoverPoint = selectedCrossoverPoint.Parent;
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| 136 | subtreeIndex = selectedCrossoverPoint.SubtreeIndex;
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| 137 | }
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| 138 | } else if (leafCrossoverPoints.Count > 0) {
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| 139 | // select from leaf crossover point if possible
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[3294] | 140 | var selectedCrossoverPoint = leafCrossoverPoints[random.Next(leafCrossoverPoints.Count)];
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[3997] | 141 | crossoverPoint = selectedCrossoverPoint.Parent;
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[3294] | 142 | subtreeIndex = selectedCrossoverPoint.SubtreeIndex;
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[3997] | 143 | } else {
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| 144 | // otherwise select internal crossover point
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[3237] | 145 | var selectedCrossoverPoint = internalCrossoverPoints[random.Next(internalCrossoverPoints.Count)];
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[3997] | 146 | crossoverPoint = selectedCrossoverPoint.Parent;
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[3237] | 147 | subtreeIndex = selectedCrossoverPoint.SubtreeIndex;
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[645] | 148 | }
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| 149 | }
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[3237] | 150 |
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| 151 | private static SymbolicExpressionTreeNode SelectRandomBranch(IRandom random, IEnumerable<SymbolicExpressionTreeNode> branches, double internalNodeProbability) {
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| 152 | if (internalNodeProbability < 0.0 || internalNodeProbability > 1.0) throw new ArgumentException("internalNodeProbability");
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[3997] | 153 | List<SymbolicExpressionTreeNode> allowedInternalBranches;
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| 154 | List<SymbolicExpressionTreeNode> allowedLeafBranches;
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| 155 | if (random.NextDouble() < internalNodeProbability) {
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| 156 | // select internal node if possible
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| 157 | allowedInternalBranches = (from branch in branches
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| 158 | where branch.SubTrees.Count > 0
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| 159 | select branch).ToList();
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| 160 | if (allowedInternalBranches.Count > 0) {
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| 161 | return allowedInternalBranches.SelectRandom(random);
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| 162 | } else {
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| 163 | // no internal nodes allowed => select leaf nodes
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| 164 | allowedLeafBranches = (from branch in branches
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[3989] | 165 | where branch.SubTrees.Count == 0
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| 166 | select branch).ToList();
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[3997] | 167 | return allowedLeafBranches.SelectRandom(random);
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| 168 | }
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[3237] | 169 | } else {
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[3997] | 170 | // select leaf node if possible
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| 171 | allowedLeafBranches = (from branch in branches
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| 172 | where branch.SubTrees.Count == 0
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| 173 | select branch).ToList();
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| 174 | if (allowedLeafBranches.Count > 0) {
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| 175 | return allowedLeafBranches.SelectRandom(random);
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| 176 | } else {
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| 177 | allowedInternalBranches = (from branch in branches
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| 178 | where branch.SubTrees.Count > 0
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| 179 | select branch).ToList();
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| 180 | return allowedInternalBranches.SelectRandom(random);
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| 181 | }
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[3237] | 182 | }
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| 183 | }
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| 184 |
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| 185 | private static int GetBranchLevel(SymbolicExpressionTreeNode root, SymbolicExpressionTreeNode point) {
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| 186 | if (root == point) return 0;
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| 187 | foreach (var subtree in root.SubTrees) {
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| 188 | int branchLevel = GetBranchLevel(subtree, point);
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| 189 | if (branchLevel < int.MaxValue) return 1 + branchLevel;
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| 190 | }
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| 191 | return int.MaxValue;
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| 192 | }
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[645] | 193 | }
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| 194 | }
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