[16623] | 1 | #region License Information
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| 2 | /* HeuristicLab
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[17180] | 3 | * Copyright (C) Heuristic and Evolutionary Algorithms Laboratory (HEAL)
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[16623] | 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 HEAL.Attic;
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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.Encodings.SymbolicExpressionTreeEncoding;
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| 29 | using HeuristicLab.Optimization;
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| 30 | using HeuristicLab.Parameters;
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| 31 | using HeuristicLab.Selection;
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| 32 |
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| 33 | namespace HeuristicLab.Problems.DataAnalysis.Symbolic {
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| 34 | [StorableType("3E8EA052-3B86-4609-BD38-E3FE78DAD2FF")]
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| 35 | [Item("DiversitySelector", "A selection operator that applies a diversity penalty to the objective function before applying an inner selector.")]
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| 36 | public sealed class DiversitySelector : StochasticSingleObjectiveSelector, ISingleObjectiveSelector {
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| 37 | private const string StrictSimilarityParameterName = "StrictSimilarity";
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| 38 | private const string SimilarityWeightParameterName = "SimilarityWeight";
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| 39 | private const string SymbolicExpressionTreeParameterName = "SymbolicExpressionTree";
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| 40 | private const string SelectorParameterName = "Selector";
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| 41 | private const string DiversityParameterName = "Diversity";
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| 42 |
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| 43 | public IValueParameter<ISingleObjectiveSelector> SelectorParameter {
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| 44 | get { return (IValueParameter<ISingleObjectiveSelector>)Parameters[SelectorParameterName]; }
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| 45 | }
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| 46 |
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| 47 | public ISingleObjectiveSelector Selector {
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| 48 | get { return SelectorParameter.Value; }
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| 49 | set { SelectorParameter.Value = value; }
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| 50 | }
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| 51 |
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| 52 | public IScopeTreeLookupParameter<ISymbolicExpressionTree> SymbolicExpressionTreeParameter {
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| 53 | get { return (IScopeTreeLookupParameter<ISymbolicExpressionTree>)Parameters[SymbolicExpressionTreeParameterName]; }
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| 54 | }
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| 55 |
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| 56 | public IScopeTreeLookupParameter<DoubleValue> DiversityParameter {
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| 57 | get { return (IScopeTreeLookupParameter<DoubleValue>)Parameters[DiversityParameterName]; }
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| 58 | }
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| 59 |
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| 60 | public IFixedValueParameter<BoolValue> StrictSimilarityParameter {
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| 61 | get { return (IFixedValueParameter<BoolValue>)Parameters[StrictSimilarityParameterName]; }
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| 62 | }
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| 63 |
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| 64 | public IFixedValueParameter<DoubleValue> SimilarityWeightParameter {
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| 65 | get { return (IFixedValueParameter<DoubleValue>)Parameters[SimilarityWeightParameterName]; }
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| 66 | }
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| 67 |
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[17076] | 68 | public bool StrictSimilarity {
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| 69 | get { return StrictSimilarityParameter.Value.Value; }
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| 70 | set { StrictSimilarityParameter.Value.Value = value; }
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| 71 | }
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[16623] | 72 |
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[17076] | 73 | public double SimilarityWeight {
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| 74 | get { return SimilarityWeightParameter.Value.Value; }
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| 75 | set { SimilarityWeightParameter.Value.Value = value; }
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| 76 | }
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[16623] | 77 |
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| 78 | public DiversitySelector() : base() {
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| 79 | Parameters.Add(new FixedValueParameter<BoolValue>(StrictSimilarityParameterName, "Calculate strict similarity.", new BoolValue(true)));
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| 80 | Parameters.Add(new FixedValueParameter<DoubleValue>(SimilarityWeightParameterName, "Weight of the diversity term.", new DoubleValue(1)));
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| 81 | Parameters.Add(new ScopeTreeLookupParameter<ISymbolicExpressionTree>(SymbolicExpressionTreeParameterName, "The symbolic expression trees that should be analyzed."));
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| 82 | Parameters.Add(new ValueParameter<ISingleObjectiveSelector>(SelectorParameterName, "The inner selection operator to select the parents.", new TournamentSelector()));
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[17076] | 83 | Parameters.Add(new ScopeTreeLookupParameter<DoubleValue>(DiversityParameterName, "The diversity value calcuated by the operator (output). The inner selector uses this value."));
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[16623] | 84 |
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| 85 | RegisterParameterEventHandlers();
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| 86 | }
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| 87 |
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| 88 | [StorableConstructor]
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[17076] | 89 | private DiversitySelector(StorableConstructorFlag _) : base(_) { }
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[16623] | 90 |
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| 91 | private DiversitySelector(DiversitySelector original, Cloner cloner) : base(original, cloner) { }
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| 92 |
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| 93 | public override IDeepCloneable Clone(Cloner cloner) {
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| 94 | return new DiversitySelector(this, cloner);
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| 95 | }
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| 96 |
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| 97 | [StorableHook(HookType.AfterDeserialization)]
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| 98 | private void AfterDeserialization() {
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| 99 | if (!Parameters.ContainsKey(DiversityParameterName)) {
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| 100 | Parameters.Add(new ScopeTreeLookupParameter<DoubleValue>(DiversityParameterName));
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| 101 | }
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[17076] | 102 |
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| 103 | RegisterParameterEventHandlers();
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[16623] | 104 | }
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| 105 |
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| 106 | #region Events
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| 107 | private void RegisterParameterEventHandlers() {
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[16839] | 108 | SelectorParameter.ValueChanged += SelectorParameter_ValueChanged;
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| 109 | CopySelectedParameter.ValueChanged += CopySelectedParameter_ValueChanged;
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| 110 | CopySelected.ValueChanged += CopySelected_ValueChanged;
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[17076] | 111 |
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| 112 | MaximizationParameter.NameChanged += MaximizationParameter_NameChanged;
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| 113 | QualityParameter.NameChanged += QualityParameter_NameChanged;
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| 114 | RandomParameter.NameChanged += RandomParameter_NameChanged;
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[16623] | 115 | }
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| 116 |
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[17076] | 117 | private void RandomParameter_NameChanged(object sender, EventArgs e) { ParameterizeSelector(Selector); }
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| 118 | private void QualityParameter_NameChanged(object sender, EventArgs e) { ParameterizeSelector(Selector); }
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| 119 | private void MaximizationParameter_NameChanged(object sender, EventArgs e) { ParameterizeSelector(Selector); }
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| 120 |
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[16839] | 121 | private void CopySelectedParameter_ValueChanged(object sender, EventArgs e) {
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| 122 | if (CopySelected.Value != true) {
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| 123 | CopySelected.Value = true;
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| 124 | }
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| 125 | CopySelected.ValueChanged += CopySelected_ValueChanged;
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| 126 | }
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| 127 |
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[16623] | 128 | private void SelectorParameter_ValueChanged(object sender, EventArgs e) {
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| 129 | ParameterizeSelector(Selector);
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| 130 | }
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| 131 |
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| 132 | private void CopySelected_ValueChanged(object sender, EventArgs e) {
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| 133 | if (CopySelected.Value != true) {
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| 134 | CopySelected.Value = true;
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| 135 | }
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| 136 | }
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| 137 | #endregion
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| 138 |
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| 139 | protected override IScope[] Select(List<IScope> scopes) {
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| 140 | var w = SimilarityWeight;
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| 141 | if (w.IsAlmost(0)) {
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| 142 | ApplyInnerSelector();
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[17076] | 143 | return CurrentScope.SubScopes[1].SubScopes.ToArray(); // return selected individuals (selectors create two sub-scopes with remaining and selected)
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[16623] | 144 | }
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| 145 |
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| 146 | var trees = SymbolicExpressionTreeParameter.ActualValue;
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| 147 | var qualities = QualityParameter.ActualValue;
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| 148 |
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| 149 | // calculate average similarity for each tree
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| 150 | var similarityMatrix = SymbolicExpressionTreeHash.ComputeSimilarityMatrix(trees, simplify: false, strict: StrictSimilarity);
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| 151 | var similarities = new double[trees.Length];
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| 152 | for (int i = 0; i < trees.Length; ++i) {
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| 153 | for (int j = 0; j < trees.Length; ++j) {
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| 154 | if (i != j) {
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| 155 | similarities[i] += similarityMatrix[i, j];
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| 156 | }
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| 157 | }
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| 158 | similarities[i] /= (trees.Length - 1);
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| 159 | }
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| 160 |
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| 161 | var v = 1 - w;
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| 162 |
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| 163 | var maximization = MaximizationParameter.ActualValue.Value;
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| 164 | var diversities = new ItemArray<DoubleValue>(trees.Length);
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| 165 | for (int i = 0; i < trees.Length; ++i) {
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| 166 | var q = qualities[i].Value;
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| 167 | var d = 1 - similarities[i]; // average distance
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| 168 |
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| 169 | // assuming both q and d are in the interval [0, 1]
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| 170 | var value = maximization
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| 171 | ? (v * q) + (w * d)
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| 172 | : (v * q) - (w * d);
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| 173 |
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| 174 | diversities[i] = new DoubleValue(value);
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| 175 | }
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| 176 |
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| 177 | Selector.QualityParameter.ActualName = "Diversity";
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| 178 | DiversityParameter.ActualValue = diversities;
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| 179 | ApplyInnerSelector(); // apply inner selector
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| 180 |
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| 181 | return CurrentScope.SubScopes[1].SubScopes.ToArray();
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| 182 | }
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| 183 |
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| 184 | private void ParameterizeSelector(ISingleObjectiveSelector selector) {
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| 185 | selector.CopySelected = new BoolValue(true); // must always be true
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| 186 | selector.MaximizationParameter.ActualName = MaximizationParameter.Name;
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| 187 | selector.QualityParameter.ActualName = QualityParameter.Name;
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| 188 |
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| 189 | IStochasticOperator stoOp = (selector as IStochasticOperator);
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| 190 | if (stoOp != null) stoOp.RandomParameter.ActualName = RandomParameter.Name;
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| 191 | }
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| 192 |
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| 193 | private void ApplyInnerSelector() {
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| 194 | // necessary for inner GenderSpecificSelector to execute all operations in OperationCollection
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| 195 | Stack<IOperation> executionStack = new Stack<IOperation>();
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| 196 | executionStack.Push(ExecutionContext.CreateChildOperation(Selector));
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| 197 | while (executionStack.Count > 0) {
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| 198 | CancellationToken.ThrowIfCancellationRequested();
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| 199 | IOperation next = executionStack.Pop();
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| 200 | if (next is OperationCollection) {
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| 201 | OperationCollection coll = (OperationCollection)next;
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| 202 | for (int i = coll.Count - 1; i >= 0; i--)
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| 203 | if (coll[i] != null) executionStack.Push(coll[i]);
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| 204 | } else if (next is IAtomicOperation) {
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| 205 | IAtomicOperation operation = (IAtomicOperation)next;
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| 206 | next = operation.Operator.Execute((IExecutionContext)operation, CancellationToken);
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| 207 | if (next != null) executionStack.Push(next);
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| 208 | }
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| 209 | }
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| 210 | }
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| 211 | }
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| 212 | }
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