1 | #region License Information
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2 | /* HeuristicLab
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3 | * Copyright (C) 2002-2019 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 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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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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72 |
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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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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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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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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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89 | private DiversitySelector(StorableConstructorFlag _) : base(_) { }
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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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102 |
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103 | RegisterParameterEventHandlers();
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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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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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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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115 | }
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116 |
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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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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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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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143 | return CurrentScope.SubScopes[1].SubScopes.ToArray(); // return selected individuals (selectors create two sub-scopes with remaining and selected)
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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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