1 | #region License Information
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2 | /* HeuristicLab
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3 | * Copyright (C) 2002-2016 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
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4 | *
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5 | * This file is part of HeuristicLab.
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6 | *
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7 | * HeuristicLab is free software: you can redistribute it and/or modify
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8 | * it under the terms of the GNU General Public License as published by
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9 | * the Free Software Foundation, either version 3 of the License, or
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10 | * (at your option) any later version.
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11 | *
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12 | * HeuristicLab is distributed in the hope that it will be useful,
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13 | * but WITHOUT ANY WARRANTY; without even the implied warranty of
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14 | * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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15 | * GNU General Public License for more details.
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16 | *
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17 | * You should have received a copy of the GNU General Public License
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18 | * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
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19 | */
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20 | #endregion
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21 |
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22 | using System;
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23 | using System.Collections.Generic;
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24 | using System.Linq;
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25 | using HeuristicLab.Common;
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26 | using HeuristicLab.Core;
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27 | using HeuristicLab.Data;
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28 | using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
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29 | using HeuristicLab.Parameters;
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30 | using HeuristicLab.Persistence;
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31 | using HeuristicLab.Random;
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32 |
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33 | namespace HeuristicLab.Problems.DataAnalysis.Symbolic {
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34 | [StorableType("a5460680-59af-43a0-9407-cadce588ebef")]
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35 | public abstract class SymbolicDataAnalysisExpressionCrossover<T> : SymbolicExpressionTreeCrossover, ISymbolicDataAnalysisExpressionCrossover<T> where T : class, IDataAnalysisProblemData {
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36 | private const string SymbolicDataAnalysisTreeInterpreterParameterName = "SymbolicExpressionTreeInterpreter";
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37 | private const string ProblemDataParameterName = "ProblemData";
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38 | private const string EvaluatorParameterName = "Evaluator";
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39 | private const string EvaluationPartitionParameterName = "EvaluationPartition";
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40 | private const string RelativeNumberOfEvaluatedSamplesParameterName = "RelativeNumberOfEvaluatedSamples";
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41 | private const string MaximumSymbolicExpressionTreeLengthParameterName = "MaximumSymbolicExpressionTreeLength";
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42 | private const string MaximumSymbolicExpressionTreeDepthParameterName = "MaximumSymbolicExpressionTreeDepth";
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43 |
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44 | #region Parameter properties
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45 | public ILookupParameter<ISymbolicDataAnalysisExpressionTreeInterpreter> SymbolicDataAnalysisTreeInterpreterParameter {
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46 | get { return (ILookupParameter<ISymbolicDataAnalysisExpressionTreeInterpreter>)Parameters[SymbolicDataAnalysisTreeInterpreterParameterName]; }
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47 | }
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48 | public IValueLookupParameter<T> ProblemDataParameter {
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49 | get { return (IValueLookupParameter<T>)Parameters[ProblemDataParameterName]; }
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50 | }
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51 | public ILookupParameter<ISymbolicDataAnalysisSingleObjectiveEvaluator<T>> EvaluatorParameter {
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52 | get { return (ILookupParameter<ISymbolicDataAnalysisSingleObjectiveEvaluator<T>>)Parameters[EvaluatorParameterName]; }
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53 | }
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54 | public IValueLookupParameter<IntRange> EvaluationPartitionParameter {
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55 | get { return (IValueLookupParameter<IntRange>)Parameters[EvaluationPartitionParameterName]; }
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56 | }
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57 | public IValueLookupParameter<PercentValue> RelativeNumberOfEvaluatedSamplesParameter {
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58 | get { return (IValueLookupParameter<PercentValue>)Parameters[RelativeNumberOfEvaluatedSamplesParameterName]; }
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59 | }
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60 | public IValueLookupParameter<IntValue> MaximumSymbolicExpressionTreeLengthParameter {
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61 | get { return (IValueLookupParameter<IntValue>)Parameters[MaximumSymbolicExpressionTreeLengthParameterName]; }
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62 | }
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63 | public IValueLookupParameter<IntValue> MaximumSymbolicExpressionTreeDepthParameter {
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64 | get { return (IValueLookupParameter<IntValue>)Parameters[MaximumSymbolicExpressionTreeDepthParameterName]; }
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65 | }
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66 | #endregion
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67 |
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68 | #region Properties
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69 | public IntValue MaximumSymbolicExpressionTreeLength {
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70 | get { return MaximumSymbolicExpressionTreeLengthParameter.ActualValue; }
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71 | }
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72 | public IntValue MaximumSymbolicExpressionTreeDepth {
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73 | get { return MaximumSymbolicExpressionTreeDepthParameter.ActualValue; }
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74 | }
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75 | #endregion
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76 |
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77 | [StorableConstructor]
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78 | protected SymbolicDataAnalysisExpressionCrossover(StorableConstructorFlag deserializing) : base(deserializing) { }
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79 | protected SymbolicDataAnalysisExpressionCrossover(SymbolicDataAnalysisExpressionCrossover<T> original, Cloner cloner)
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80 | : base(original, cloner) {
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81 | }
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82 | public SymbolicDataAnalysisExpressionCrossover()
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83 | : base() {
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84 | Parameters.Add(new LookupParameter<ISymbolicDataAnalysisExpressionTreeInterpreter>(SymbolicDataAnalysisTreeInterpreterParameterName, "The interpreter that should be used to calculate the output values of the symbolic data analysis tree."));
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85 | Parameters.Add(new LookupParameter<ISymbolicDataAnalysisSingleObjectiveEvaluator<T>>(EvaluatorParameterName, "The single objective solution evaluator"));
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86 | Parameters.Add(new ValueLookupParameter<T>(ProblemDataParameterName, "The problem data on which the symbolic data analysis solution should be evaluated."));
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87 | Parameters.Add(new ValueLookupParameter<IntRange>(EvaluationPartitionParameterName, "The start index of the dataset partition on which the symbolic data analysis solution should be evaluated."));
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88 | Parameters.Add(new ValueLookupParameter<PercentValue>(RelativeNumberOfEvaluatedSamplesParameterName, "The relative number of samples of the dataset partition, which should be randomly chosen for evaluation between the start and end index."));
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89 | Parameters.Add(new ValueLookupParameter<IntValue>(MaximumSymbolicExpressionTreeDepthParameterName, "The maximum tree depth."));
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90 | Parameters.Add(new ValueLookupParameter<IntValue>(MaximumSymbolicExpressionTreeLengthParameterName, "The maximum tree length."));
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91 |
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92 | EvaluatorParameter.Hidden = true;
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93 | EvaluationPartitionParameter.Hidden = true;
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94 | SymbolicDataAnalysisTreeInterpreterParameter.Hidden = true;
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95 | ProblemDataParameter.Hidden = true;
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96 | RelativeNumberOfEvaluatedSamplesParameter.Hidden = true;
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97 | }
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98 |
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99 | /// <summary>
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100 | /// Creates a SymbolicExpressionTreeNode reusing the root and start symbols (since they are expensive to create).
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101 | /// </summary>
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102 | /// <param name="random"></param>
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103 | /// <param name="node"></param>
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104 | /// <param name="rootSymbol"></param>
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105 | /// <param name="startSymbol"></param>
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106 | /// <returns></returns>
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107 | protected static ISymbolicExpressionTree CreateTreeFromNode(IRandom random, ISymbolicExpressionTreeNode node, ISymbol rootSymbol, ISymbol startSymbol) {
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108 | var rootNode = new SymbolicExpressionTreeTopLevelNode(rootSymbol);
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109 | if (rootNode.HasLocalParameters) rootNode.ResetLocalParameters(random);
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110 |
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111 | var startNode = new SymbolicExpressionTreeTopLevelNode(startSymbol);
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112 | if (startNode.HasLocalParameters) startNode.ResetLocalParameters(random);
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113 |
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114 | startNode.AddSubtree(node);
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115 | rootNode.AddSubtree(startNode);
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116 |
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117 | return new SymbolicExpressionTree(rootNode);
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118 | }
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119 |
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120 | protected IEnumerable<int> GenerateRowsToEvaluate() {
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121 | return GenerateRowsToEvaluate(RelativeNumberOfEvaluatedSamplesParameter.ActualValue.Value);
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122 | }
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123 |
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124 | protected IEnumerable<int> GenerateRowsToEvaluate(double percentageOfRows) {
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125 | IEnumerable<int> rows;
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126 | int samplesStart = EvaluationPartitionParameter.ActualValue.Start;
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127 | int samplesEnd = EvaluationPartitionParameter.ActualValue.End;
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128 | int testPartitionStart = ProblemDataParameter.ActualValue.TestPartition.Start;
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129 | int testPartitionEnd = ProblemDataParameter.ActualValue.TestPartition.End;
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130 |
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131 | if (samplesEnd < samplesStart) throw new ArgumentException("Start value is larger than end value.");
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132 |
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133 | if (percentageOfRows.IsAlmost(1.0))
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134 | rows = Enumerable.Range(samplesStart, samplesEnd - samplesStart);
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135 | else {
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136 | int seed = RandomParameter.ActualValue.Next();
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137 | int count = (int)((samplesEnd - samplesStart) * percentageOfRows);
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138 | if (count == 0) count = 1;
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139 | rows = RandomEnumerable.SampleRandomNumbers(seed, samplesStart, samplesEnd, count);
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140 | }
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141 |
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142 | return rows.Where(i => i < testPartitionStart || testPartitionEnd <= i);
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143 | }
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144 |
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145 | protected static void Swap(CutPoint crossoverPoint, ISymbolicExpressionTreeNode selectedBranch) {
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146 | if (crossoverPoint.Child != null) {
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147 | // manipulate the tree of parent0 in place
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148 | // replace the branch in tree0 with the selected branch from tree1
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149 | crossoverPoint.Parent.RemoveSubtree(crossoverPoint.ChildIndex);
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150 | if (selectedBranch != null) {
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151 | crossoverPoint.Parent.InsertSubtree(crossoverPoint.ChildIndex, selectedBranch);
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152 | }
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153 | } else {
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154 | // child is null (additional child should be added under the parent)
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155 | if (selectedBranch != null) {
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156 | crossoverPoint.Parent.AddSubtree(selectedBranch);
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157 | }
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158 | }
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159 | }
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160 | }
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161 | }
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