[5557] | 1 | #region License Information
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| 2 | /* HeuristicLab
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[11171] | 3 | * Copyright (C) 2002-2014 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
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[5557] | 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.Linq;
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| 23 | using HeuristicLab.Common;
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| 24 | using HeuristicLab.Core;
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| 25 | using HeuristicLab.Data;
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| 26 | using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
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| 27 | using HeuristicLab.Optimization;
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| 28 | using HeuristicLab.Parameters;
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| 29 | using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
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| 30 |
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| 31 | namespace HeuristicLab.Problems.DataAnalysis.Symbolic {
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| 32 | /// <summary>
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| 33 | /// An operator that analyzes the training best symbolic data analysis solution for single objective symbolic data analysis problems.
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| 34 | /// </summary>
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| 35 | [Item("SymbolicDataAnalysisSingleObjectiveTrainingBestSolutionAnalyzer", "An operator that analyzes the training best symbolic data analysis solution for single objective symbolic data analysis problems.")]
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| 36 | [StorableClass]
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[10599] | 37 | public abstract class SymbolicDataAnalysisSingleObjectiveTrainingBestSolutionAnalyzer<T> : SymbolicDataAnalysisSingleObjectiveAnalyzer, IIterationBasedOperator
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| 38 |
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[5607] | 39 | where T : class, ISymbolicDataAnalysisSolution {
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[5557] | 40 | private const string TrainingBestSolutionParameterName = "Best training solution";
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| 41 | private const string TrainingBestSolutionQualityParameterName = "Best training solution quality";
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[10599] | 42 | private const string TrainingBestSolutionGenerationParameterName = "Best training solution generation";
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[9152] | 43 | private const string UpdateAlwaysParameterName = "Always update best solution";
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[10599] | 44 | private const string IterationsParameterName = "Iterations";
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| 45 | private const string MaximumIterationsParameterName = "Maximum Iterations";
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[5557] | 46 |
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| 47 | #region parameter properties
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| 48 | public ILookupParameter<T> TrainingBestSolutionParameter {
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| 49 | get { return (ILookupParameter<T>)Parameters[TrainingBestSolutionParameterName]; }
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| 50 | }
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| 51 | public ILookupParameter<DoubleValue> TrainingBestSolutionQualityParameter {
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| 52 | get { return (ILookupParameter<DoubleValue>)Parameters[TrainingBestSolutionQualityParameterName]; }
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| 53 | }
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[10599] | 54 | public ILookupParameter<IntValue> TrainingBestSolutionGenerationParameter {
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| 55 | get { return (ILookupParameter<IntValue>)Parameters[TrainingBestSolutionGenerationParameterName]; }
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| 56 | }
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[9152] | 57 | public IFixedValueParameter<BoolValue> UpdateAlwaysParameter {
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| 58 | get { return (IFixedValueParameter<BoolValue>)Parameters[UpdateAlwaysParameterName]; }
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| 59 | }
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[10599] | 60 | public ILookupParameter<IntValue> IterationsParameter {
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| 61 | get { return (ILookupParameter<IntValue>)Parameters[IterationsParameterName]; }
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| 62 | }
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| 63 | public IValueLookupParameter<IntValue> MaximumIterationsParameter {
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| 64 | get { return (IValueLookupParameter<IntValue>)Parameters[MaximumIterationsParameterName]; }
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| 65 | }
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[5557] | 66 | #endregion
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| 67 | #region properties
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| 68 | public T TrainingBestSolution {
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| 69 | get { return TrainingBestSolutionParameter.ActualValue; }
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| 70 | set { TrainingBestSolutionParameter.ActualValue = value; }
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| 71 | }
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| 72 | public DoubleValue TrainingBestSolutionQuality {
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| 73 | get { return TrainingBestSolutionQualityParameter.ActualValue; }
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| 74 | set { TrainingBestSolutionQualityParameter.ActualValue = value; }
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| 75 | }
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[9152] | 76 | public BoolValue UpdateAlways {
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| 77 | get { return UpdateAlwaysParameter.Value; }
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| 78 | }
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[5557] | 79 | #endregion
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| 80 |
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| 81 | [StorableConstructor]
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| 82 | protected SymbolicDataAnalysisSingleObjectiveTrainingBestSolutionAnalyzer(bool deserializing) : base(deserializing) { }
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| 83 | protected SymbolicDataAnalysisSingleObjectiveTrainingBestSolutionAnalyzer(SymbolicDataAnalysisSingleObjectiveTrainingBestSolutionAnalyzer<T> original, Cloner cloner) : base(original, cloner) { }
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| 84 | public SymbolicDataAnalysisSingleObjectiveTrainingBestSolutionAnalyzer()
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| 85 | : base() {
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| 86 | Parameters.Add(new LookupParameter<T>(TrainingBestSolutionParameterName, "The training best symbolic data analyis solution."));
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[5607] | 87 | Parameters.Add(new LookupParameter<DoubleValue>(TrainingBestSolutionQualityParameterName, "The quality of the training best symbolic data analysis solution."));
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[10599] | 88 | Parameters.Add(new LookupParameter<IntValue>(TrainingBestSolutionGenerationParameterName, "The generation in which the best training solution was found."));
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[9152] | 89 | Parameters.Add(new FixedValueParameter<BoolValue>(UpdateAlwaysParameterName, "Determines if the best training solution should always be updated regardless of its quality.", new BoolValue(false)));
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[10599] | 90 | Parameters.Add(new LookupParameter<IntValue>(IterationsParameterName, "The number of performed iterations."));
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| 91 | Parameters.Add(new ValueLookupParameter<IntValue>(MaximumIterationsParameterName, "The maximum number of performed iterations.") { Hidden = true });
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[9152] | 92 | UpdateAlwaysParameter.Hidden = true;
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[5557] | 93 | }
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| 94 |
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[9152] | 95 | [StorableHook(HookType.AfterDeserialization)]
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| 96 | private void AfterDeserialization() {
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| 97 | if (!Parameters.ContainsKey(UpdateAlwaysParameterName)) {
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| 98 | Parameters.Add(new FixedValueParameter<BoolValue>(UpdateAlwaysParameterName, "Determines if the best training solution should always be updated regardless of its quality.", new BoolValue(false)));
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| 99 | UpdateAlwaysParameter.Hidden = true;
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| 100 | }
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[10599] | 101 | if (!Parameters.ContainsKey(TrainingBestSolutionGenerationParameterName))
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| 102 | Parameters.Add(new LookupParameter<IntValue>(TrainingBestSolutionGenerationParameterName, "The generation in which the best training solution was found."));
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| 103 | if (!Parameters.ContainsKey(IterationsParameterName))
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| 104 | Parameters.Add(new LookupParameter<IntValue>(IterationsParameterName, "The number of performed iterations."));
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| 105 | if (!Parameters.ContainsKey(MaximumIterationsParameterName))
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| 106 | Parameters.Add(new ValueLookupParameter<IntValue>(MaximumIterationsParameterName, "The maximum number of performed iterations.") { Hidden = true });
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[9152] | 107 | }
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| 108 |
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[5557] | 109 | public override IOperation Apply() {
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| 110 | #region find best tree
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| 111 | double bestQuality = Maximization.Value ? double.NegativeInfinity : double.PositiveInfinity;
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| 112 | ISymbolicExpressionTree bestTree = null;
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[5882] | 113 | ISymbolicExpressionTree[] tree = SymbolicExpressionTree.ToArray();
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[5557] | 114 | double[] quality = Quality.Select(x => x.Value).ToArray();
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| 115 | for (int i = 0; i < tree.Length; i++) {
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| 116 | if (IsBetter(quality[i], bestQuality, Maximization.Value)) {
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| 117 | bestQuality = quality[i];
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| 118 | bestTree = tree[i];
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| 119 | }
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| 120 | }
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| 121 | #endregion
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| 122 |
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| 123 | var results = ResultCollection;
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[9152] | 124 | if (bestTree != null && (UpdateAlways.Value || TrainingBestSolutionQuality == null ||
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[8798] | 125 | IsBetter(bestQuality, TrainingBestSolutionQuality.Value, Maximization.Value))) {
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[5557] | 126 | TrainingBestSolution = CreateSolution(bestTree, bestQuality);
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| 127 | TrainingBestSolutionQuality = new DoubleValue(bestQuality);
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[10599] | 128 | if (IterationsParameter.ActualValue != null)
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| 129 | TrainingBestSolutionGenerationParameter.ActualValue = new IntValue(IterationsParameter.ActualValue.Value);
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[5557] | 130 |
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[5747] | 131 | if (!results.ContainsKey(TrainingBestSolutionParameter.Name)) {
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| 132 | results.Add(new Result(TrainingBestSolutionParameter.Name, TrainingBestSolutionParameter.Description, TrainingBestSolution));
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| 133 | results.Add(new Result(TrainingBestSolutionQualityParameter.Name, TrainingBestSolutionQualityParameter.Description, TrainingBestSolutionQuality));
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[10599] | 134 | if (TrainingBestSolutionGenerationParameter.ActualValue != null)
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| 135 | results.Add(new Result(TrainingBestSolutionGenerationParameter.Name, TrainingBestSolutionGenerationParameter.Description, TrainingBestSolutionGenerationParameter.ActualValue));
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[5557] | 136 | } else {
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[5747] | 137 | results[TrainingBestSolutionParameter.Name].Value = TrainingBestSolution;
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| 138 | results[TrainingBestSolutionQualityParameter.Name].Value = TrainingBestSolutionQuality;
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[10599] | 139 | if (TrainingBestSolutionGenerationParameter.ActualValue != null)
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| 140 | results[TrainingBestSolutionGenerationParameter.Name].Value = TrainingBestSolutionGenerationParameter.ActualValue;
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| 141 |
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[5557] | 142 | }
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| 143 | }
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| 144 | return base.Apply();
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| 145 | }
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| 146 |
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| 147 | protected abstract T CreateSolution(ISymbolicExpressionTree bestTree, double bestQuality);
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| 148 |
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| 149 | private bool IsBetter(double lhs, double rhs, bool maximization) {
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| 150 | if (maximization) return lhs > rhs;
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| 151 | else return lhs < rhs;
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| 152 | }
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| 153 | }
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| 154 | }
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