source: branches/2839_HiveProjectManagement/HeuristicLab.Problems.DataAnalysis.Symbolic/3.4/Analyzers/SymbolicDataAnalysisMultiObjectiveValidationBestSolutionAnalyzer.cs @ 16057

Last change on this file since 16057 was 16057, checked in by jkarder, 4 years ago

#2839:

File size: 9.6 KB
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1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2018 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
4 *
5 * This file is part of HeuristicLab.
6 *
7 * HeuristicLab is free software: you can redistribute it and/or modify
8 * it under the terms of the GNU General Public License as published by
9 * the Free Software Foundation, either version 3 of the License, or
10 * (at your option) any later version.
11 *
12 * HeuristicLab is distributed in the hope that it will be useful,
13 * but WITHOUT ANY WARRANTY; without even the implied warranty of
14 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
15 * GNU General Public License for more details.
16 *
17 * You should have received a copy of the GNU General Public License
18 * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
19 */
20#endregion
21
22using System;
23using System.Collections.Generic;
24using System.Linq;
25using HeuristicLab.Common;
26using HeuristicLab.Core;
27using HeuristicLab.Data;
28using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
29using HeuristicLab.Optimization;
30using HeuristicLab.Parameters;
31using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
32
33namespace HeuristicLab.Problems.DataAnalysis.Symbolic {
34  /// <summary>
35  /// An operator that analyzes the validation best symbolic data analysis solution for multi objective symbolic data analysis problems.
36  /// </summary>
37  [Item("SymbolicDataAnalysisMultiObjectiveValidationBestSolutionAnalyzer", "An operator that analyzes the validation best symbolic data analysis solution for multi objective symbolic data analysis problems.")]
38  [StorableClass]
39  public abstract class SymbolicDataAnalysisMultiObjectiveValidationBestSolutionAnalyzer<S, T, U> : SymbolicDataAnalysisMultiObjectiveValidationAnalyzer<T, U>,
40    ISymbolicDataAnalysisMultiObjectiveAnalyzer
41    where S : class, ISymbolicDataAnalysisSolution
42    where T : class, ISymbolicDataAnalysisMultiObjectiveEvaluator<U>
43    where U : class, IDataAnalysisProblemData {
44    private const string ValidationBestSolutionsParameterName = "Best validation solutions";
45    private const string ValidationBestSolutionQualitiesParameterName = "Best validation solution qualities";
46    private const string UpdateAlwaysParameterName = "Always update best solutions";
47
48    #region parameter properties
49    public ILookupParameter<ItemList<S>> ValidationBestSolutionsParameter {
50      get { return (ILookupParameter<ItemList<S>>)Parameters[ValidationBestSolutionsParameterName]; }
51    }
52    public ILookupParameter<ItemList<DoubleArray>> ValidationBestSolutionQualitiesParameter {
53      get { return (ILookupParameter<ItemList<DoubleArray>>)Parameters[ValidationBestSolutionQualitiesParameterName]; }
54    }
55    public IFixedValueParameter<BoolValue> UpdateAlwaysParameter {
56      get { return (IFixedValueParameter<BoolValue>)Parameters[UpdateAlwaysParameterName]; }
57    }
58    #endregion
59    #region properties
60    public ItemList<S> ValidationBestSolutions {
61      get { return ValidationBestSolutionsParameter.ActualValue; }
62      set { ValidationBestSolutionsParameter.ActualValue = value; }
63    }
64    public ItemList<DoubleArray> ValidationBestSolutionQualities {
65      get { return ValidationBestSolutionQualitiesParameter.ActualValue; }
66      set { ValidationBestSolutionQualitiesParameter.ActualValue = value; }
67    }
68    public BoolValue UpdateAlways {
69      get { return UpdateAlwaysParameter.Value; }
70    }
71    #endregion
72
73    [StorableConstructor]
74    protected SymbolicDataAnalysisMultiObjectiveValidationBestSolutionAnalyzer(bool deserializing) : base(deserializing) { }
75    protected SymbolicDataAnalysisMultiObjectiveValidationBestSolutionAnalyzer(SymbolicDataAnalysisMultiObjectiveValidationBestSolutionAnalyzer<S, T, U> original, Cloner cloner) : base(original, cloner) { }
76    public SymbolicDataAnalysisMultiObjectiveValidationBestSolutionAnalyzer()
77      : base() {
78      Parameters.Add(new LookupParameter<ItemList<S>>(ValidationBestSolutionsParameterName, "The validation best (Pareto-optimal) symbolic data analysis solutions."));
79      Parameters.Add(new LookupParameter<ItemList<DoubleArray>>(ValidationBestSolutionQualitiesParameterName, "The qualities of the validation best (Pareto-optimal) solutions."));
80      Parameters.Add(new FixedValueParameter<BoolValue>(UpdateAlwaysParameterName, "Determines if the best validation solutions should always be updated regardless of its quality.", new BoolValue(false)));
81      UpdateAlwaysParameter.Hidden = true;
82    }
83
84    [StorableHook(HookType.AfterDeserialization)]
85    private void AfterDeserialization() {
86      if (!Parameters.ContainsKey(UpdateAlwaysParameterName)) {
87        Parameters.Add(new FixedValueParameter<BoolValue>(UpdateAlwaysParameterName, "Determines if the best training solutions should always be updated regardless of its quality.", new BoolValue(false)));
88        UpdateAlwaysParameter.Hidden = true;
89      }
90    }
91
92    public override IOperation Apply() {
93      IEnumerable<int> rows = GenerateRowsToEvaluate();
94      if (!rows.Any()) return base.Apply();
95
96      var results = ResultCollection;
97      // create empty parameter and result values
98      if (ValidationBestSolutions == null) {
99        ValidationBestSolutions = new ItemList<S>();
100        ValidationBestSolutionQualities = new ItemList<DoubleArray>();
101        results.Add(new Result(ValidationBestSolutionQualitiesParameter.Name, ValidationBestSolutionQualitiesParameter.Description, ValidationBestSolutionQualities));
102        results.Add(new Result(ValidationBestSolutionsParameter.Name, ValidationBestSolutionsParameter.Description, ValidationBestSolutions));
103      }
104
105      //if the pareto front of best solutions shall be updated regardless of the quality, the list initialized empty to discard old solutions
106      IList<double[]> trainingBestQualities;
107      if (UpdateAlways.Value) {
108        trainingBestQualities = new List<double[]>();
109      } else {
110        trainingBestQualities = ValidationBestSolutionQualities.Select(x => x.ToArray()).ToList();
111      }
112
113      #region find best trees
114      IList<int> nonDominatedIndexes = new List<int>();
115      ISymbolicExpressionTree[] tree = SymbolicExpressionTree.ToArray();
116      bool[] maximization = Maximization.ToArray();
117      List<double[]> newNonDominatedQualities = new List<double[]>();
118      var evaluator = EvaluatorParameter.ActualValue;
119      var problemData = ProblemDataParameter.ActualValue;
120      IExecutionContext childContext = (IExecutionContext)ExecutionContext.CreateChildOperation(evaluator);
121
122      var qualities = tree
123        .Select(t => evaluator.Evaluate(childContext, t, problemData, rows))
124        .ToArray();
125      for (int i = 0; i < tree.Length; i++) {
126        if (IsNonDominated(qualities[i], trainingBestQualities, maximization) &&
127          IsNonDominated(qualities[i], qualities, maximization)) {
128          if (!newNonDominatedQualities.Contains(qualities[i], new DoubleArrayComparer())) {
129            newNonDominatedQualities.Add(qualities[i]);
130            nonDominatedIndexes.Add(i);
131          }
132        }
133      }
134      #endregion
135      #region update Pareto-optimal solution archive
136      if (nonDominatedIndexes.Count > 0) {
137        ItemList<DoubleArray> nonDominatedQualities = new ItemList<DoubleArray>();
138        ItemList<S> nonDominatedSolutions = new ItemList<S>();
139        // add all new non-dominated solutions to the archive
140        foreach (var index in nonDominatedIndexes) {
141          S solution = CreateSolution(tree[index], qualities[index]);
142          nonDominatedSolutions.Add(solution);
143          nonDominatedQualities.Add(new DoubleArray(qualities[index]));
144        }
145        // add old non-dominated solutions only if they are not dominated by one of the new solutions
146        for (int i = 0; i < trainingBestQualities.Count; i++) {
147          if (IsNonDominated(trainingBestQualities[i], newNonDominatedQualities, maximization)) {
148            if (!newNonDominatedQualities.Contains(trainingBestQualities[i], new DoubleArrayComparer())) {
149              nonDominatedSolutions.Add(ValidationBestSolutions[i]);
150              nonDominatedQualities.Add(ValidationBestSolutionQualities[i]);
151            }
152          }
153        }
154
155        results[ValidationBestSolutionsParameter.Name].Value = nonDominatedSolutions;
156        results[ValidationBestSolutionQualitiesParameter.Name].Value = nonDominatedQualities;
157      }
158      #endregion
159      return base.Apply();
160    }
161
162    protected abstract S CreateSolution(ISymbolicExpressionTree bestTree, double[] bestQuality);
163
164    private bool IsNonDominated(double[] point, IList<double[]> points, bool[] maximization) {
165      foreach (var refPoint in points) {
166        bool refPointDominatesPoint = true;
167        for (int i = 0; i < point.Length; i++) {
168          refPointDominatesPoint &= IsBetter(refPoint[i], point[i], maximization[i]);
169        }
170        if (refPointDominatesPoint) return false;
171      }
172      return true;
173    }
174    private bool IsBetter(double lhs, double rhs, bool maximization) {
175      if (maximization) return lhs > rhs;
176      else return lhs < rhs;
177    }
178
179    private class DoubleArrayComparer : IEqualityComparer<double[]> {
180      public bool Equals(double[] x, double[] y) {
181        if (y.Length != x.Length) throw new ArgumentException();
182        for (int i = 0; i < x.Length; i++) {
183          if (!x[i].IsAlmost(y[i])) return false;
184        }
185        return true;
186      }
187
188      public int GetHashCode(double[] obj) {
189        int c = obj.Length;
190        for (int i = 0; i < obj.Length; i++)
191          c ^= obj[i].GetHashCode();
192        return c;
193      }
194    }
195
196  }
197}
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