source: branches/PushGP/HeuristicLab.PushGP/HeuristicLab.Problems.ProgramSynthesis/Push/Selector/LexicaseSelector.cs @ 14778

Last change on this file since 14778 was 14778, checked in by pkimmesw, 3 years ago

#2665 LexicaseSelector

File size: 5.8 KB
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1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2015 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.Parameters;
29using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
30using HeuristicLab.Random;
31using HeuristicLab.Selection;
32
33namespace HeuristicLab.Misc {
34  using HeuristicLab.Problems.ProgramSynthesis.Push.Selector;
35
36  /// <summary>
37  /// A lexicase selection operator which considers all successful evaluated training cases for selection.
38  ///
39  /// ToDo: LexicaseSelector and ICaseSingleObjectiveSelector are ISingleObjectiveOperator, which contains Maximization and Qualities which is not needed
40  /// </summary>
41  [Item("LexicaseSelector", "A lexicase selection operator which considers all successful evaluated training cases for selection.")]
42  [StorableClass]
43  public sealed class LexicaseSelector : StochasticSingleObjectiveSelector, ICaseSingleObjectiveSelector {
44    public ILookupParameter<ItemArray<DoubleArray>> CaseQualitiesParameter
45    {
46      get { return (ILookupParameter<ItemArray<DoubleArray>>)Parameters["CaseQualities"]; }
47    }
48
49    [StorableConstructor]
50    private LexicaseSelector(bool deserializing) : base(deserializing) { }
51    private LexicaseSelector(LexicaseSelector original, Cloner cloner) : base(original, cloner) { }
52    public override IDeepCloneable Clone(Cloner cloner) {
53      return new LexicaseSelector(this, cloner);
54    }
55
56    public LexicaseSelector()
57      : base() {
58      Parameters.Add(new ScopeTreeLookupParameter<DoubleArray>("CaseQualities", "The quality of every single training case for each individual."));
59    }
60
61    protected override IScope[] Select(List<IScope> scopes) {
62      int count = NumberOfSelectedSubScopesParameter.ActualValue.Value;
63      bool copy = CopySelectedParameter.Value.Value;
64      IRandom random = RandomParameter.ActualValue;
65      bool maximization = MaximizationParameter.ActualValue.Value;
66      List<double> qualities = QualityParameter.ActualValue.Where(x => IsValidQuality(x.Value)).Select(x => x.Value).ToList();
67      List<DoubleArray> caseQualities = CaseQualitiesParameter.ActualValue.ToList();
68
69      // remove scopes, qualities and case qualities, if the case qualities are empty
70      var removeindices = Enumerable.Range(0, caseQualities.Count)
71                                    .Zip(caseQualities, (i, c) => new { Index = i, CaseQuality = c })
72                                    .Where(c => c.CaseQuality.Count() == 0)
73                                    .Select(c => c.Index)
74                                    .Reverse();
75      foreach (var i in removeindices) {
76        scopes.RemoveAt(i);
77        qualities.RemoveAt(i);
78        caseQualities.RemoveAt(i);
79      }
80
81      if (caseQualities.Any(x => x.Count() != caseQualities[0].Length)) { throw new ArgumentException("Not all case qualities have the same length"); }
82
83      IScope[] selected = new IScope[count];
84
85      for (int i = 0; i < count; i++) {
86        int index = LexicaseSelect(caseQualities, RandomParameter.ActualValue, maximization);
87
88        if (copy)
89          selected[i] = (IScope)scopes[index].Clone();
90        else {
91          selected[i] = scopes[index];
92          scopes.RemoveAt(index);
93          qualities.RemoveAt(index);
94          caseQualities.RemoveAt(index);
95        }
96      }
97      return selected;
98    }
99
100    private int LexicaseSelect(List<DoubleArray> caseQualities, IRandom random, bool maximization) {
101      IList<int> candidates = Enumerable.Range(0, caseQualities.Count()).ToList();
102      IEnumerable<int> order = Enumerable.Range(0, caseQualities[0].Count()).Shuffle(random);
103
104      foreach (int curCase in order) {
105        List<int> nextCandidates = new List<int>();
106        double best = maximization ? double.NegativeInfinity : double.PositiveInfinity;
107        foreach (int candidate in candidates) {
108          if (caseQualities[candidate][curCase].IsAlmost(best)) {
109            // if the individuals is as good as the best one, add it
110            nextCandidates.Add(candidate);
111          } else if (((maximization) && (caseQualities[candidate][curCase] > best)) ||
112             ((!maximization) && (caseQualities[candidate][curCase] < best))) {
113            // if the individuals is better than the best one, remove all previous candidates and add the new one
114            nextCandidates.Clear();
115            nextCandidates.Add(candidate);
116            // also set the nes best quality value
117            best = caseQualities[candidate][curCase];
118          }
119          // else {do nothing}
120        }
121
122        if (nextCandidates.Count == 1) {
123          return nextCandidates.First();
124        } else if (nextCandidates.Count < 1) {
125          return candidates.SampleRandom(random);
126        }
127        candidates = nextCandidates;
128      }
129
130
131      if (candidates.Count == 1) {
132        return candidates.First();
133      }
134      return candidates.SampleRandom(random);
135    }
136  }
137}
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