source: trunk/sources/HeuristicLab.Problems.DataAnalysis.Symbolic/3.4/Crossovers/MultiSymbolicDataAnalysisExpressionCrossover.cs @ 7521

Last change on this file since 7521 was 7521, checked in by mkommend, 8 years ago

#1682: Forbid name changes in new gp crossovers

File size: 10.7 KB
Line 
1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2012 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.Linq;
24using HeuristicLab.Collections;
25using HeuristicLab.Common;
26using HeuristicLab.Core;
27using HeuristicLab.Data;
28using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
29using HeuristicLab.Operators;
30using HeuristicLab.Optimization;
31using HeuristicLab.Parameters;
32using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
33using HeuristicLab.PluginInfrastructure;
34
35namespace HeuristicLab.Problems.DataAnalysis.Symbolic {
36  [Item("MultiSymbolicDataAnalysisExpressionCrossover", "Randomly selects and applies one of its crossovers every time it is called.")]
37  public class MultiSymbolicDataAnalysisExpressionCrossover<T> : StochasticMultiBranch<ISymbolicExpressionTreeCrossover>,
38    ISymbolicDataAnalysisExpressionCrossover<T> where T : class, IDataAnalysisProblemData {
39    private const string ParentsParameterName = "Parents";
40    private const string ChildParameterName = "Child";
41    private const string MaximumSymbolicExpressionTreeLengthParameterName = "MaximumSymbolicExpressionTreeLength";
42    private const string MaximumSymbolicExpressionTreeDepthParameterName = "MaximumSymbolicExpressionTreeDepth";
43    private const string SymbolicDataAnalysisTreeInterpreterParameterName = "SymbolicExpressionTreeInterpreter";
44    private const string EvaluatorParameterName = "Evaluator";
45    private const string SymbolicDataAnalysisEvaluationPartitionParameterName = "EvaluationPartition";
46    private const string RelativeNumberOfEvaluatedSamplesParameterName = "RelativeNumberOfEvaluatedSamples";
47    private const string ProblemDataParameterName = "ProblemData";
48
49    protected override bool CreateChildOperation {
50      get { return true; }
51    }
52
53    public override bool CanChangeName {
54      get { return false; }
55    }
56
57    #region parameter properties
58    public ILookupParameter<ISymbolicDataAnalysisExpressionTreeInterpreter> SymbolicDataAnalysisTreeInterpreterParameter {
59      get { return (ILookupParameter<ISymbolicDataAnalysisExpressionTreeInterpreter>)Parameters[SymbolicDataAnalysisTreeInterpreterParameterName]; }
60    }
61    public ILookupParameter<ItemArray<ISymbolicExpressionTree>> ParentsParameter {
62      get { return (ScopeTreeLookupParameter<ISymbolicExpressionTree>)Parameters[ParentsParameterName]; }
63    }
64    public ILookupParameter<ISymbolicExpressionTree> ChildParameter {
65      get { return (ILookupParameter<ISymbolicExpressionTree>)Parameters[ChildParameterName]; }
66    }
67    public IValueLookupParameter<IntValue> MaximumSymbolicExpressionTreeLengthParameter {
68      get { return (IValueLookupParameter<IntValue>)Parameters[MaximumSymbolicExpressionTreeLengthParameterName]; }
69    }
70    public IValueLookupParameter<IntValue> MaximumSymbolicExpressionTreeDepthParameter {
71      get { return (IValueLookupParameter<IntValue>)Parameters[MaximumSymbolicExpressionTreeDepthParameterName]; }
72    }
73    public ILookupParameter<ISymbolicDataAnalysisSingleObjectiveEvaluator<T>> EvaluatorParameter {
74      get { return (ILookupParameter<ISymbolicDataAnalysisSingleObjectiveEvaluator<T>>)Parameters[EvaluatorParameterName]; }
75    }
76    public IValueLookupParameter<IntRange> EvaluationPartitionParameter {
77      get { return (IValueLookupParameter<IntRange>)Parameters[SymbolicDataAnalysisEvaluationPartitionParameterName]; }
78    }
79    public IValueLookupParameter<PercentValue> RelativeNumberOfEvaluatedSamplesParameter {
80      get { return (IValueLookupParameter<PercentValue>)Parameters[RelativeNumberOfEvaluatedSamplesParameterName]; }
81    }
82    public IValueLookupParameter<T> ProblemDataParameter {
83      get { return (IValueLookupParameter<T>)Parameters[ProblemDataParameterName]; }
84    }
85    #endregion
86
87    [StorableConstructor]
88    protected MultiSymbolicDataAnalysisExpressionCrossover(bool deserializing) : base(deserializing) { }
89    protected MultiSymbolicDataAnalysisExpressionCrossover(MultiSymbolicDataAnalysisExpressionCrossover<T> original, Cloner cloner) : base(original, cloner) { }
90    public override IDeepCloneable Clone(Cloner cloner) { return new MultiSymbolicDataAnalysisExpressionCrossover<T>(this, cloner); }
91    public MultiSymbolicDataAnalysisExpressionCrossover()
92      : base() {
93      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."));
94      Parameters.Add(new ValueLookupParameter<T>(ProblemDataParameterName, "The problem data on which the symbolic data analysis solution should be evaluated."));
95      Parameters.Add(new LookupParameter<ISymbolicDataAnalysisExpressionTreeInterpreter>(SymbolicDataAnalysisTreeInterpreterParameterName, "The interpreter that should be used to calculate the output values of the symbolic data analysis tree."));
96      Parameters.Add(new ValueLookupParameter<IntValue>(MaximumSymbolicExpressionTreeLengthParameterName, "The maximal length (number of nodes) of the symbolic expression tree."));
97      Parameters.Add(new ValueLookupParameter<IntValue>(MaximumSymbolicExpressionTreeDepthParameterName, "The maximal depth of the symbolic expression tree (a tree with one node has depth = 0)."));
98      Parameters.Add(new LookupParameter<ISymbolicDataAnalysisSingleObjectiveEvaluator<T>>(EvaluatorParameterName, "The single objective solution evaluator"));
99      Parameters.Add(new ValueLookupParameter<IntRange>(SymbolicDataAnalysisEvaluationPartitionParameterName, "The start index of the dataset partition on which the symbolic data analysis solution should be evaluated."));
100      Parameters.Add(new ScopeTreeLookupParameter<ISymbolicExpressionTree>(ParentsParameterName, "The parent symbolic expression trees which should be crossed."));
101      Parameters.Add(new LookupParameter<ISymbolicExpressionTree>(ChildParameterName, "The child symbolic expression tree resulting from the crossover."));
102
103      EvaluatorParameter.Hidden = true;
104      EvaluationPartitionParameter.Hidden = true;
105      SymbolicDataAnalysisTreeInterpreterParameter.Hidden = true;
106      ProblemDataParameter.Hidden = true;
107      RelativeNumberOfEvaluatedSamplesParameter.Hidden = true;
108
109      InitializeOperators();
110      name = "MultiSymbolicDataAnalysisExpressionCrossover";
111    }
112
113    private void InitializeOperators() {
114      var list = ApplicationManager.Manager.GetInstances<ISymbolicExpressionTreeCrossover>().ToList();
115      var dataAnalysisCrossovers = from type in ApplicationManager.Manager.GetTypes(typeof(ISymbolicDataAnalysisExpressionCrossover<T>))
116                                   where this.GetType().Assembly == type.Assembly
117                                   where !typeof(IMultiOperator<ISymbolicExpressionTreeCrossover>).IsAssignableFrom(type)
118                                   select (ISymbolicDataAnalysisExpressionCrossover<T>)Activator.CreateInstance(type);
119      list.AddRange(dataAnalysisCrossovers);
120
121      var checkedItemList = new CheckedItemList<ISymbolicExpressionTreeCrossover>();
122      checkedItemList.AddRange(list.OrderBy(op => op.Name));
123      Operators = checkedItemList;
124      Operators_ItemsAdded(this, new CollectionItemsChangedEventArgs<IndexedItem<ISymbolicExpressionTreeCrossover>>(Operators.CheckedItems));
125    }
126
127    public ISymbolicExpressionTree Crossover(IRandom random, ISymbolicExpressionTree parent0, ISymbolicExpressionTree parent1) {
128      double sum = Operators.CheckedItems.Sum(o => Probabilities[o.Index]);
129      if (sum.IsAlmost(0)) throw new InvalidOperationException(Name + ": All selected operators have zero probability.");
130      double r = random.NextDouble() * sum;
131      sum = 0;
132      int index = -1;
133      foreach (var indexedItem in Operators.CheckedItems) {
134        sum += Probabilities[indexedItem.Index];
135        if (sum > r) {
136          index = indexedItem.Index;
137          break;
138        }
139      }
140      return Operators[index].Crossover(random, parent0, parent1);
141    }
142
143    protected override void Operators_ItemsReplaced(object sender, CollectionItemsChangedEventArgs<IndexedItem<ISymbolicExpressionTreeCrossover>> e) {
144      base.Operators_ItemsReplaced(sender, e);
145      ParameterizeCrossovers();
146    }
147
148    protected override void Operators_ItemsAdded(object sender, CollectionItemsChangedEventArgs<IndexedItem<ISymbolicExpressionTreeCrossover>> e) {
149      base.Operators_ItemsAdded(sender, e);
150      ParameterizeCrossovers();
151    }
152
153    private void ParameterizeCrossovers() {
154      foreach (ISymbolicExpressionTreeCrossover op in Operators) {
155        op.ChildParameter.ActualName = ChildParameter.Name;
156        op.ParentsParameter.ActualName = ParentsParameter.Name;
157      }
158      foreach (IStochasticOperator op in Operators.OfType<IStochasticOperator>()) {
159        op.RandomParameter.ActualName = RandomParameter.Name;
160      }
161      foreach (ISymbolicExpressionTreeSizeConstraintOperator op in Operators.OfType<ISymbolicExpressionTreeSizeConstraintOperator>()) {
162        op.MaximumSymbolicExpressionTreeDepthParameter.ActualName = MaximumSymbolicExpressionTreeDepthParameter.Name;
163        op.MaximumSymbolicExpressionTreeLengthParameter.ActualName = MaximumSymbolicExpressionTreeLengthParameter.Name;
164      }
165
166      foreach (ISymbolicDataAnalysisInterpreterOperator op in Operators.OfType<ISymbolicDataAnalysisInterpreterOperator>()) {
167        op.SymbolicDataAnalysisTreeInterpreterParameter.ActualName = SymbolicDataAnalysisTreeInterpreterParameter.Name;
168      }
169      foreach (var op in Operators.OfType<ISymbolicDataAnalysisExpressionCrossover<T>>()) {
170        op.ProblemDataParameter.ActualName = ProblemDataParameter.Name;
171        op.EvaluationPartitionParameter.ActualName = EvaluationPartitionParameter.Name;
172        op.RelativeNumberOfEvaluatedSamplesParameter.ActualName = RelativeNumberOfEvaluatedSamplesParameter.Name;
173        op.EvaluatorParameter.ActualName = EvaluatorParameter.Name;
174      }
175    }
176  }
177}
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