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source: branches/HeuristicLab.Crossovers/HeuristicLab.Problems.DataAnalysis.Symbolic/3.4/Crossovers/SymbolicDataAnalysisExpressionDeterministicBestCrossover.cs @ 7476

Last change on this file since 7476 was 7476, checked in by bburlacu, 12 years ago

#1682: Added crossovers.

File size: 6.6 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.Collections.Generic;
24using System.Linq;
25using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
26using HeuristicLab.Common;
27using HeuristicLab.Core;
28using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
29
30namespace HeuristicLab.Problems.DataAnalysis.Symbolic {
31
32  [Item("DeterministicBestCrossover", "An operator which performs subtree swapping in a deterministic way, by choosing the best subtree to be swapped in a certain position.")]
33  public sealed class SymbolicDataAnalysisExpressionDeterministicBestCrossover<T> : SymbolicDataAnalysisExpressionCrossover<T> where T : class, IDataAnalysisProblemData {
34    [StorableConstructor]
35    private SymbolicDataAnalysisExpressionDeterministicBestCrossover(bool deserializing) : base(deserializing) { }
36    private SymbolicDataAnalysisExpressionDeterministicBestCrossover(SymbolicDataAnalysisExpressionCrossover<T> original, Cloner cloner)
37      : base(original, cloner) {
38    }
39    public SymbolicDataAnalysisExpressionDeterministicBestCrossover()
40      : base() {
41      Name = "DeterministicBestCrossover";
42    }
43    public override IDeepCloneable Clone(Cloner cloner) {
44      return new SymbolicDataAnalysisExpressionDeterministicBestCrossover<T>(this, cloner);
45    }
46    protected override ISymbolicExpressionTree Cross(IRandom random, ISymbolicExpressionTree parent0, ISymbolicExpressionTree parent1) {
47      if (this.ExecutionContext == null)
48        throw new InvalidOperationException("ExecutionContext not set.");
49      List<int> rows = GenerateRowsToEvaluate().ToList();
50      T problemData = ProblemDataParameter.ActualValue;
51      ISymbolicDataAnalysisSingleObjectiveEvaluator<T> evaluator = EvaluatorParameter.ActualValue;
52
53      return Cross(random, parent0, parent1, this.ExecutionContext, evaluator, problemData, rows, MaximumSymbolicExpressionTreeDepth.Value, MaximumSymbolicExpressionTreeLength.Value);
54    }
55
56    public override ISymbolicExpressionTree Crossover(IRandom random, ISymbolicExpressionTree parent0, ISymbolicExpressionTree parent1) {
57      return Cross(random, parent0, parent1);
58    }
59    /// <summary>
60    /// Takes two parent individuals P0 and P1.
61    /// Randomly choose a node i from the first parent, then test all nodes j from the second parent to determine the best child that would be obtained by swapping i for j.
62    /// </summary>
63    public static ISymbolicExpressionTree Cross(IRandom random, ISymbolicExpressionTree parent0, ISymbolicExpressionTree parent1, IExecutionContext context,
64                                                ISymbolicDataAnalysisSingleObjectiveEvaluator<T> evaluator, T problemData, List<int> rows, int maxDepth, int maxLength) {
65      var crossoverPoints0 = new List<CutPoint>();
66      parent0.Root.ForEachNodePostfix((n) => {
67        if (n.Subtrees.Any() && n != parent0.Root)
68          crossoverPoints0.AddRange(from s in n.Subtrees select new CutPoint(n, s));
69      });
70      CutPoint crossoverPoint0 = crossoverPoints0.SelectRandom(random);
71      int level = parent0.Root.GetBranchLevel(crossoverPoint0.Child);
72      int length = parent0.Root.GetLength() - crossoverPoint0.Child.GetLength();
73
74      var allowedBranches = new List<ISymbolicExpressionTreeNode>();
75      parent1.Root.ForEachNodePostfix((n) => {
76        if (n.Subtrees.Any() && n != parent1.Root)
77          allowedBranches.AddRange(from s in n.Subtrees
78                                   where crossoverPoint0.IsMatchingPointType(s) && s.GetDepth() + level <= maxDepth && s.GetLength() + length <= maxLength
79                                   select s);
80      });
81
82      if (allowedBranches.Count == 0)
83        return parent0;
84
85      // create symbols in order to improvize an ad-hoc tree so that the child can be evaluated
86      ISymbolicExpressionTreeNode selectedBranch = null;
87
88      var nodeQualities = new List<Tuple<ISymbolicExpressionTreeNode, double>>();
89
90      var originalChild = crossoverPoint0.Child;
91
92      foreach (var node in allowedBranches) {
93        var parent = node.Parent;
94        swap(crossoverPoint0, node); // the swap will set the nodes parent to crossoverPoint0.Parent
95        double quality = evaluator.Evaluate(context, parent0, problemData, rows);
96        swap(crossoverPoint0, originalChild); // swap the child back (so that the next swap will not affect the currently swapped node from parent1)
97        nodeQualities.Add(new Tuple<ISymbolicExpressionTreeNode, double>(node, quality));
98        node.Parent = parent; // restore correct parent
99      }
100
101      nodeQualities.Sort((a, b) => a.Item2.CompareTo(b.Item2)); // assuming this sorts the list in ascending order
102      selectedBranch = evaluator.Maximization ? nodeQualities.Last().Item1 : nodeQualities.First().Item1;
103
104
105      if (selectedBranch == null)
106        throw new Exception("Selected branch is null");
107
108      if (selectedBranch.Parent == null)
109        throw new Exception("Parent is null");
110
111
112      // swap the node that would create the best offspring
113      swap(crossoverPoint0, selectedBranch);
114
115      return parent0;
116    }
117
118    private static void swap(CutPoint crossoverPoint, ISymbolicExpressionTreeNode selectedBranch) {
119      if (crossoverPoint.Child != null) {
120        // manipulate the tree of parent0 in place
121        // replace the branch in tree0 with the selected branch from tree1
122        crossoverPoint.Parent.RemoveSubtree(crossoverPoint.ChildIndex);
123        if (selectedBranch != null) {
124          crossoverPoint.Parent.InsertSubtree(crossoverPoint.ChildIndex, selectedBranch);
125        }
126      } else {
127        // child is null (additional child should be added under the parent)
128        if (selectedBranch != null) {
129          crossoverPoint.Parent.AddSubtree(selectedBranch);
130        }
131      }
132    }
133  }
134}
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