source: branches/HeuristicLab.EvolutionaryTracking/HeuristicLab.Problems.DataAnalysis.Symbolic/3.4/SymbolicDataAnalysisSolutionValuesCalculator.cs @ 9835

Last change on this file since 9835 was 9835, checked in by bburlacu, 8 years ago

#1772: Merged remaining trunk changes into the EvolutionaryTracking branch.

File size: 3.4 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.Collections.Generic;
23using HeuristicLab.Common;
24using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
25
26namespace HeuristicLab.Problems.DataAnalysis.Symbolic {
27  public abstract class SymbolicDataAnalysisSolutionValuesCalculator {
28    protected readonly ISymbolicExpressionTree tempTree;
29    protected readonly ConstantTreeNode constantNode;
30
31    public SymbolicDataAnalysisSolutionValuesCalculator() {
32      constantNode = ((ConstantTreeNode)new Constant().CreateTreeNode());
33      ISymbolicExpressionTreeNode root = new ProgramRootSymbol().CreateTreeNode();
34      ISymbolicExpressionTreeNode start = new StartSymbol().CreateTreeNode();
35      root.AddSubtree(start);
36      tempTree = new SymbolicExpressionTree(root);
37    }
38
39    // should be moved to an interface, then un-abstract the class
40    public abstract Dictionary<ISymbolicExpressionTreeNode, double> CalculateReplacementValues(ISymbolicExpressionTree tree, ISymbolicDataAnalysisExpressionTreeInterpreter interpreter, IDataAnalysisProblemData problemData);
41    public abstract Dictionary<ISymbolicExpressionTreeNode, double> CalculateImpactValues(ISymbolicExpressionTree tree, ISymbolicDataAnalysisExpressionTreeInterpreter interpreter, IDataAnalysisProblemData problemData, double lowerEstimationLimit, double upperEstimationLimit);
42
43    protected void SwitchNode(ISymbolicExpressionTreeNode root, ISymbolicExpressionTreeNode oldBranch, ISymbolicExpressionTreeNode newBranch) {
44      for (int i = 0; i < root.SubtreeCount; i++) {
45        if (root.GetSubtree(i) == oldBranch) {
46          root.RemoveSubtree(i);
47          root.InsertSubtree(i, newBranch);
48          return;
49        }
50      }
51    }
52
53    protected double CalculateReplacementValue(ISymbolicExpressionTreeNode node, ISymbolicExpressionTree sourceTree, ISymbolicDataAnalysisExpressionTreeInterpreter interpreter, IDataAnalysisProblemData problemData) {
54      // remove old ADFs
55      while (tempTree.Root.SubtreeCount > 1) tempTree.Root.RemoveSubtree(1);
56      // clone ADFs of source tree
57      for (int i = 1; i < sourceTree.Root.SubtreeCount; i++) {
58        tempTree.Root.AddSubtree((ISymbolicExpressionTreeNode)sourceTree.Root.GetSubtree(i).Clone());
59      }
60      var start = tempTree.Root.GetSubtree(0);
61      while (start.SubtreeCount > 0) start.RemoveSubtree(0);
62      start.AddSubtree((ISymbolicExpressionTreeNode)node.Clone());
63      var rows = problemData.TrainingIndices;
64      return interpreter.GetSymbolicExpressionTreeValues(tempTree, problemData.Dataset, rows).Median();
65    }
66  }
67}
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