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source: branches/DataPreprocessing/HeuristicLab.Problems.DataAnalysis.Symbolic/3.4/SymbolicExpressionTreeBacktransformator.cs @ 10880

Last change on this file since 10880 was 10880, checked in by tsteinre, 10 years ago
  • refined IModelBacktransformator
File size: 3.4 KB
RevLine 
[10854]1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2013 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 System.Linq;
[10878]24using HeuristicLab.Common;
[10854]25using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
26using HeuristicLab.Problems.DataAnalysis.Transformations;
27
28namespace HeuristicLab.Problems.DataAnalysis.Symbolic {
29  public class SymbolicExpressionTreeBacktransformator : IModelBacktransformator {
[10872]30    private readonly ITransformationMapper<ISymbolicExpressionTreeNode> transformationMapper;
[10854]31
[10872]32    public SymbolicExpressionTreeBacktransformator(ITransformationMapper<ISymbolicExpressionTreeNode> transformationMapper) {
[10854]33      this.transformationMapper = transformationMapper;
34    }
35
[10880]36    public void Backtransform(IDataAnalysisModel model, IEnumerable<ITransformation> transformations, string targetVariable) {
[10854]37      var symbolicModel = (ISymbolicDataAnalysisModel)model;
38
39      foreach (var transformation in transformations) {
[10880]40        ApplyBacktransformation(transformation, symbolicModel.SymbolicExpressionTree, targetVariable);
[10854]41      }
42    }
43
[10880]44    private void ApplyBacktransformation(ITransformation transformation, ISymbolicExpressionTree symbolicExpressionTree, string targetVariable) {
[10869]45      var variableNodes = symbolicExpressionTree.IterateNodesBreadth()
[10874]46        .OfType<VariableTreeNode>()
47        .Where(n => n.VariableName == transformation.Column);
[10869]48
49      foreach (var variableNode in variableNodes) {
[10878]50        // generate new subtrees because same subtree cannot be added more than once
51        var transformationTree = transformationMapper.GenerateModel(transformation);
[10874]52        SwapTransformationWithVariable(transformationTree, variableNode);
[10869]53      }
[10854]54    }
55
[10874]56    private void SwapTransformationWithVariable(ISymbolicExpressionTreeNode transformationTree, VariableTreeNode variableNode) {
57      var parent = variableNode.Parent;
58      int index = parent.IndexOfSubtree(variableNode);
[10869]59      parent.RemoveSubtree(index);
60
[10878]61      if (!variableNode.Weight.IsAlmost(1.0)) {
62        transformationTree = CreateNodeFromWeight(transformationTree, variableNode);
63      }
64
65      parent.InsertSubtree(index, transformationTree);
66    }
67
68    private ISymbolicExpressionTreeNode CreateNodeFromWeight(ISymbolicExpressionTreeNode transformationTree, VariableTreeNode variableNode) {
[10874]69      var multiplicationNode = new SymbolicExpressionTreeNode(new Multiplication());
70      multiplicationNode.AddSubtree(new ConstantTreeNode(new Constant()) { Value = variableNode.Weight });
71      multiplicationNode.AddSubtree(transformationTree);
[10878]72      transformationTree = multiplicationNode;
73      return transformationTree;
[10854]74    }
75  }
76}
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