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source: branches/DataPreprocessing/HeuristicLab.Problems.DataAnalysis.Symbolic/3.4/SymbolicExpressionTreeBacktransformator.cs @ 10854

Last change on this file since 10854 was 10854, checked in by pfleck, 10 years ago
  • Started implementing backtransforming of model with preprocessing transformations.
File size: 2.3 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;
24using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
25using HeuristicLab.Problems.DataAnalysis.Transformations;
26
27namespace HeuristicLab.Problems.DataAnalysis.Symbolic {
28  public class SymbolicExpressionTreeBacktransformator : IModelBacktransformator {
29    private readonly ITransformationMapper<ISymbolicExpressionTree> transformationMapper;
30
31    public SymbolicExpressionTreeBacktransformator(ITransformationMapper<ISymbolicExpressionTree> transformationMapper) {
32      this.transformationMapper = transformationMapper;
33    }
34
35    public IDataAnalysisModel Backtransform(IDataAnalysisModel model, IEnumerable<ITransformation> transformations) {
36      var symbolicModel = (ISymbolicDataAnalysisModel)model;
37
38      foreach (var transformation in transformations) {
39        ApplyBacktransformation(transformation, symbolicModel.SymbolicExpressionTree);
40      }
41
42      return symbolicModel;
43    }
44
45    private void ApplyBacktransformation(ITransformation transformation, ISymbolicExpressionTree symbolicExpressionTree) {
46      bool modelHasVariable = symbolicExpressionTree.IterateNodesBreadth().Any(n => IsVariableNode(n, transformation.Column));
47      // TODO
48    }
49
50    private bool IsVariableNode(ISymbolicExpressionTreeNode node, string variableName) {
51      var variableNode = node as VariableTreeNode;
52      if (variableNode == null) return false;
53      return variableNode.VariableName == variableName;
54    }
55  }
56}
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