source: branches/DataAnalysis Refactoring/HeuristicLab.Problems.DataAnalysis.Symbolic.Classification/3.4/SymbolicClassificationSolution.cs @ 5736

Last change on this file since 5736 was 5736, checked in by gkronber, 11 years ago

#1418 implemented linear scaling for classification solutions, fixed bugs interactive simplifier view for classification solutions.

File size: 3.6 KB
Line 
1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2011 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.Common;
25using HeuristicLab.Core;
26using HeuristicLab.Data;
27using HeuristicLab.Encodings.SymbolicExpressionTreeEncoding;
28using HeuristicLab.Operators;
29using HeuristicLab.Parameters;
30using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
31using HeuristicLab.Optimization;
32using System;
33
34namespace HeuristicLab.Problems.DataAnalysis.Symbolic.Classification {
35  /// <summary>
36  /// Represents a symbolic classification solution (model + data) and attributes of the solution like accuracy and complexity
37  /// </summary>
38  [StorableClass]
39  [Item(Name = "SymbolicClassificationSolution", Description = "Represents a symbolic classification solution (model + data) and attributes of the solution like accuracy and complexity.")]
40  public sealed class SymbolicClassificationSolution : ClassificationSolution, ISymbolicClassificationSolution {
41    private const string ModelLengthResultName = "ModelLength";
42    private const string ModelDepthResultName = "ModelDepth";
43
44    public new ISymbolicClassificationModel Model {
45      get { return (ISymbolicClassificationModel)base.Model; }
46      set { base.Model = value; }
47    }
48
49    ISymbolicDataAnalysisModel ISymbolicDataAnalysisSolution.Model {
50      get { return (ISymbolicDataAnalysisModel)base.Model; }
51    }
52    public int ModelLength {
53      get { return ((IntValue)this[ModelLengthResultName].Value).Value; }
54      private set { ((IntValue)this[ModelLengthResultName].Value).Value = value; }
55    }
56
57    public int ModelDepth {
58      get { return ((IntValue)this[ModelDepthResultName].Value).Value; }
59      private set { ((IntValue)this[ModelDepthResultName].Value).Value = value; }
60    }
61
62    [StorableConstructor]
63    private SymbolicClassificationSolution(bool deserializing) : base(deserializing) { }
64    private SymbolicClassificationSolution(SymbolicClassificationSolution original, Cloner cloner)
65      : base(original, cloner) {
66    }
67    public SymbolicClassificationSolution(ISymbolicClassificationModel model, IClassificationProblemData problemData)
68      : base(model, problemData) {
69      Add(new Result(ModelLengthResultName, "Length of the symbolic classification model.", new IntValue()));
70      Add(new Result(ModelDepthResultName, "Depth of the symbolic classification model.", new IntValue()));
71      RecalculateResults();
72    }
73
74    public override IDeepCloneable Clone(Cloner cloner) {
75      return new SymbolicClassificationSolution(this, cloner);
76    }
77
78    protected override void OnModelChanged(EventArgs e) {
79      base.OnModelChanged(e);
80      RecalculateResults();
81    }
82
83    private new void RecalculateResults() {
84      ModelLength = Model.SymbolicExpressionTree.Length;
85      ModelDepth = Model.SymbolicExpressionTree.Depth;
86    }
87  }
88}
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