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source: trunk/sources/HeuristicLab.Problems.DataAnalysis.Symbolic.TimeSeriesPrognosis/3.4/SymbolicTimeSeriesPrognosisSolution.cs @ 12749

Last change on this file since 12749 was 12012, checked in by ascheibe, 10 years ago

#2212 merged r12008, r12009, r12010 back into trunk

File size: 3.5 KB
Line 
1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2015 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 HeuristicLab.Common;
23using HeuristicLab.Core;
24using HeuristicLab.Data;
25using HeuristicLab.Optimization;
26using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
27
28namespace HeuristicLab.Problems.DataAnalysis.Symbolic.TimeSeriesPrognosis {
29  /// <summary>
30  /// Represents a symbolic time-series prognosis solution (model + data) and attributes of the solution like accuracy and complexity
31  /// </summary>
32  [StorableClass]
33  [Item(Name = "SymbolicTimeSeriesPrognosisSolution", Description = "Represents a symbolic time-series prognosis solution (model + data) and attributes of the solution like accuracy and complexity.")]
34  public sealed class SymbolicTimeSeriesPrognosisSolution : TimeSeriesPrognosisSolution, ISymbolicTimeSeriesPrognosisSolution {
35    private const string ModelLengthResultName = "Model Length";
36    private const string ModelDepthResultName = "Model Depth";
37
38    public new ISymbolicTimeSeriesPrognosisModel Model {
39      get { return (ISymbolicTimeSeriesPrognosisModel)base.Model; }
40      set { base.Model = value; }
41    }
42    ISymbolicDataAnalysisModel ISymbolicDataAnalysisSolution.Model {
43      get { return (ISymbolicDataAnalysisModel)base.Model; }
44    }
45    public int ModelLength {
46      get { return ((IntValue)this[ModelLengthResultName].Value).Value; }
47      private set { ((IntValue)this[ModelLengthResultName].Value).Value = value; }
48    }
49
50    public int ModelDepth {
51      get { return ((IntValue)this[ModelDepthResultName].Value).Value; }
52      private set { ((IntValue)this[ModelDepthResultName].Value).Value = value; }
53    }
54
55    [StorableConstructor]
56    private SymbolicTimeSeriesPrognosisSolution(bool deserializing) : base(deserializing) { }
57    private SymbolicTimeSeriesPrognosisSolution(SymbolicTimeSeriesPrognosisSolution original, Cloner cloner)
58      : base(original, cloner) {
59    }
60    public SymbolicTimeSeriesPrognosisSolution(ISymbolicTimeSeriesPrognosisModel model, ITimeSeriesPrognosisProblemData problemData)
61      : base(model, problemData) {
62      Add(new Result(ModelLengthResultName, "Length of the symbolic regression model.", new IntValue()));
63      Add(new Result(ModelDepthResultName, "Depth of the symbolic regression model.", new IntValue()));
64      CalculateResults();
65    }
66
67    public override IDeepCloneable Clone(Cloner cloner) {
68      return new SymbolicTimeSeriesPrognosisSolution(this, cloner);
69    }
70
71    protected override void RecalculateResults() {
72      base.RecalculateResults();
73      CalculateResults();
74    }
75    private void CalculateResults() {
76      ModelLength = Model.SymbolicExpressionTree.Length;
77      ModelDepth = Model.SymbolicExpressionTree.Depth;
78    }
79  }
80}
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