1 | #region License Information
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2 | /* HeuristicLab
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3 | * Copyright (C) 2002-2015 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
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4 | *
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5 | * This file is part of HeuristicLab.
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6 | *
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7 | * HeuristicLab is free software: you can redistribute it and/or modify
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8 | * it under the terms of the GNU General Public License as published by
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9 | * the Free Software Foundation, either version 3 of the License, or
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10 | * (at your option) any later version.
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11 | *
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12 | * HeuristicLab is distributed in the hope that it will be useful,
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13 | * but WITHOUT ANY WARRANTY; without even the implied warranty of
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14 | * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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15 | * GNU General Public License for more details.
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16 | *
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17 | * You should have received a copy of the GNU General Public License
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18 | * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
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19 | */
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20 | #endregion
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21 |
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22 | using HeuristicLab.Common;
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23 | using HeuristicLab.Core;
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24 | using HeuristicLab.Data;
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25 | using HeuristicLab.Optimization;
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26 | using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
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27 |
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28 | namespace HeuristicLab.Problems.DataAnalysis.Symbolic.TimeSeriesPrognosis {
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29 | /// <summary>
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30 | /// Represents a symbolic time-series prognosis solution (model + data) and attributes of the solution like accuracy and complexity
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31 | /// </summary>
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32 | [StorableClass("7178DE16-E2C9-4781-BE25-2DC3A07D3BDB")]
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33 | [Item(Name = "SymbolicTimeSeriesPrognosisSolution", Description = "Represents a symbolic time-series prognosis solution (model + data) and attributes of the solution like accuracy and complexity.")]
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34 | public sealed class SymbolicTimeSeriesPrognosisSolution : TimeSeriesPrognosisSolution, ISymbolicTimeSeriesPrognosisSolution {
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35 | private const string ModelLengthResultName = "Model Length";
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36 | private const string ModelDepthResultName = "Model Depth";
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37 |
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38 | public new ISymbolicTimeSeriesPrognosisModel Model {
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39 | get { return (ISymbolicTimeSeriesPrognosisModel)base.Model; }
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40 | set { base.Model = value; }
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41 | }
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42 | ISymbolicDataAnalysisModel ISymbolicDataAnalysisSolution.Model {
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43 | get { return (ISymbolicDataAnalysisModel)base.Model; }
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44 | }
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45 | public int ModelLength {
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46 | get { return ((IntValue)this[ModelLengthResultName].Value).Value; }
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47 | private set { ((IntValue)this[ModelLengthResultName].Value).Value = value; }
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48 | }
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49 |
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50 | public int ModelDepth {
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51 | get { return ((IntValue)this[ModelDepthResultName].Value).Value; }
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52 | private set { ((IntValue)this[ModelDepthResultName].Value).Value = value; }
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53 | }
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54 |
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55 | [StorableConstructor]
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56 | private SymbolicTimeSeriesPrognosisSolution(bool deserializing) : base(deserializing) { }
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57 | private SymbolicTimeSeriesPrognosisSolution(SymbolicTimeSeriesPrognosisSolution original, Cloner cloner)
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58 | : base(original, cloner) {
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59 | }
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60 | public SymbolicTimeSeriesPrognosisSolution(ISymbolicTimeSeriesPrognosisModel model, ITimeSeriesPrognosisProblemData problemData)
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61 | : base(model, problemData) {
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62 | Add(new Result(ModelLengthResultName, "Length of the symbolic regression model.", new IntValue()));
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63 | Add(new Result(ModelDepthResultName, "Depth of the symbolic regression model.", new IntValue()));
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64 | CalculateResults();
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65 | }
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66 |
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67 | public override IDeepCloneable Clone(Cloner cloner) {
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68 | return new SymbolicTimeSeriesPrognosisSolution(this, cloner);
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69 | }
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70 |
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71 | protected override void RecalculateResults() {
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72 | base.RecalculateResults();
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73 | CalculateResults();
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74 | }
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75 | private void CalculateResults() {
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76 | ModelLength = Model.SymbolicExpressionTree.Length;
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77 | ModelDepth = Model.SymbolicExpressionTree.Depth;
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78 | }
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79 | }
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80 | }
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