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source: branches/2389-EpsLexicase/HeuristicLab.Problems.DataAnalysis.Symbolic.TimeSeriesPrognosis/3.4/SymbolicTimeSeriesPrognosisModel.cs @ 16659

Last change on this file since 16659 was 15583, checked in by swagner, 7 years ago

#2640: Updated year of copyrights in license headers

File size: 3.3 KB
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1#region License Information
2/* HeuristicLab
3 * Copyright (C) 2002-2018 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.Encodings.SymbolicExpressionTreeEncoding;
27using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
28using HeuristicLab.Problems.DataAnalysis.Symbolic.Regression;
29
30namespace HeuristicLab.Problems.DataAnalysis.Symbolic.TimeSeriesPrognosis {
31  /// <summary>
32  /// Represents a symbolic time-series prognosis model
33  /// </summary>
34  [StorableClass]
35  [Item(Name = "Symbolic Time-Series Prognosis Model", Description = "Represents a symbolic time series prognosis model.")]
36  public class SymbolicTimeSeriesPrognosisModel : SymbolicRegressionModel, ISymbolicTimeSeriesPrognosisModel {
37
38    public new ISymbolicTimeSeriesPrognosisExpressionTreeInterpreter Interpreter {
39      get { return (ISymbolicTimeSeriesPrognosisExpressionTreeInterpreter)base.Interpreter; }
40    }
41
42    [StorableConstructor]
43    protected SymbolicTimeSeriesPrognosisModel(bool deserializing) : base(deserializing) { }
44    protected SymbolicTimeSeriesPrognosisModel(SymbolicTimeSeriesPrognosisModel original, Cloner cloner) : base(original, cloner) { }
45    public override IDeepCloneable Clone(Cloner cloner) {
46      return new SymbolicTimeSeriesPrognosisModel(this, cloner);
47    }
48
49    public SymbolicTimeSeriesPrognosisModel(string targetVariable, ISymbolicExpressionTree tree, ISymbolicTimeSeriesPrognosisExpressionTreeInterpreter interpreter, double lowerLimit = double.MinValue, double upperLimit = double.MaxValue) : base(targetVariable, tree, interpreter, lowerLimit, upperLimit) { }
50
51    public IEnumerable<IEnumerable<double>> GetPrognosedValues(IDataset dataset, IEnumerable<int> rows, IEnumerable<int> horizons) {
52      var estimatedValues = Interpreter.GetSymbolicExpressionTreeValues(SymbolicExpressionTree, dataset, rows, horizons);
53      return estimatedValues.Select(predictionPerRow => predictionPerRow.LimitToRange(LowerEstimationLimit, UpperEstimationLimit));
54    }
55
56    public ISymbolicTimeSeriesPrognosisSolution CreateTimeSeriesPrognosisSolution(ITimeSeriesPrognosisProblemData problemData) {
57      return new SymbolicTimeSeriesPrognosisSolution(this, new TimeSeriesPrognosisProblemData(problemData));
58    }
59    ITimeSeriesPrognosisSolution ITimeSeriesPrognosisModel.CreateTimeSeriesPrognosisSolution(ITimeSeriesPrognosisProblemData problemData) {
60      return CreateTimeSeriesPrognosisSolution(problemData);
61    }
62  }
63}
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