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source: branches/ALPS/HeuristicLab.Problems.DataAnalysis.Views/3.4/TimeSeriesPrognosis/TimeSeriesPrognosisSolutionErrorCharacteristicsCurveView.cs @ 12018

Last change on this file since 12018 was 12018, checked in by pfleck, 10 years ago

#2269

  • merged trunk after 3.3.11 release
  • updated copyright and plugin version in ALPS plugin
  • removed old ALPS samples based on an userdefined alg
File size: 2.6 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 System.Collections.Generic;
23using System.Linq;
24using HeuristicLab.MainForm;
25
26namespace HeuristicLab.Problems.DataAnalysis.Views {
27  [View("Error Characteristics Curve")]
28  [Content(typeof(ITimeSeriesPrognosisSolution))]
29  public partial class TimeSeriesPrognosisSolutionErrorCharacteristicsCurveView : RegressionSolutionErrorCharacteristicsCurveView {
30
31
32    public TimeSeriesPrognosisSolutionErrorCharacteristicsCurveView()
33      : base() {
34      InitializeComponent();
35    }
36
37    public new ITimeSeriesPrognosisSolution Content {
38      get { return (ITimeSeriesPrognosisSolution)base.Content; }
39      set { base.Content = value; }
40    }
41    public new ITimeSeriesPrognosisProblemData ProblemData {
42      get {
43        if (Content == null) return null;
44        return Content.ProblemData;
45      }
46    }
47
48    protected override void UpdateChart() {
49      base.UpdateChart();
50      if (Content == null) return;
51
52      IEnumerable<double> trainingStartValues = ProblemData.Dataset.GetDoubleValues(ProblemData.TargetVariable, ProblemData.TrainingIndices.Select(r => r - 1).Where(r => r > 0)).ToList();
53      if (trainingStartValues.Any()) {
54        //AR1 model
55        double alpha, beta;
56        OnlineCalculatorError errorState;
57        OnlineLinearScalingParameterCalculator.Calculate(ProblemData.Dataset.GetDoubleValues(ProblemData.TargetVariable, ProblemData.TrainingIndices.Where(x => x > 0)), trainingStartValues, out alpha, out beta, out errorState);
58        var ar1model = new TimeSeriesPrognosisAutoRegressiveModel(ProblemData.TargetVariable, new double[] { beta }, alpha).CreateTimeSeriesPrognosisSolution(ProblemData);
59        ar1model.Name = "AR(1) Model";
60        AddRegressionSolution(ar1model);
61      }
62    }
63  }
64}
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