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source: trunk/sources/HeuristicLab.Problems.DataAnalysis/3.4/Implementation/TimeSeriesPrognosis/TimeSeriesPrognosisSolution.cs @ 6802

Last change on this file since 6802 was 6802, checked in by gkronber, 13 years ago

#1081 added classes (problem, evaluators, analyzers, solution, model, online-calculators, and views) for time series prognosis problems and added an algorithm implementation to generation linear AR (auto-regressive) time series prognosis solution.

File size: 2.5 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.Persistence.Default.CompositeSerializers.Storable;
26
27namespace HeuristicLab.Problems.DataAnalysis {
28  /// <summary>
29  /// Represents a time series prognosis data analysis solution
30  /// </summary>
31  [StorableClass]
32  public abstract class TimeSeriesPrognosisSolution : TimeSeriesPrognosisSolutionBase {
33
34    [StorableConstructor]
35    protected TimeSeriesPrognosisSolution(bool deserializing)
36      : base(deserializing) {
37    }
38    protected TimeSeriesPrognosisSolution(TimeSeriesPrognosisSolution original, Cloner cloner)
39      : base(original, cloner) {
40    }
41    protected TimeSeriesPrognosisSolution(ITimeSeriesPrognosisModel model, ITimeSeriesPrognosisProblemData problemData)
42      : base(model, problemData) {
43    }
44
45    protected override void RecalculateResults() {
46      CalculateResults();
47    }
48
49    public override IEnumerable<double> PrognosedValues {
50      get { return GetPrognosedValues(Enumerable.Range(0, ProblemData.Dataset.Rows)); }
51    }
52    public override IEnumerable<double> PrognosedTrainingValues {
53      get { return GetPrognosedValues(ProblemData.TrainingIndizes); }
54    }
55    public override IEnumerable<double> PrognosedTestValues {
56      get { return GetPrognosedValues(ProblemData.TestIndizes); }
57    }
58    public override IEnumerable<double> GetPrognosedValues(IEnumerable<int> rows) {
59      return Model.GetPrognosedValues(ProblemData.Dataset, rows);
60    }
61
62    protected override void OnProblemDataChanged() {
63      base.OnProblemDataChanged();
64    }
65
66    protected override void OnModelChanged() {
67      base.OnModelChanged();
68    }
69  }
70}
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