source: trunk/sources/HeuristicLab.Problems.DataAnalysis/3.4/Implementation/TimeSeriesPrognosis/Models/TimeSeriesPrognosisAutoRegressiveModel.cs @ 13993

Last change on this file since 13993 was 13993, checked in by gkronber, 4 years ago

#2604: minor changes in time series models and fix build fail

File size: 4.7 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;
23using System.Collections.Generic;
24using System.Linq;
25using HeuristicLab.Common;
26using HeuristicLab.Core;
27using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
28
29namespace HeuristicLab.Problems.DataAnalysis {
30  [StorableClass]
31  [Item("Autoregressive TimeSeries Model", "A linear autoregressive time series model used to predict future values.")]
32  public class TimeSeriesPrognosisAutoRegressiveModel : RegressionModel, ITimeSeriesPrognosisModel {
33    public override IEnumerable<string> VariablesUsedForPrediction {
34      get { return new[] { TargetVariable }; }
35    }
36
37    [Storable]
38    public double[] Phi { get; private set; }
39    [Storable]
40    public double Constant { get; private set; }
41
42    public int TimeOffset { get { return Phi.Length; } }
43
44    [StorableConstructor]
45    protected TimeSeriesPrognosisAutoRegressiveModel(bool deserializing) : base(deserializing) { }
46    protected TimeSeriesPrognosisAutoRegressiveModel(TimeSeriesPrognosisAutoRegressiveModel original, Cloner cloner)
47      : base(original, cloner) {
48      this.Phi = (double[])original.Phi.Clone();
49      this.Constant = original.Constant;
50    }
51    public override IDeepCloneable Clone(Cloner cloner) {
52      return new TimeSeriesPrognosisAutoRegressiveModel(this, cloner);
53    }
54    public TimeSeriesPrognosisAutoRegressiveModel(string targetVariable, double[] phi, double constant)
55      : base(targetVariable, "AR(1) Model") {
56      Phi = (double[])phi.Clone();
57      Constant = constant;
58    }
59
60    public IEnumerable<IEnumerable<double>> GetPrognosedValues(IDataset dataset, IEnumerable<int> rows, IEnumerable<int> horizons) {
61      var rowsEnumerator = rows.GetEnumerator();
62      var horizonsEnumerator = horizons.GetEnumerator();
63      var targetValues = dataset.GetReadOnlyDoubleValues(TargetVariable);
64      // produce a n-step forecast for all rows
65      while (rowsEnumerator.MoveNext() & horizonsEnumerator.MoveNext()) {
66        int row = rowsEnumerator.Current;
67        int horizon = horizonsEnumerator.Current;
68        if (row - TimeOffset < 0) {
69          yield return Enumerable.Repeat(double.NaN, horizon);
70          continue;
71        }
72
73        double[] prognosis = new double[horizon];
74        for (int h = 0; h < horizon; h++) {
75          double estimatedValue = 0.0;
76          for (int i = 1; i <= TimeOffset; i++) {
77            int offset = h - i;
78            if (offset >= 0) estimatedValue += prognosis[offset] * Phi[i - 1];
79            else estimatedValue += targetValues[row + offset] * Phi[i - 1];
80
81          }
82          estimatedValue += Constant;
83          prognosis[h] = estimatedValue;
84        }
85
86        yield return prognosis;
87      }
88
89      if (rowsEnumerator.MoveNext() || horizonsEnumerator.MoveNext())
90        throw new ArgumentException("Number of elements in rows and horizon enumerations doesn't match.");
91    }
92
93    public override IEnumerable<double> GetEstimatedValues(IDataset dataset, IEnumerable<int> rows) {
94      var targetVariables = dataset.GetReadOnlyDoubleValues(TargetVariable);
95      foreach (int row in rows) {
96        double estimatedValue = 0.0;
97        if (row - TimeOffset < 0) {
98          yield return double.NaN;
99          continue;
100        }
101
102        for (int i = 1; i <= TimeOffset; i++) {
103          estimatedValue += targetVariables[row - i] * Phi[i - 1];
104        }
105        estimatedValue += Constant;
106        yield return estimatedValue;
107      }
108    }
109
110    public ITimeSeriesPrognosisSolution CreateTimeSeriesPrognosisSolution(ITimeSeriesPrognosisProblemData problemData) {
111      return new TimeSeriesPrognosisSolution(this, new TimeSeriesPrognosisProblemData(problemData));
112    }
113    public override IRegressionSolution CreateRegressionSolution(IRegressionProblemData problemData) {
114      throw new NotSupportedException();
115    }
116
117  }
118}
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