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source: trunk/sources/HeuristicLab.Problems.DataAnalysis/3.3/Evaluators/OnlineCovarianceEvaluator.cs @ 7160

Last change on this file since 7160 was 5445, checked in by swagner, 14 years ago

Updated year of copyrights (#1406)

File size: 2.3 KB
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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;
23
24namespace HeuristicLab.Problems.DataAnalysis.Evaluators {
25  public class OnlineCovarianceEvaluator : IOnlineEvaluator {
26
27    private double originalMean, estimatedMean, Cn;
28    private int n;
29    public double Covariance {
30      get {
31        if (n < 1)
32          throw new InvalidOperationException("No elements");
33        else
34          return Cn / n;
35      }
36    }
37
38    public OnlineCovarianceEvaluator() {
39      Reset();
40    }
41
42    #region IOnlineEvaluator Members
43    public double Value {
44      get { return Covariance; }
45    }
46    public void Reset() {
47      n = 0;
48      Cn = 0.0;
49      originalMean = 0.0;
50      estimatedMean = 0.0;
51    }
52
53    public void Add(double original, double estimated) {
54      if (double.IsNaN(estimated) || double.IsInfinity(estimated) ||
55          double.IsNaN(original) || double.IsInfinity(original)) {
56        throw new ArgumentException("Covariance is not defined for series containing NaN or infinity elements");
57      } else {
58        n++;
59        // online calculation of tMean
60        originalMean = originalMean + (original - originalMean) / n;
61        double delta = estimated - estimatedMean; // delta = (y - yMean(n-1))
62        estimatedMean = estimatedMean + delta / n;
63
64        // online calculation of covariance
65        Cn = Cn + delta * (original - originalMean); // C(n) = C(n-1) + (y - yMean(n-1)) (t - tMean(n))       
66      }
67    }
68    #endregion
69  }
70}
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