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source: trunk/sources/HeuristicLab.Problems.DataAnalysis/3.4/OnlineEvaluators/OnlineCovarianceEvaluator.cs @ 5809

Last change on this file since 5809 was 5809, checked in by mkommend, 12 years ago

#1418: Reintegrated branch into trunk.

File size: 3.2 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;
23using System.Collections.Generic;
24
25namespace HeuristicLab.Problems.DataAnalysis {
26  public class OnlineCovarianceEvaluator : IOnlineEvaluator {
27
28    private double originalMean, estimatedMean, Cn;
29    private int n;
30    public double Covariance {
31      get {
32        return n > 0 ? Cn / n : 0.0;
33      }
34    }
35
36    public OnlineCovarianceEvaluator() {
37      Reset();
38    }
39
40    #region IOnlineEvaluator Members
41    public double Value {
42      get { return Covariance; }
43    }
44    public void Reset() {
45      n = 0;
46      Cn = 0.0;
47      originalMean = 0.0;
48      estimatedMean = 0.0;
49    }
50
51    public void Add(double original, double estimated) {
52      if (double.IsNaN(estimated) || double.IsInfinity(estimated) ||
53          double.IsNaN(original) || double.IsInfinity(original)) {
54        throw new ArgumentException("Covariance is not defined for series containing NaN or infinity elements");
55      } else {
56        n++;
57        // online calculation of tMean
58        originalMean = originalMean + (original - originalMean) / n;
59        double delta = estimated - estimatedMean; // delta = (y - yMean(n-1))
60        estimatedMean = estimatedMean + delta / n;
61
62        // online calculation of covariance
63        Cn = Cn + delta * (original - originalMean); // C(n) = C(n-1) + (y - yMean(n-1)) (t - tMean(n))       
64      }
65    }
66    #endregion
67
68    public static double Calculate(IEnumerable<double> first, IEnumerable<double> second) {
69      IEnumerator<double> firstEnumerator = first.GetEnumerator();
70      IEnumerator<double> secondEnumerator = second.GetEnumerator();
71      OnlineCovarianceEvaluator covarianceEvaluator = new OnlineCovarianceEvaluator();
72
73      // always move forward both enumerators (do not use short-circuit evaluation!)
74      while (firstEnumerator.MoveNext() & secondEnumerator.MoveNext()) {
75        double estimated = secondEnumerator.Current;
76        double original = firstEnumerator.Current;
77        covarianceEvaluator.Add(original, estimated);
78      }
79
80      // check if both enumerators are at the end to make sure both enumerations have the same length
81      if (secondEnumerator.MoveNext() || firstEnumerator.MoveNext()) {
82        throw new ArgumentException("Number of elements in first and second enumeration doesn't match.");
83      } else {
84        return covarianceEvaluator.Covariance;
85      }
86    }
87  }
88}
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