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source: branches/DataAnalysis Refactoring/HeuristicLab.Problems.DataAnalysis/3.4/OnlineEvaluators/OnlinePearsonsRSquaredEvaluator.cs @ 5564

Last change on this file since 5564 was 5564, checked in by gkronber, 14 years ago

#1418 fixed bugs in online evaluators introduced with r5559

File size: 3.4 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;
24using HeuristicLab.Common;
25
26namespace HeuristicLab.Problems.DataAnalysis {
27  public class OnlinePearsonsRSquaredEvaluator : IOnlineEvaluator {
28    private OnlineCovarianceEvaluator covEvaluator = new OnlineCovarianceEvaluator();
29    private OnlineMeanAndVarianceCalculator sxEvaluator = new OnlineMeanAndVarianceCalculator();
30    private OnlineMeanAndVarianceCalculator syEvaluator = new OnlineMeanAndVarianceCalculator();
31
32    public double RSquared {
33      get {
34        double xVar = sxEvaluator.PopulationVariance;
35        double yVar = syEvaluator.PopulationVariance;
36        if (xVar.IsAlmost(0.0) || yVar.IsAlmost(0.0)) {
37          return 0.0;
38        } else {
39          double r = covEvaluator.Covariance / (Math.Sqrt(xVar) * Math.Sqrt(yVar));
40          return r * r;
41        }
42      }
43    }
44
45    public OnlinePearsonsRSquaredEvaluator() { }
46
47    #region IOnlineEvaluator Members
48    public double Value {
49      get { return RSquared; }
50    }
51    public void Reset() {
52      covEvaluator.Reset();
53      sxEvaluator.Reset();
54      syEvaluator.Reset();
55    }
56
57    public void Add(double x, double y) {
58      if (IsInvalidValue(x) || IsInvalidValue(y)) {
59        throw new ArgumentException("R² is not defined for variables with NaN or infinity values.");
60      }
61      covEvaluator.Add(x, y);
62      sxEvaluator.Add(x);
63      syEvaluator.Add(y);
64    }
65
66    #endregion
67
68    private bool IsInvalidValue(double x) {
69      return double.IsNaN(x) || double.IsInfinity(x);
70    }
71
72    public static double Calculate(IEnumerable<double> first, IEnumerable<double> second) {
73      IEnumerator<double> firstEnumerator = first.GetEnumerator();
74      IEnumerator<double> secondEnumerator = second.GetEnumerator();
75      OnlinePearsonsRSquaredEvaluator rSquaredEvaluator = new OnlinePearsonsRSquaredEvaluator();
76
77      // always move forward both enumerators (do not use short-circuit evaluation!)
78      while (firstEnumerator.MoveNext() & secondEnumerator.MoveNext()) {
79        double estimated = secondEnumerator.Current;
80        double original = firstEnumerator.Current;
81        rSquaredEvaluator.Add(original, estimated);
82      }
83
84      // check if both enumerators are at the end to make sure both enumerations have the same length
85      if (secondEnumerator.MoveNext() || firstEnumerator.MoveNext()) {
86        throw new ArgumentException("Number of elements in first and second enumeration doesn't match.");
87      } else {
88        return rSquaredEvaluator.RSquared;
89      }
90    }
91  }
92}
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