1 | #region License Information
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2 | /* HeuristicLab
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3 | * Copyright (C) 2002-2011 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
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4 | *
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5 | * This file is part of HeuristicLab.
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6 | *
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7 | * HeuristicLab is free software: you can redistribute it and/or modify
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8 | * it under the terms of the GNU General Public License as published by
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9 | * the Free Software Foundation, either version 3 of the License, or
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10 | * (at your option) any later version.
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11 | *
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12 | * HeuristicLab is distributed in the hope that it will be useful,
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13 | * but WITHOUT ANY WARRANTY; without even the implied warranty of
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14 | * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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15 | * GNU General Public License for more details.
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16 | *
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17 | * You should have received a copy of the GNU General Public License
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18 | * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.
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19 | */
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20 | #endregion
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21 |
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22 | using System;
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23 | using System.Collections.Generic;
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24 | using HeuristicLab.Common;
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25 |
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26 | namespace HeuristicLab.Problems.DataAnalysis {
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27 | public class OnlinePearsonsRSquaredEvaluator : IOnlineEvaluator {
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28 | private OnlineCovarianceEvaluator covEvaluator = new OnlineCovarianceEvaluator();
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29 | private OnlineMeanAndVarianceCalculator sxEvaluator = new OnlineMeanAndVarianceCalculator();
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30 | private OnlineMeanAndVarianceCalculator syEvaluator = new OnlineMeanAndVarianceCalculator();
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31 |
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32 | public double RSquared {
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33 | get {
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34 | double xVar = sxEvaluator.PopulationVariance;
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35 | double yVar = syEvaluator.PopulationVariance;
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36 | if (xVar.IsAlmost(0.0) || yVar.IsAlmost(0.0)) {
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37 | return 0.0;
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38 | } else {
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39 | double r = covEvaluator.Covariance / (Math.Sqrt(xVar) * Math.Sqrt(yVar));
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40 | return r * r;
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41 | }
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42 | }
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43 | }
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44 |
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45 | public OnlinePearsonsRSquaredEvaluator() { }
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46 |
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47 | #region IOnlineEvaluator Members
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48 | public double Value {
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49 | get { return RSquared; }
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50 | }
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51 | public void Reset() {
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52 | covEvaluator.Reset();
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53 | sxEvaluator.Reset();
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54 | syEvaluator.Reset();
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55 | }
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56 |
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57 | public void Add(double x, double y) {
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58 | if (IsInvalidValue(x) || IsInvalidValue(y)) {
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59 | throw new ArgumentException("R² is not defined for variables with NaN or infinity values.");
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60 | }
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61 | covEvaluator.Add(x, y);
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62 | sxEvaluator.Add(x);
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63 | syEvaluator.Add(y);
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64 | }
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65 |
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66 | #endregion
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67 |
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68 | private bool IsInvalidValue(double x) {
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69 | return double.IsNaN(x) || double.IsInfinity(x);
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70 | }
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71 |
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72 | public static double Calculate(IEnumerable<double> first, IEnumerable<double> second) {
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73 | IEnumerator<double> firstEnumerator = first.GetEnumerator();
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74 | IEnumerator<double> secondEnumerator = second.GetEnumerator();
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75 | OnlinePearsonsRSquaredEvaluator rSquaredEvaluator = new OnlinePearsonsRSquaredEvaluator();
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76 |
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77 | // always move forward both enumerators (do not use short-circuit evaluation!)
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78 | while (firstEnumerator.MoveNext() & secondEnumerator.MoveNext()) {
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79 | double estimated = secondEnumerator.Current;
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80 | double original = firstEnumerator.Current;
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81 | rSquaredEvaluator.Add(original, estimated);
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82 | }
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83 |
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84 | // check if both enumerators are at the end to make sure both enumerations have the same length
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85 | if (secondEnumerator.MoveNext() || firstEnumerator.MoveNext()) {
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86 | throw new ArgumentException("Number of elements in first and second enumeration doesn't match.");
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87 | } else {
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88 | return rSquaredEvaluator.RSquared;
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89 | }
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90 | }
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91 | }
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92 | }
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