[3996] | 1 | #region License Information
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| 2 | /* HeuristicLab
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[5445] | 3 | * Copyright (C) 2002-2011 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
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[3996] | 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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[5500] | 23 | using System.Collections.Generic;
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[3996] | 24 | using HeuristicLab.Common;
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| 25 |
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[5490] | 26 | namespace HeuristicLab.Problems.DataAnalysis {
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[5942] | 27 | public class OnlinePearsonsRSquaredCalculator : IOnlineCalculator {
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| 28 | private OnlineCovarianceCalculator covCalculator = new OnlineCovarianceCalculator();
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| 29 | private OnlineMeanAndVarianceCalculator sxCalculator = new OnlineMeanAndVarianceCalculator();
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| 30 | private OnlineMeanAndVarianceCalculator syCalculator = new OnlineMeanAndVarianceCalculator();
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[3996] | 31 |
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| 32 | public double RSquared {
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| 33 | get {
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[5942] | 34 | double xVar = sxCalculator.PopulationVariance;
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| 35 | double yVar = syCalculator.PopulationVariance;
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[4126] | 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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[5942] | 39 | double r = covCalculator.Covariance / (Math.Sqrt(xVar) * Math.Sqrt(yVar));
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[4126] | 40 | return r * r;
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| 41 | }
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[3996] | 42 | }
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| 43 | }
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| 44 |
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[5942] | 45 | public OnlinePearsonsRSquaredCalculator() { }
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[3996] | 46 |
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[5942] | 47 | #region IOnlineCalculator Members
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| 48 | public OnlineCalculatorError ErrorState {
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| 49 | get { return covCalculator.ErrorState | sxCalculator.PopulationVarianceErrorState | syCalculator.PopulationVarianceErrorState; }
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[5894] | 50 | }
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[4022] | 51 | public double Value {
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| 52 | get { return RSquared; }
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| 53 | }
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[3996] | 54 | public void Reset() {
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[5942] | 55 | covCalculator.Reset();
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| 56 | sxCalculator.Reset();
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| 57 | syCalculator.Reset();
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[3996] | 58 | }
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| 59 |
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[4122] | 60 | public void Add(double x, double y) {
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[5746] | 61 | // no need to check validity of values explicitly here as it is checked in all three evaluators
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[5942] | 62 | covCalculator.Add(x, y);
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| 63 | sxCalculator.Add(x);
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| 64 | syCalculator.Add(y);
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[3996] | 65 | }
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| 66 |
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| 67 | #endregion
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| 68 |
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[5942] | 69 | public static double Calculate(IEnumerable<double> first, IEnumerable<double> second, out OnlineCalculatorError errorState) {
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[5500] | 70 | IEnumerator<double> firstEnumerator = first.GetEnumerator();
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| 71 | IEnumerator<double> secondEnumerator = second.GetEnumerator();
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[5942] | 72 | OnlinePearsonsRSquaredCalculator rSquaredCalculator = new OnlinePearsonsRSquaredCalculator();
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[5500] | 73 |
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[5564] | 74 | // always move forward both enumerators (do not use short-circuit evaluation!)
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| 75 | while (firstEnumerator.MoveNext() & secondEnumerator.MoveNext()) {
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[5500] | 76 | double estimated = secondEnumerator.Current;
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| 77 | double original = firstEnumerator.Current;
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[5942] | 78 | rSquaredCalculator.Add(original, estimated);
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[5945] | 79 | if (rSquaredCalculator.ErrorState != OnlineCalculatorError.None) break;
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[5500] | 80 | }
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| 81 |
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[5564] | 82 | // check if both enumerators are at the end to make sure both enumerations have the same length
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[5945] | 83 | if (rSquaredCalculator.ErrorState == OnlineCalculatorError.None &&
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| 84 | (secondEnumerator.MoveNext() || firstEnumerator.MoveNext())) {
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[5500] | 85 | throw new ArgumentException("Number of elements in first and second enumeration doesn't match.");
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| 86 | } else {
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[5942] | 87 | errorState = rSquaredCalculator.ErrorState;
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| 88 | return rSquaredCalculator.RSquared;
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[5500] | 89 | }
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| 90 | }
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[3996] | 91 | }
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| 92 | }
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