#region License Information
/* HeuristicLab
* Copyright (C) 2002-2011 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
*
* This file is part of HeuristicLab.
*
* HeuristicLab is free software: you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation, either version 3 of the License, or
* (at your option) any later version.
*
* HeuristicLab is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with HeuristicLab. If not, see .
*/
#endregion
using System;
using System.Collections.Generic;
namespace HeuristicLab.Problems.DataAnalysis {
public class OnlineCovarianceEvaluator : IOnlineEvaluator {
private double originalMean, estimatedMean, Cn;
private int n;
public double Covariance {
get {
return n > 0 ? Cn / n : 0.0;
}
}
public OnlineCovarianceEvaluator() {
Reset();
}
#region IOnlineEvaluator Members
public double Value {
get { return Covariance; }
}
public void Reset() {
n = 0;
Cn = 0.0;
originalMean = 0.0;
estimatedMean = 0.0;
}
public void Add(double original, double estimated) {
if (double.IsNaN(estimated) || double.IsInfinity(estimated) ||
double.IsNaN(original) || double.IsInfinity(original)) {
throw new ArgumentException("Covariance is not defined for series containing NaN or infinity elements");
} else {
n++;
// online calculation of tMean
originalMean = originalMean + (original - originalMean) / n;
double delta = estimated - estimatedMean; // delta = (y - yMean(n-1))
estimatedMean = estimatedMean + delta / n;
// online calculation of covariance
Cn = Cn + delta * (original - originalMean); // C(n) = C(n-1) + (y - yMean(n-1)) (t - tMean(n))
}
}
#endregion
public static double Calculate(IEnumerable first, IEnumerable second) {
IEnumerator firstEnumerator = first.GetEnumerator();
IEnumerator secondEnumerator = second.GetEnumerator();
OnlineCovarianceEvaluator covarianceEvaluator = new OnlineCovarianceEvaluator();
// always move forward both enumerators (do not use short-circuit evaluation!)
while (firstEnumerator.MoveNext() & secondEnumerator.MoveNext()) {
double estimated = secondEnumerator.Current;
double original = firstEnumerator.Current;
covarianceEvaluator.Add(original, estimated);
}
// check if both enumerators are at the end to make sure both enumerations have the same length
if (secondEnumerator.MoveNext() || firstEnumerator.MoveNext()) {
throw new ArgumentException("Number of elements in first and second enumeration doesn't match.");
} else {
return covarianceEvaluator.Covariance;
}
}
}
}