[4022] | 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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[4022] | 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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[5530] | 23 | using System.Collections.Generic;
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[4022] | 24 |
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[5491] | 25 | namespace HeuristicLab.Problems.DataAnalysis {
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[4022] | 26 | public class OnlineMeanAndVarianceCalculator {
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| 27 |
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| 28 | private double m_oldM, m_newM, m_oldS, m_newS;
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| 29 | private int n;
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| 30 |
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| 31 | public double Variance {
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| 32 | get {
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| 33 | return (n > 1) ? m_newS / (n - 1) : 0.0;
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| 34 | }
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| 35 | }
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| 36 |
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[4122] | 37 | public double PopulationVariance {
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| 38 | get {
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| 39 | return (n > 0) ? m_newS / n : 0.0;
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| 40 | }
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| 41 | }
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| 42 |
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[4022] | 43 | public double Mean {
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| 44 | get {
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| 45 | return (n > 0) ? m_newM : 0.0;
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| 46 | }
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| 47 | }
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| 48 |
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[4044] | 49 | public int Count {
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| 50 | get { return n; }
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| 51 | }
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| 52 |
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[4022] | 53 | public OnlineMeanAndVarianceCalculator() {
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| 54 | Reset();
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| 55 | }
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| 56 |
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| 57 | public void Reset() {
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| 58 | n = 0;
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| 59 | }
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| 60 |
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| 61 | public void Add(double x) {
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| 62 | if (double.IsNaN(x) || double.IsInfinity(x)) {
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| 63 | throw new ArgumentException("Mean and variance are not defined for NaN or infinity elements");
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| 64 | } else {
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| 65 | n++;
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| 66 | // See Knuth TAOCP vol 2, 3rd edition, page 232
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| 67 | if (n == 1) {
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| 68 | m_oldM = m_newM = x;
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| 69 | m_oldS = 0.0;
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| 70 | } else {
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| 71 | m_newM = m_oldM + (x - m_oldM) / n;
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| 72 | m_newS = m_oldS + (x - m_oldM) * (x - m_newM);
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| 73 |
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| 74 | // set up for next iteration
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| 75 | m_oldM = m_newM;
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| 76 | m_oldS = m_newS;
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| 77 | }
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| 78 | }
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| 79 | }
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[5530] | 80 |
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| 81 | public static void Calculate(IEnumerable<double> x, out double mean, out double variance) {
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| 82 | OnlineMeanAndVarianceCalculator meanAndVarianceCalculator = new OnlineMeanAndVarianceCalculator();
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| 83 | foreach (double xi in x) {
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| 84 | meanAndVarianceCalculator.Add(xi);
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| 85 | }
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| 86 | mean = meanAndVarianceCalculator.Mean;
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| 87 | variance = meanAndVarianceCalculator.Variance;
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| 88 | }
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[4022] | 89 | }
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| 90 | }
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