1  #region License Information


2  /* HeuristicLab


3  * Copyright (C) 20022012 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 


22  using System;


23  using System.Collections.Generic;


24  using System.Linq;


25 


26  namespace HeuristicLab.Common {


27  public static class EnumerableStatisticExtensions {


28  /// <summary>


29  /// Calculates the median element of the enumeration.


30  /// </summary>


31  /// <param name="values"></param>


32  /// <returns></returns>


33  public static double Median(this IEnumerable<double> values) {


34  // iterate only once


35  double[] valuesArr = values.ToArray();


36  int n = valuesArr.Length;


37  if (n == 0) throw new InvalidOperationException("Enumeration contains no elements.");


38 


39  Array.Sort(valuesArr);


40 


41  // return the middle element (if n is uneven) or the average of the two middle elements if n is even.


42  if (n % 2 == 1) {


43  return valuesArr[n / 2];


44  } else {


45  return (valuesArr[(n / 2)  1] + valuesArr[n / 2]) / 2.0;


46  }


47  }


48 


49 


50  /// <summary>


51  /// Calculates the standard deviation of values.


52  /// </summary>


53  /// <param name="values"></param>


54  /// <returns></returns>


55  public static double StandardDeviation(this IEnumerable<double> values) {


56  return Math.Sqrt(Variance(values));


57  }


58 


59  /// <summary>


60  /// Calculates the variance of values. (sum (x  x_mean)² / n)


61  /// </summary>


62  /// <param name="values"></param>


63  /// <returns></returns>


64  public static double Variance(this IEnumerable<double> values) {


65  int m_n = 0;


66  double m_oldM = 0.0;


67  double m_newM = 0.0;


68  double m_oldS = 0.0;


69  double m_newS = 0.0;


70  foreach (double x in values) {


71  m_n++;


72  if (m_n == 1) {


73  m_oldM = m_newM = x;


74  m_oldS = 0.0;


75  } else {


76  m_newM = m_oldM + (x  m_oldM) / m_n;


77  m_newS = m_oldS + (x  m_oldM) * (x  m_newM);


78 


79  // set up for next iteration


80  m_oldM = m_newM;


81  m_oldS = m_newS;


82  }


83  }


84  return ((m_n > 1) ? m_newS / (m_n  1) : 0.0);


85  }


86 


87  /// <summary>


88  /// Calculates the pth percentile of the values.


89  /// </summary


90  public static double Percentile(this IEnumerable<double> values, double p) {


91  // iterate only once


92  double[] valuesArr = values.ToArray();


93  int n = valuesArr.Length;


94  if (n == 0) throw new InvalidOperationException("Enumeration contains no elements.");


95  if (n == 1) return values.ElementAt(0);


96 


97  if (p.IsAlmost(0.0)) return valuesArr[0];


98  if (p.IsAlmost(1.0)) return valuesArr[n  1];


99 


100  double t = p * (n  1);


101  int index = (int)Math.Floor(t);


102  double percentage = t  index;


103  return valuesArr[index] * (1  percentage) + valuesArr[index + 1] * percentage;


104  }


105 


106  public static IEnumerable<double> LimitToRange(this IEnumerable<double> values, double min, double max) {


107  if (min > max) throw new ArgumentException(string.Format("Minimum {0} is larger than maximum {1}.", min, max));


108  foreach (var x in values) {


109  if (double.IsNaN(x)) yield return (max + min) / 2.0;


110  else if (x < min) yield return min;


111  else if (x > max) yield return max;


112  else yield return x;


113  }


114  }


115  }


116  }

