#region License Information
/* HeuristicLab
* Copyright (C) 2002-2015 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;
using System.Linq;
namespace HeuristicLab.Common {
public static class EnumerableStatisticExtensions {
///
/// Calculates the median element of the enumeration.
///
///
///
public static double Median(this IEnumerable values) {
// iterate only once
double[] valuesArr = values.ToArray();
int n = valuesArr.Length;
if (n == 0) throw new InvalidOperationException("Enumeration contains no elements.");
Array.Sort(valuesArr);
// return the middle element (if n is uneven) or the average of the two middle elements if n is even.
if (n % 2 == 1) {
return valuesArr[n / 2];
} else {
return (valuesArr[(n / 2) - 1] + valuesArr[n / 2]) / 2.0;
}
}
///
/// Calculates the range (max - min) of the enumeration.
///
///
///
public static double Range(this IEnumerable values) {
double min = double.PositiveInfinity;
double max = double.NegativeInfinity;
int i = 0;
foreach (var e in values) {
if (min > e) min = e;
if (max < e) max = e;
i++;
}
if (i < 1) throw new ArgumentException("The enumerable must contain at least two elements", "values");
return max - min;
}
///
/// Calculates the standard deviation of values.
///
///
///
public static double StandardDeviation(this IEnumerable values) {
return Math.Sqrt(Variance(values));
}
///
/// Calculates the variance of values. (sum (x - x_mean)² / n)
///
///
///
public static double Variance(this IEnumerable values) {
int m_n = 0;
double m_oldM = 0.0;
double m_newM = 0.0;
double m_oldS = 0.0;
double m_newS = 0.0;
foreach (double x in values) {
m_n++;
if (m_n == 1) {
m_oldM = m_newM = x;
m_oldS = 0.0;
} else {
m_newM = m_oldM + (x - m_oldM) / m_n;
m_newS = m_oldS + (x - m_oldM) * (x - m_newM);
// set up for next iteration
m_oldM = m_newM;
m_oldS = m_newS;
}
}
return ((m_n > 1) ? m_newS / (m_n - 1) : 0.0);
}
///
/// Calculates the pth percentile of the values.
/// values, double p) {
// iterate only once
double[] valuesArr = values.ToArray();
int n = valuesArr.Length;
if (n == 0) throw new InvalidOperationException("Enumeration contains no elements.");
if (n == 1) return values.ElementAt(0);
if (p.IsAlmost(0.0)) return valuesArr[0];
if (p.IsAlmost(1.0)) return valuesArr[n - 1];
double t = p * (n - 1);
int index = (int)Math.Floor(t);
double percentage = t - index;
return valuesArr[index] * (1 - percentage) + valuesArr[index + 1] * percentage;
}
public static IEnumerable LimitToRange(this IEnumerable values, double min, double max) {
if (min > max) throw new ArgumentException(string.Format("Minimum {0} is larger than maximum {1}.", min, max));
foreach (var x in values) {
if (double.IsNaN(x)) yield return (max + min) / 2.0;
else if (x < min) yield return min;
else if (x > max) yield return max;
else yield return x;
}
}
}
}