1 | #region License Information
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2 | /* HeuristicLab
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3 | * Copyright (C) 2002-2015 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
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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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23 | using System.Collections.Generic;
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24 | using System.Diagnostics.Contracts;
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25 | using System.Linq;
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26 |
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27 | namespace HeuristicLab.Common {
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28 | public static class EnumerableStatisticExtensions {
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29 | /// <summary>
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30 | /// Calculates the median element of the enumeration.
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31 | /// </summary>
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32 | /// <param name="values"></param>
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33 | /// <returns></returns>
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34 | public static double Median(this IEnumerable<double> values) {
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35 | // See unit tests for comparison with naive implementation
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36 | return Quantile(values, 0.5);
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37 | }
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38 |
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39 | /// <summary>
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40 | /// Calculates the alpha-quantile element of the enumeration.
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41 | /// </summary>
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42 | /// <param name="values"></param>
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43 | /// <returns></returns>
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44 | public static double Quantile(this IEnumerable<double> values, double alpha) {
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45 | // See unit tests for comparison with naive implementation
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46 | double[] valuesArr = values.ToArray();
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47 | int n = valuesArr.Length;
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48 | if (n == 0) throw new InvalidOperationException("Enumeration contains no elements.");
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49 |
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50 | // "When N is even, statistics books define the median as the arithmetic mean of the elements k = N/2
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51 | // and k = N/2 + 1 (that is, N/2 from the bottom and N/2 from the top).
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52 | // If you accept such pedantry, you must perform two separate selections to find these elements."
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53 |
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54 | // return the element at Math.Ceiling (if n*alpha is fractional) or the average of two elements if n*alpha is integer.
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55 | var pos = n * alpha;
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56 | Contract.Assert(pos >= 0);
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57 | Contract.Assert(pos < n);
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58 | bool isInteger = Math.Round(pos).IsAlmost(pos);
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59 | if (isInteger) {
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60 | return 0.5 * (Select((int)pos - 1, valuesArr) + Select((int)pos, valuesArr));
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61 | } else {
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62 | return Select((int)Math.Ceiling(pos) - 1, valuesArr);
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63 | }
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64 | }
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65 |
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66 | // Numerical Recipes in C++, §8.5 Selecting the Mth Largest, O(n)
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67 | // Given k in [0..n-1] returns an array value from array arr[0..n-1] such that k array values are
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68 | // less than or equal to the one returned. The input array will be rearranged to have this value in
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69 | // location arr[k], with all smaller elements moved to arr[0..k-1] (in arbitrary order) and all
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70 | // larger elements in arr[k+1..n-1] (also in arbitrary order).
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71 | //
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72 | // Could be changed to Select<T> where T is IComparable but in this case is significantly slower for double values
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73 | private static double Select(int k, double[] arr) {
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74 | Contract.Assert(arr.GetLowerBound(0) == 0);
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75 | Contract.Assert(k >= 0 && k < arr.Length);
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76 | int i, ir, j, l, mid, n = arr.Length;
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77 | double a;
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78 | l = 0;
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79 | ir = n - 1;
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80 | for (; ; ) {
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81 | if (ir <= l + 1) {
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82 | // Active partition contains 1 or 2 elements.
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83 | if (ir == l + 1 && arr[ir] < arr[l]) {
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84 | // if (ir == l + 1 && arr[ir].CompareTo(arr[l]) < 0) {
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85 | // Case of 2 elements.
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86 | // SWAP(arr[l], arr[ir]);
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87 | double temp = arr[l];
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88 | arr[l] = arr[ir];
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89 | arr[ir] = temp;
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90 | }
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91 | return arr[k];
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92 | } else {
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93 | mid = (l + ir) >> 1; // Choose median of left, center, and right elements
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94 | {
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95 | // SWAP(arr[mid], arr[l + 1]); // as partitioning element a. Also
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96 | double temp = arr[mid];
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97 | arr[mid] = arr[l + 1];
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98 | arr[l + 1] = temp;
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99 | }
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100 |
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101 | if (arr[l] > arr[ir]) {
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102 | // if (arr[l].CompareTo(arr[ir]) > 0) { // rearrange so that arr[l] arr[ir] <= arr[l+1],
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103 | // SWAP(arr[l], arr[ir]); . arr[ir] >= arr[l+1]
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104 | double temp = arr[l];
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105 | arr[l] = arr[ir];
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106 | arr[ir] = temp;
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107 | }
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108 |
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109 | if (arr[l + 1] > arr[ir]) {
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110 | // if (arr[l + 1].CompareTo(arr[ir]) > 0) {
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111 | // SWAP(arr[l + 1], arr[ir]);
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112 | double temp = arr[l + 1];
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113 | arr[l + 1] = arr[ir];
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114 | arr[ir] = temp;
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115 | }
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116 | if (arr[l] > arr[l + 1]) {
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117 | //if (arr[l].CompareTo(arr[l + 1]) > 0) {
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118 | // SWAP(arr[l], arr[l + 1]);
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119 | double temp = arr[l];
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120 | arr[l] = arr[l + 1];
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121 | arr[l + 1] = temp;
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122 |
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123 | }
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124 | i = l + 1; // Initialize pointers for partitioning.
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125 | j = ir;
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126 | a = arr[l + 1]; // Partitioning element.
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127 | for (; ; ) { // Beginning of innermost loop.
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128 | do i++; while (arr[i] < a /* arr[i].CompareTo(a) < 0 */); // Scan up to find element > a.
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129 | do j--; while (arr[j] > a /* arr[j].CompareTo(a) > 0 */); // Scan down to find element < a.
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130 | if (j < i) break; // Pointers crossed. Partitioning complete.
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131 | {
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132 | // SWAP(arr[i], arr[j]);
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133 | double temp = arr[i];
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134 | arr[i] = arr[j];
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135 | arr[j] = temp;
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136 | }
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137 | } // End of innermost loop.
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138 | arr[l + 1] = arr[j]; // Insert partitioning element.
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139 | arr[j] = a;
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140 | if (j >= k) ir = j - 1; // Keep active the partition that contains the
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141 | if (j <= k) l = i; // kth element.
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142 | }
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143 | }
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144 | }
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145 |
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146 | /// <summary>
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147 | /// Calculates the range (max - min) of the enumeration.
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148 | /// </summary>
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149 | /// <param name="values"></param>
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150 | /// <returns></returns>
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151 | public static double Range(this IEnumerable<double> values) {
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152 | double min = double.PositiveInfinity;
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153 | double max = double.NegativeInfinity;
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154 | int i = 0;
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155 | foreach (var e in values) {
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156 | if (min > e) min = e;
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157 | if (max < e) max = e;
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158 | i++;
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159 | }
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160 | if (i < 1) throw new ArgumentException("The enumerable must contain at least two elements", "values");
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161 | return max - min;
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162 | }
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163 |
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164 |
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165 | /// <summary>
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166 | /// Calculates the standard deviation of values.
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167 | /// </summary>
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168 | /// <param name="values"></param>
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169 | /// <returns></returns>
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170 | public static double StandardDeviation(this IEnumerable<double> values) {
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171 | return Math.Sqrt(Variance(values));
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172 | }
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173 |
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174 | /// <summary>
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175 | /// Calculates the variance of values. (sum (x - x_mean)² / n)
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176 | /// </summary>
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177 | /// <param name="values"></param>
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178 | /// <returns></returns>
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179 | public static double Variance(this IEnumerable<double> values) {
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180 | int m_n = 0;
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181 | double m_oldM = 0.0;
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182 | double m_newM = 0.0;
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183 | double m_oldS = 0.0;
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184 | double m_newS = 0.0;
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185 | foreach (double x in values) {
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186 | m_n++;
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187 | if (m_n == 1) {
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188 | m_oldM = m_newM = x;
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189 | m_oldS = 0.0;
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190 | } else {
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191 | m_newM = m_oldM + (x - m_oldM) / m_n;
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192 | m_newS = m_oldS + (x - m_oldM) * (x - m_newM);
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193 |
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194 | // set up for next iteration
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195 | m_oldM = m_newM;
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196 | m_oldS = m_newS;
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197 | }
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198 | }
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199 | return ((m_n > 1) ? m_newS / (m_n - 1) : 0.0);
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200 | }
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201 |
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202 | public static IEnumerable<double> LimitToRange(this IEnumerable<double> values, double min, double max) {
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203 | if (min > max) throw new ArgumentException(string.Format("Minimum {0} is larger than maximum {1}.", min, max));
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204 | foreach (var x in values) {
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205 | if (double.IsNaN(x)) yield return (max + min) / 2.0;
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206 | else if (x < min) yield return min;
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207 | else if (x > max) yield return max;
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208 | else yield return x;
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209 | }
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210 | }
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211 | }
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212 | }
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