1 | #region License Information
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2 | /* HeuristicLab
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3 | * Copyright (C) 2002-2013 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;
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25 | using System.Linq;
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26 | using HeuristicLab.Analysis.AlgorithmBehavior.Analyzers;
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27 | using MIConvexHull;
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28 | using Microsoft.VisualStudio.TestTools.UnitTesting;
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29 |
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30 | namespace AlgorithmBehaviorUnitTests {
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31 | [TestClass]
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32 | public class LPConvexHullTest {
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33 | [TestMethod]
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34 | public void TestMethod1() {
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35 | int nrOfSamples = 70;
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36 | int sampleSize = 2;
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37 | double[][] inputs = CreateRandomData(nrOfSamples, sampleSize);
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38 | var convAlgData = ConvertPermutationToVertex(inputs);
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39 |
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40 | Stopwatch watch = new Stopwatch();
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41 | watch.Start();
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42 | var result2 = LPHull.Calculate(inputs);
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43 | watch.Stop();
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44 | Console.WriteLine("LPHull: " + watch.ElapsedMilliseconds);
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45 | watch.Restart();
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46 | var result1 = ConvexHull.Create(convAlgData).Points.Select(x => x.Position).ToList();
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47 | watch.Stop();
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48 | Console.WriteLine("MIConvexHull: " + watch.ElapsedMilliseconds);
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49 |
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50 | int k = 0;
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51 | foreach (var d in result1) {
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52 | bool found = false;
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53 | foreach (var e in result2) {
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54 | int i = 0;
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55 | for (i = 0; i < e.Count(); i++) {
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56 | if (d[i] != e[i]) {
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57 | break;
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58 | }
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59 | }
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60 | if (i == e.Count()) {
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61 | found = true;
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62 | k++;
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63 | break;
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64 | }
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65 | }
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66 | Assert.IsTrue(found);
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67 | }
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68 | Console.WriteLine("Ratio: " + k + "/" + result1.Count);
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69 | Assert.AreEqual(k, result1.Count);
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70 | }
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71 |
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72 | [TestMethod]
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73 | public void TestExt() {
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74 | var inputs = CreateDataExtremePoint1().ToList();
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75 | double[] alpha = inputs.Last();
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76 | bool result = LPHull.EXT(inputs, alpha, inputs.Count() - 1);
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77 | Assert.IsTrue(result);
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78 |
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79 | inputs = CreateDataExtremePoint2().ToList();
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80 | alpha = inputs.Last();
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81 | result = LPHull.EXT(inputs, alpha, inputs.Count() - 1);
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82 | Assert.IsTrue(result);
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83 |
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84 | inputs = CreateDataNonExtremePoint1().ToList();
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85 | alpha = inputs.Last();
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86 | result = LPHull.EXT(inputs, alpha, inputs.Count() - 1);
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87 | Assert.IsFalse(result);
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88 |
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89 | inputs = CreateDataOnHull().ToList();
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90 | alpha = inputs.Last();
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91 | result = LPHull.EXT(inputs, alpha, inputs.Count() - 1);
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92 | Assert.IsFalse(result);
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93 | }
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94 |
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95 | private double[][] CreateDataExtremePoint1() {
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96 | double[][] result = new double[5][];
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97 |
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98 | result[0] = new double[] { 0.1, 0.1 };
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99 | result[1] = new double[] { 1, 1 };
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100 | result[2] = new double[] { 1, 0 };
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101 | result[3] = new double[] { 0, 1 };
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102 | result[4] = new double[] { 2.0, 1.4 };
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103 |
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104 | return result;
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105 | }
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106 |
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107 | private double[][] CreateDataExtremePoint2() {
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108 | double[][] result = new double[5][];
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109 |
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110 | result[0] = new double[] { 0.1, 0.1 };
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111 | result[1] = new double[] { 1, 1 };
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112 | result[2] = new double[] { 1, 0 };
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113 | result[3] = new double[] { 0, 1 };
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114 | result[4] = new double[] { 1.0, 1.4 };
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115 |
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116 | return result;
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117 | }
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118 |
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119 | private double[][] CreateDataNonExtremePoint1() {
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120 | double[][] result = new double[5][];
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121 |
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122 | result[0] = new double[] { 0.1, 0.1 };
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123 | result[1] = new double[] { 1, 1 };
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124 | result[2] = new double[] { 1, 0 };
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125 | result[3] = new double[] { 0, 1 };
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126 | result[4] = new double[] { 0.8, 0.4 };
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127 |
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128 | return result;
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129 | }
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130 |
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131 | private double[][] CreateDataOnHull() {
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132 | double[][] result = new double[5][];
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133 |
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134 | result[0] = new double[] { 0.1, 0.1 };
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135 | result[1] = new double[] { 1, 1 };
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136 | result[2] = new double[] { 1, 0 };
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137 | result[3] = new double[] { 0, 1 };
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138 | result[4] = new double[] { 1.0, 0.5 };
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139 |
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140 | return result;
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141 | }
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142 |
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143 | private List<DefaultVertex> ConvertPermutationToVertex(double[][] data) {
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144 | List<DefaultVertex> result = new List<DefaultVertex>();
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145 | for (int i = 0; i < data.Count(); i++) {
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146 | double[] d = data[i];
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147 | for (int j = 0; j < d.Length; j++) {
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148 | DefaultVertex vertex = new DefaultVertex();
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149 | vertex.Position = d.Select(x => x).ToArray();
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150 | result.Add(vertex);
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151 | }
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152 | }
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153 | return result;
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154 | }
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155 |
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156 | private double[][] CreateRandomData(int n, int m) {
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157 | double[][] result = new double[n][];
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158 | Random rand = new Random();
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159 |
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160 | for (int i = 0; i < n; i++) {
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161 | result[i] = new double[m];
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162 | for (int j = 0; j < m; j++) {
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163 | result[i][j] = (double)rand.Next(1, 60);
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164 | }
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165 | }
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166 | return result;
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167 | }
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168 | }
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169 | }
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