1 | #region License Information
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2 | /* HeuristicLab
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3 | * Copyright (C) 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.Linq;
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24 | using HEAL.Attic;
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25 | using HeuristicLab.Common;
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26 | using HeuristicLab.Core;
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27 | using HeuristicLab.Data;
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28 | using HeuristicLab.Encodings.PermutationEncoding;
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29 | using HeuristicLab.Optimization;
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30 | using HeuristicLab.Parameters;
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31 | using HeuristicLab.Problems.Instances;
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32 | using HeuristicLab.Problems.TravelingSalesman;
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33 | using HeuristicLab.Random;
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34 |
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35 | namespace HeuristicLab.Problems.PTSP {
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36 | [Item("Probabilistic TSP (p-TSP)", "Represents a Probabilistic Traveling Salesman Problem.")]
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37 | [StorableType("86041a8c-14e6-46e1-b20f-566892c871f6")]
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38 | public abstract class ProbabilisticTSP : PermutationProblem,
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39 | IProblemInstanceConsumer<PTSPData> {
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40 | protected bool SuppressEvents { get; set; }
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41 |
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42 | public static int DistanceMatrixSizeLimit = 1000;
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43 |
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44 | #region Parameter Properties
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45 | [Storable] public ValueParameter<IProbabilisticTSPData> PTSPDataParameter { get; private set; }
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46 | [Storable] public OptionalValueParameter<ITSPSolution> BestKnownSolutionParameter { get; private set; }
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47 | #endregion
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48 |
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49 | #region Properties
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50 | public IProbabilisticTSPData ProbabilisticTSPData {
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51 | get { return PTSPDataParameter.Value; }
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52 | set { PTSPDataParameter.Value = value; }
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53 | }
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54 | public ITSPSolution BestKnownSolution {
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55 | get { return BestKnownSolutionParameter.Value; }
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56 | set { BestKnownSolutionParameter.Value = value; }
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57 | }
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58 | #endregion
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59 |
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60 | public override bool Maximization {
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61 | get { return false; }
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62 | }
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63 |
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64 | [StorableConstructor]
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65 | protected ProbabilisticTSP(StorableConstructorFlag _) : base(_) { }
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66 | protected ProbabilisticTSP(ProbabilisticTSP original, Cloner cloner)
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67 | : base(original, cloner) {
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68 | PTSPDataParameter = cloner.Clone(original.PTSPDataParameter);
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69 | BestKnownSolutionParameter = cloner.Clone(original.BestKnownSolutionParameter);
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70 | }
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71 | protected ProbabilisticTSP() {
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72 | Parameters.Add(PTSPDataParameter = new ValueParameter<IProbabilisticTSPData>("PTSP Data", "The main parameters for the p-TSP."));
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73 | Parameters.Add(BestKnownSolutionParameter = new OptionalValueParameter<ITSPSolution>("BestKnownSolution", "The best known solution of this p-TSP instance."));
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74 |
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75 | ProbabilisticTSPData = new MatrixProbabilisticTSPData();
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76 | Encoding.Length = ProbabilisticTSPData.Cities;
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77 | }
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78 |
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79 | protected override void OnEncodingChanged() {
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80 | base.OnEncodingChanged();
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81 | Encoding.Length = ProbabilisticTSPData.Cities;
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82 | }
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83 |
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84 | public override void Analyze(Permutation[] solutions, double[] qualities, ResultCollection results, IRandom random) {
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85 | base.Analyze(solutions, qualities, results, random);
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86 | var max = Maximization;
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87 |
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88 | var i = !max ? qualities.Select((x, index) => new { index, x }).OrderBy(x => x).First().index
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89 | : qualities.Select((x, index) => new { index, x }).OrderByDescending(x => x).First().index;
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90 |
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91 | if (double.IsNaN(BestKnownQuality) ||
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92 | max && qualities[i] > BestKnownQuality ||
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93 | !max && qualities[i] < BestKnownQuality) {
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94 | BestKnownQuality = qualities[i];
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95 | BestKnownSolution = ProbabilisticTSPData.GetSolution((Permutation)solutions[i].Clone(), qualities[i]);
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96 | }
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97 |
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98 | IResult bestSolutionResult;
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99 | if (results.TryGetValue("Best p-TSP Solution", out bestSolutionResult)) {
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100 | var bestSolution = bestSolutionResult.Value as ITSPSolution;
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101 | if (bestSolution == null || Maximization && bestSolution.TourLength.Value < qualities[i]
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102 | || !Maximization && bestSolution.TourLength.Value > qualities[i]) {
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103 | bestSolutionResult.Value = ProbabilisticTSPData.GetSolution(solutions[i], qualities[i]);
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104 | }
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105 | } else results.Add(new Result("Best p-TSP Solution", ProbabilisticTSPData.GetSolution(solutions[i], qualities[i])));
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106 | }
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107 |
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108 | public virtual void Load(PTSPData data) {
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109 | if (data.Coordinates == null && data.Distances == null)
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110 | throw new System.IO.InvalidDataException("The given instance specifies neither coordinates nor distances!");
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111 | if (data.Dimension > DistanceMatrixSizeLimit && (data.DistanceMeasure == DistanceMeasure.Att
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112 | || data.DistanceMeasure == DistanceMeasure.Manhattan
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113 | || data.DistanceMeasure == DistanceMeasure.Maximum))
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114 | throw new System.IO.InvalidDataException("The given instance uses an unsupported distance measure and is too large for using a distance matrix.");
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115 | if (data.Coordinates != null && data.Coordinates.GetLength(1) != 2)
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116 | throw new System.IO.InvalidDataException("The coordinates of the given instance are not in the right format, there need to be one row for each customer and two columns for the x and y coordinates.");
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117 |
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118 | Encoding.Length = data.Dimension;
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119 | Name = data.Name;
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120 | Description = data.Description;
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121 |
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122 | if (data.Dimension <= DistanceMatrixSizeLimit) {
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123 | ProbabilisticTSPData = new MatrixProbabilisticTSPData(data.Name, data.GetDistanceMatrix(), data.Probabilities, data.Coordinates) { Description = data.Description };
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124 | } else if (data.DistanceMeasure == DistanceMeasure.Direct && data.Distances != null) {
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125 | ProbabilisticTSPData = new MatrixProbabilisticTSPData(data.Name, data.Distances, data.Probabilities, data.Coordinates) { Description = data.Description };
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126 | } else {
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127 | switch (data.DistanceMeasure) {
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128 | case DistanceMeasure.Att:
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129 | ProbabilisticTSPData = new AttPTSPData(data.Name, data.Coordinates, data.Probabilities) { Description = data.Description };
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130 | break;
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131 | case DistanceMeasure.Euclidean:
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132 | ProbabilisticTSPData = new EuclideanPTSPData(data.Name, data.Coordinates, data.Probabilities, EuclideanTSPData.DistanceRounding.None) { Description = data.Description };
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133 | break;
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134 | case DistanceMeasure.RoundedEuclidean:
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135 | ProbabilisticTSPData = new EuclideanPTSPData(data.Name, data.Coordinates, data.Probabilities, EuclideanTSPData.DistanceRounding.Midpoint) { Description = data.Description };
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136 | break;
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137 | case DistanceMeasure.UpperEuclidean:
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138 | ProbabilisticTSPData = new EuclideanPTSPData(data.Name, data.Coordinates, data.Probabilities, EuclideanTSPData.DistanceRounding.Ceiling) { Description = data.Description };
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139 | break;
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140 | case DistanceMeasure.Geo:
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141 | ProbabilisticTSPData = new GeoPTSPData(data.Name, data.Coordinates, data.Probabilities) { Description = data.Description };
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142 | break;
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143 | case DistanceMeasure.Manhattan:
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144 | ProbabilisticTSPData = new ManhattanPTSPData(data.Name, data.Coordinates, data.Probabilities) { Description = data.Description };
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145 | break;
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146 | case DistanceMeasure.Maximum:
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147 | ProbabilisticTSPData = new MaximumPTSPData(data.Name, data.Coordinates, data.Probabilities) { Description = data.Description };
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148 | break;
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149 | default:
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150 | throw new System.IO.InvalidDataException("An unknown distance measure is given in the instance!");
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151 | }
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152 | }
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153 | BestKnownSolution = null;
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154 | BestKnownQuality = double.NaN;
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155 |
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156 | if (data.BestKnownTour != null) {
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157 | try {
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158 | var tour = new Permutation(PermutationTypes.RelativeUndirected, data.BestKnownTour);
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159 | var tourLength = Evaluate(tour, new FastRandom(1));
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160 | BestKnownSolution = new TSPSolution(data.Coordinates != null ? new DoubleMatrix(data.Coordinates) : null, tour, new DoubleValue(tourLength));
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161 | BestKnownQuality = tourLength;
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162 | } catch (InvalidOperationException) {
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163 | if (data.BestKnownQuality.HasValue)
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164 | BestKnownQuality = data.BestKnownQuality.Value;
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165 | }
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166 | } else if (data.BestKnownQuality.HasValue) {
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167 | BestKnownQuality = data.BestKnownQuality.Value;
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168 | }
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169 | OnReset();
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170 | }
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171 | }
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172 | }
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