1 | using System;
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2 | using System.Collections.Generic;
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3 | using System.ComponentModel;
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4 | using System.Diagnostics;
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5 | using HeuristicLab.BioBoost.Data;
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6 | using HeuristicLab.BioBoost.ProblemDescription;
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7 | using HeuristicLab.BioBoost.Utils;
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8 | using HeuristicLab.Common;
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9 | using HeuristicLab.Core;
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10 | using HeuristicLab.Data;
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11 | using HeuristicLab.Encodings.IntegerVectorEncoding;
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12 | using HeuristicLab.Encodings.RealVectorEncoding;
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13 | using HeuristicLab.Operators;
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14 | using HeuristicLab.Optimization;
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15 | using HeuristicLab.Parameters;
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16 | using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
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17 | using HeuristicLab.PluginInfrastructure;
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18 | using System.Linq;
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19 | using HeuristicLab.BioBoost.Representation;
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20 | using HeuristicLab.Random;
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21 | using DiscreteIntegerVectorCrossover = HeuristicLab.Encodings.IntegerVectorEncoding.DiscreteCrossover;
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22 | using DiscreteRealVectorCrossover = HeuristicLab.Encodings.RealVectorEncoding.DiscreteCrossover;
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23 |
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24 | namespace HeuristicLab.BioBoost.Operators.Crossover {
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25 | [StorableClass]
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26 | public class PlantBasedCrossover : SingleSuccessorOperator, ICrossover, IStochasticOperator {
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27 |
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28 | #region Parameters
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29 | public ValueLookupParameter<IntMatrix> RegionBoundsParameter {
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30 | get { return (ValueLookupParameter<IntMatrix>)Parameters["RegionBounds"]; }
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31 | }
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32 | public LookupParameter<BioBoostProblemData> ProblemDataParameter {
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33 | get { return (LookupParameter<BioBoostProblemData>)Parameters["ProblemData"]; }
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34 | }
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35 | public ILookupParameter<IRandom> RandomParameter { get { return (ILookupParameter<IRandom>) Parameters["Random"]; } }
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36 | public IValueLookupParameter<IntValue> OrderingParameter { get { return (IValueLookupParameter<IntValue>) Parameters["Ordering"]; } }
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37 | public IValueLookupParameter<IntValue> FrequencyParameter { get { return (IValueLookupParameter<IntValue>) Parameters["Frequency"]; } }
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38 | public IValueLookupParameter<PercentValue> FairnessParameter { get { return (IValueLookupParameter<PercentValue>) Parameters["Fairness"]; } }
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39 | #endregion
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40 |
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41 | #region Parameter Values
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42 | public BioBoostProblemData ProblemData { get { return ProblemDataParameter.ActualValue; } }
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43 | public IRandom Random { get { return RandomParameter.ActualValue; } }
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44 | public int Ordering { get { return OrderingParameter.ActualValue.Value; } }
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45 | public int Frequency { get { return FrequencyParameter.ActualValue.Value; } }
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46 | public double Fairness { get { return FairnessParameter.ActualValue.Value; } }
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47 | #endregion
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48 |
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49 | #region Construction & Cloning
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50 | [StorableConstructor]
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51 | protected PlantBasedCrossover(bool isDeserializing) : base(isDeserializing) { }
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52 | protected PlantBasedCrossover(PlantBasedCrossover orig, Cloner cloner) : base(orig, cloner) { }
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53 |
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54 | public PlantBasedCrossover() {
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55 | Parameters.Add(new LookupParameter<BioBoostProblemData>("ProblemData", "The data store of the detailed problem description."));
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56 | Parameters.Add(new ValueLookupParameter<IntMatrix>("RegionBounds", "The limits of valid region ids."));
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57 | Parameters.Add(new LookupParameter<IRandom>("Random", "A/The random value generator."));
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58 | Parameters.Add(new ValueLookupParameter<IntValue>("Ordering", "Choose ordering 1: largest-first, -1: smallest first, 0: random", new IntValue(1)));
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59 | Parameters.Add(new ValueLookupParameter<IntValue>("Frequency", "Number of crossover points -1: random, 0: after every plant, n: n times", new IntValue(1)));
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60 | Parameters.Add(new ValueLookupParameter<PercentValue>("Fairness", "Amount of fairness: 0 don't bother, 1 avoid favoring one parent", new PercentValue(0)));
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61 | }
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62 |
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63 | public override IDeepCloneable Clone(Cloner cloner) {
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64 | return new PlantBasedCrossover(this, cloner);
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65 | }
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66 |
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67 | [StorableHook(HookType.AfterDeserialization)]
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68 | public void AfterDeserialization() {
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69 | if (!Parameters.ContainsKey("Ordering"))
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70 | Parameters.Add(new ValueLookupParameter<IntValue>("Ordering", "Choose ordering 1: largest-first, -1: smallest first, 0: random", new IntValue(0)));
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71 | if (!Parameters.ContainsKey("Frequency"))
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72 | Parameters.Add(new ValueLookupParameter<IntValue>("Frequency", "Number of crossover points -n: random (1-n), 0: ignore (order-based only), n: n times", new IntValue(0)));
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73 | if (!Parameters.ContainsKey("Fairness"))
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74 | Parameters.Add(new ValueLookupParameter<PercentValue>("Fairness", "Amount of fairness 0: don't bother - 1: avoid favoring one parent", new PercentValue(0)));
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75 | }
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76 | #endregion
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77 |
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78 | public override IOperation Apply() {
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79 | var nParents = ExecutionContext.Scope.SubScopes.Count;
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80 | if (nParents == 0) return base.Apply();
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81 | foreach (var product in ProblemData.TransportTargets.CheckedItems) {
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82 | var targets = new IntegerVector[nParents];
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83 | var utilizations = new RealVector[nParents];
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84 | foreach (var i in Enumerable.Range(0, nParents))
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85 | GetVectors(ExecutionContext.Scope.SubScopes[i], product.Value.Value, out targets[i], out utilizations[i]);
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86 | if (targets.Any(t => t == null)) continue;
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87 | var plants = Enumerable.Range(0, nParents)
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88 | .Select(parent => targets[parent].Select((target, source) => new {parent, target, source}).GroupBy(p => p.target))
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89 | .Aggregate((x, y) => x.Concat(y))
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90 | .ToArray();
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91 | if (Ordering == 0) Util.Shuffle(plants, Random);
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92 | else if (Ordering < 0) Array.Sort(plants, (g1, g2) => g1.Count() - g2.Count());
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93 | else if (Ordering > 0) Array.Sort(plants, (g1, g2) => g2.Count() - g1.Count());
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94 | var freq = Math.Min(Math.Abs(Frequency), plants.Length);
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95 | var nTotalAssignedRegions = 0;
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96 | var nAssignRegions = new int[nParents];
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97 | var length = targets[0].Length;
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98 | var assignedRegions = Enumerable.Repeat(false, length).ToArray();
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99 | var newTargets = new IntegerVector(length);
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100 | var newUtilizations = utilizations[0] != null ? new RealVector(length) : null;
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101 | if (freq == 0) { // order-based
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102 | foreach (var plant in plants) {
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103 | if (nTotalAssignedRegions >= length) break;
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104 | if (nAssignRegions[plant.First().parent] > Fairness*nTotalAssignedRegions/nParents) // skip overrepresented parent's plant
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105 | break;
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106 | foreach (var supplier in plant) {
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107 | if (nTotalAssignedRegions >= length) break;
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108 | if (assignedRegions[supplier.source]) continue;
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109 | assignedRegions[supplier.source] = true;
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110 | newTargets[supplier.source] = supplier.target;
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111 | if (newUtilizations != null)
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112 | newUtilizations[supplier.source] = utilizations[supplier.parent][supplier.source];
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113 | nTotalAssignedRegions++;
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114 | }
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115 | }
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116 | } else { // frequency-based
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117 | var nCrossoverPoints = Frequency < 0 ? Random.Next(freq) : freq;
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118 | var crossoverPoints = Enumerable.Range(0, plants.Length);
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119 | if (nCrossoverPoints != plants.Length)
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120 | crossoverPoints = crossoverPoints.SampleRandom(Random, nCrossoverPoints);
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121 | var plantsByParent = plants.GroupBy(g => g.First().parent).OrderBy(g => g.Key).Select(g => g.ToQueue()).ToArray();
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122 | int currentParent = 0;
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123 | int i = 0;
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124 | foreach (var maxI in crossoverPoints) {
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125 | for (; i < maxI; i++) {
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126 | if (nAssignRegions[currentParent] > Fairness*nTotalAssignedRegions/nParents) // skip overrepresented parent's plant
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127 | foreach (var supplier in plantsByParent[currentParent].Dequeue()) {
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128 | if (nTotalAssignedRegions >= length) break;
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129 | if (assignedRegions[supplier.source]) continue;
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130 | assignedRegions[supplier.source] = true;
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131 | newTargets[supplier.source] = supplier.target;
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132 | if (newUtilizations != null)
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133 | newUtilizations[supplier.source] = utilizations[supplier.parent][supplier.source];
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134 | nTotalAssignedRegions++;
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135 | }
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136 | }
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137 | currentParent = (currentParent + 1)%nParents;
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138 | }
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139 | }
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140 | foreach (var region in assignedRegions // fill unassigned regions
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141 | .Select((b, i) => new {selected = b, idx = i})
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142 | .Where(p => !p.selected).Select(p => p.idx)) { // unassigned regions
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143 | int newParent;
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144 | if (Random.NextDouble() < Fairness) { // choose a fair parent
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145 | newParent = nAssignRegions.Select((parent, n) => new {parent, n}).OrderBy(p => p.n).Select(p => p.parent).First();
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146 | } else {
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147 | newParent = Random.Next(nParents);
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148 | }
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149 | // assignedRegions[region] = true;
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150 | newTargets[region] = targets[newParent][region];
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151 | if (newUtilizations != null)
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152 | newUtilizations[region] = utilizations[newParent][region];
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153 | }
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154 | SaveVectors(ExecutionContext.Scope, product.Value.Value, newTargets, newUtilizations);
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155 | }
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156 | return base.Apply();
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157 | }
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158 |
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159 | private void GetVectors(IScope scope, string product, out IntegerVector targets, out RealVector utilizations) {
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160 | IVariable targetsVar, utilizationsVar;
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161 | scope.Variables.TryGetValue(LayerDescriptor.TransportTargets.NameWithPrefix(product), out targetsVar);
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162 | scope.Variables.TryGetValue(LayerDescriptor.Utilizations.NameWithPrefix(product), out utilizationsVar);
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163 | targets = null;
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164 | utilizations = null;
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165 | if (targetsVar != null) targets = targetsVar.Value as IntegerVector;
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166 | if (utilizationsVar != null) utilizations = utilizationsVar.Value as RealVector;
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167 | }
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168 |
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169 | private void SaveVectors(IScope scope, string product, IntegerVector targets, RealVector utilizations) {
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170 | scope.Variables.Add(new Variable(LayerDescriptor.TransportTargets.NameWithPrefix(product), targets));
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171 | scope.Variables.Add(new Variable(LayerDescriptor.Utilizations.NameWithPrefix(product), utilizations));
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172 | }
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173 |
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174 | }
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175 | }
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