| 1 | #region License Information
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| 2 | /* HeuristicLab
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| 3 | * Copyright (C) 2002-2014 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 HeuristicLab.Common;
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| 23 | using HeuristicLab.Core;
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| 24 | using HeuristicLab.Data;
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| 25 | using HeuristicLab.Operators;
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| 26 | using HeuristicLab.Optimization.Operators;
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| 27 | using HeuristicLab.Parameters;
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| 28 | using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
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| 29 | using HeuristicLab.Selection;
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| 30 |
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| 31 | namespace HeuristicLab.Algorithms.VOffspringSelectionGeneticAlgorithm {
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| 32 | /// <summary>
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| 33 | /// An operator which represents the main loop of an offspring selection genetic algorithm.
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| 34 | /// </summary>
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| 35 | [Item("VOffspringSelectionGeneticAlgorithmMainOperator", "An operator that represents the core of an offspring selection genetic algorithm.")]
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| 36 | [StorableClass]
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| 37 | public sealed class VOffspringSelectionGeneticAlgorithmMainOperator : AlgorithmOperator {
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| 38 | #region Parameter properties
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| 39 | public ValueLookupParameter<IRandom> RandomParameter {
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| 40 | get { return (ValueLookupParameter<IRandom>)Parameters["Random"]; }
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| 41 | }
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| 42 | public ValueLookupParameter<BoolValue> MaximizationParameter {
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| 43 | get { return (ValueLookupParameter<BoolValue>)Parameters["Maximization"]; }
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| 44 | }
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| 45 | public ScopeTreeLookupParameter<DoubleValue> QualityParameter {
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| 46 | get { return (ScopeTreeLookupParameter<DoubleValue>)Parameters["Quality"]; }
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| 47 | }
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| 48 | public ValueLookupParameter<IOperator> SelectorParameter {
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| 49 | get { return (ValueLookupParameter<IOperator>)Parameters["Selector"]; }
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| 50 | }
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| 51 | public ValueLookupParameter<IOperator> CrossoverParameter {
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| 52 | get { return (ValueLookupParameter<IOperator>)Parameters["Crossover"]; }
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| 53 | }
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| 54 | public ValueLookupParameter<PercentValue> MutationProbabilityParameter {
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| 55 | get { return (ValueLookupParameter<PercentValue>)Parameters["MutationProbability"]; }
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| 56 | }
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| 57 | public ValueLookupParameter<IOperator> MutatorParameter {
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| 58 | get { return (ValueLookupParameter<IOperator>)Parameters["Mutator"]; }
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| 59 | }
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| 60 | public ValueLookupParameter<IOperator> EvaluatorParameter {
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| 61 | get { return (ValueLookupParameter<IOperator>)Parameters["Evaluator"]; }
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| 62 | }
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| 63 | public LookupParameter<IntValue> EvaluatedSolutionsParameter {
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| 64 | get { return (LookupParameter<IntValue>)Parameters["EvaluatedSolutions"]; }
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| 65 | }
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| 66 | public ValueLookupParameter<IntValue> ElitesParameter {
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| 67 | get { return (ValueLookupParameter<IntValue>)Parameters["Elites"]; }
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| 68 | }
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| 69 | public IValueLookupParameter<BoolValue> ReevaluateElitesParameter {
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| 70 | get { return (IValueLookupParameter<BoolValue>)Parameters["ReevaluateElites"]; }
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| 71 | }
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| 72 | public LookupParameter<DoubleValue> ComparisonFactorParameter {
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| 73 | get { return (LookupParameter<DoubleValue>)Parameters["ComparisonFactor"]; }
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| 74 | }
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| 75 | public LookupParameter<DoubleValue> CurrentSuccessRatioParameter {
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| 76 | get { return (LookupParameter<DoubleValue>)Parameters["CurrentSuccessRatio"]; }
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| 77 | }
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| 78 | public ValueLookupParameter<DoubleValue> SuccessRatioParameter {
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| 79 | get { return (ValueLookupParameter<DoubleValue>)Parameters["SuccessRatio"]; }
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| 80 | }
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| 81 | public LookupParameter<DoubleValue> SelectionPressureParameter {
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| 82 | get { return (LookupParameter<DoubleValue>)Parameters["SelectionPressure"]; }
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| 83 | }
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| 84 | public ValueLookupParameter<DoubleValue> MaximumSelectionPressureParameter {
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| 85 | get { return (ValueLookupParameter<DoubleValue>)Parameters["MaximumSelectionPressure"]; }
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| 86 | }
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| 87 | public ValueLookupParameter<BoolValue> OffspringSelectionBeforeMutationParameter {
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| 88 | get { return (ValueLookupParameter<BoolValue>)Parameters["OffspringSelectionBeforeMutation"]; }
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| 89 | }
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| 90 | public IValueLookupParameter<BoolValue> FillPopulationWithParentsParameter {
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| 91 | get { return (IValueLookupParameter<BoolValue>)Parameters["FillPopulationWithParents"]; }
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| 92 | }
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| 93 | public ValueLookupParameter<IOffspringSelector> OffspringSelectorParameter {
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| 94 | get { return (ValueLookupParameter<IOffspringSelector>)Parameters["OffspringSelector"]; }
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| 95 | }
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| 96 | public ValueLookupParameter<ISubScopesQualityComparatorOperator> SubScopesQualityComparatorParameter {
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| 97 | get { return (ValueLookupParameter<ISubScopesQualityComparatorOperator>)Parameters["SubScopesQualityComparator"]; }
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| 98 | }
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| 99 | #endregion
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| 100 |
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| 101 | [StorableConstructor]
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| 102 | private VOffspringSelectionGeneticAlgorithmMainOperator(bool deserializing) : base(deserializing) { }
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| 103 | private VOffspringSelectionGeneticAlgorithmMainOperator(VOffspringSelectionGeneticAlgorithmMainOperator original, Cloner cloner)
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| 104 | : base(original, cloner) {
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| 105 | }
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| 106 | public override IDeepCloneable Clone(Cloner cloner) {
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| 107 | return new VOffspringSelectionGeneticAlgorithmMainOperator(this, cloner);
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| 108 | }
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| 109 | public VOffspringSelectionGeneticAlgorithmMainOperator()
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| 110 | : base() {
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| 111 | Initialize();
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| 112 | }
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| 113 |
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| 114 | [StorableHook(HookType.AfterDeserialization)]
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| 115 | private void AfterDeserialization() {
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| 116 | // BackwardsCompatibility3.3
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| 117 | #region Backwards compatible code, remove with 3.4
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| 118 | if (!Parameters.ContainsKey("ReevaluateElites")) {
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| 119 | Parameters.Add(new ValueLookupParameter<BoolValue>("ReevaluateElites", "Flag to determine if elite individuals should be reevaluated (i.e., if stochastic fitness functions are used.)"));
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| 120 | }
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| 121 | if (!Parameters.ContainsKey("FillPopulationWithParents"))
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| 122 | Parameters.Add(new ValueLookupParameter<BoolValue>("FillPopulationWithParents", "True if the population should be filled with parent individual or false if worse children should be used when the maximum selection pressure is exceeded."));
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| 123 | #endregion
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| 124 | }
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| 125 |
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| 126 | private void Initialize() {
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| 127 | #region Create parameters
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| 128 | Parameters.Add(new ValueLookupParameter<IRandom>("Random", "A pseudo random number generator."));
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| 129 | Parameters.Add(new ValueLookupParameter<BoolValue>("Maximization", "True if the problem is a maximization problem, otherwise false."));
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| 130 | Parameters.Add(new ScopeTreeLookupParameter<DoubleValue>("Quality", "The value which represents the quality of a solution."));
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| 131 | Parameters.Add(new ValueLookupParameter<IOperator>("Selector", "The operator used to select solutions for reproduction."));
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| 132 | Parameters.Add(new ValueLookupParameter<IOperator>("Crossover", "The operator used to cross solutions."));
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| 133 | Parameters.Add(new ValueLookupParameter<PercentValue>("MutationProbability", "The probability that the mutation operator is applied on a solution."));
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| 134 | Parameters.Add(new ValueLookupParameter<IOperator>("Mutator", "The operator used to mutate solutions."));
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| 135 | Parameters.Add(new ValueLookupParameter<IOperator>("Evaluator", "The operator used to evaluate solutions. This operator is executed in parallel, if an engine is used which supports parallelization."));
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| 136 | Parameters.Add(new LookupParameter<IntValue>("EvaluatedSolutions", "The number of evaluated solutions."));
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| 137 | Parameters.Add(new ValueLookupParameter<IntValue>("Elites", "The numer of elite solutions which are kept in each generation."));
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| 138 | Parameters.Add(new ValueLookupParameter<BoolValue>("ReevaluateElites", "Flag to determine if elite individuals should be reevaluated (i.e., if stochastic fitness functions are used.)"));
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| 139 | Parameters.Add(new LookupParameter<DoubleValue>("ComparisonFactor", "The comparison factor is used to determine whether the offspring should be compared to the better parent, the worse parent or a quality value linearly interpolated between them. It is in the range [0;1]."));
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| 140 | Parameters.Add(new LookupParameter<DoubleValue>("CurrentSuccessRatio", "The current success ratio."));
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| 141 | Parameters.Add(new ValueLookupParameter<DoubleValue>("SuccessRatio", "The ratio of successful to total children that should be achieved."));
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| 142 | Parameters.Add(new LookupParameter<DoubleValue>("SelectionPressure", "The actual selection pressure."));
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| 143 | Parameters.Add(new ValueLookupParameter<DoubleValue>("MaximumSelectionPressure", "The maximum selection pressure that terminates the algorithm."));
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| 144 | Parameters.Add(new ValueLookupParameter<BoolValue>("OffspringSelectionBeforeMutation", "True if the offspring selection step should be applied before mutation, false if it should be applied after mutation."));
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| 145 | Parameters.Add(new ValueLookupParameter<BoolValue>("FillPopulationWithParents", "True if the population should be filled with parent individual or false if worse children should be used when the maximum selection pressure is exceeded."));
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| 146 | Parameters.Add(new ValueLookupParameter<IOffspringSelector>("OffspringSelector", "The operator used as selection criterea for deciding which individuals are successful and which should be disgarded."));
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| 147 | Parameters.Add(new ValueLookupParameter<ISubScopesQualityComparatorOperator>("SubScopesQualityComparator", "The operator used to compare solution candidates."));
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| 148 | #endregion
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| 149 |
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| 150 | #region Create operators
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| 151 | Placeholder selector = new Placeholder();
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| 152 | SubScopesProcessor subScopesProcessor1 = new SubScopesProcessor();
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| 153 | ChildrenCreator childrenCreator = new ChildrenCreator();
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| 154 | ConditionalBranch osBeforeMutationBranch = new ConditionalBranch();
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| 155 | UniformSubScopesProcessor uniformSubScopesProcessor1 = new UniformSubScopesProcessor();
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| 156 | Placeholder crossover1 = new Placeholder();
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| 157 | UniformSubScopesProcessor uniformSubScopesProcessor2 = new UniformSubScopesProcessor();
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| 158 | Placeholder evaluator1 = new Placeholder();
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| 159 | SubScopesCounter subScopesCounter1 = new SubScopesCounter();
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| 160 | Placeholder qualityComparer1 = new Placeholder();
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| 161 | SubScopesRemover subScopesRemover1 = new SubScopesRemover();
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| 162 | UniformSubScopesProcessor uniformSubScopesProcessor3 = new UniformSubScopesProcessor();
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| 163 | StochasticBranch mutationBranch1 = new StochasticBranch();
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| 164 | Placeholder mutator1 = new Placeholder();
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| 165 | VariableCreator variableCreator1 = new VariableCreator();
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| 166 | VariableCreator variableCreator2 = new VariableCreator();
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| 167 | ConditionalSelector conditionalSelector = new ConditionalSelector();
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| 168 | SubScopesProcessor subScopesProcessor2 = new SubScopesProcessor();
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| 169 | UniformSubScopesProcessor uniformSubScopesProcessor4 = new UniformSubScopesProcessor();
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| 170 | Placeholder evaluator2 = new Placeholder();
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| 171 | SubScopesCounter subScopesCounter2 = new SubScopesCounter();
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| 172 | MergingReducer mergingReducer1 = new MergingReducer();
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| 173 | UniformSubScopesProcessor uniformSubScopesProcessor5 = new UniformSubScopesProcessor();
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| 174 | Placeholder crossover2 = new Placeholder();
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| 175 | StochasticBranch mutationBranch2 = new StochasticBranch();
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| 176 | Placeholder mutator2 = new Placeholder();
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| 177 | UniformSubScopesProcessor uniformSubScopesProcessor6 = new UniformSubScopesProcessor();
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| 178 | Placeholder evaluator3 = new Placeholder();
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| 179 | SubScopesCounter subScopesCounter3 = new SubScopesCounter();
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| 180 | Placeholder qualityComparer2 = new Placeholder();
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| 181 | SubScopesRemover subScopesRemover2 = new SubScopesRemover();
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| 182 | Placeholder offspringSelector = new Placeholder();
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| 183 | SubScopesProcessor subScopesProcessor3 = new SubScopesProcessor();
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| 184 | BestSelector bestSelector = new BestSelector();
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| 185 | WorstSelector worstSelector = new WorstSelector();
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| 186 | RightReducer rightReducer = new RightReducer();
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| 187 | LeftReducer leftReducer = new LeftReducer();
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| 188 | MergingReducer mergingReducer2 = new MergingReducer();
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| 189 | ConditionalBranch reevaluateElitesBranch = new ConditionalBranch();
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| 190 | UniformSubScopesProcessor uniformSubScopesProcessor7 = new UniformSubScopesProcessor();
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| 191 | Placeholder evaluator4 = new Placeholder();
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| 192 | SubScopesCounter subScopesCounter4 = new SubScopesCounter();
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| 193 | ConditionalBranch conditionalBranch = new ConditionalBranch();
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| 194 |
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| 195 | selector.Name = "Selector (placeholder)";
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| 196 | selector.OperatorParameter.ActualName = SelectorParameter.Name;
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| 197 |
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| 198 | childrenCreator.ParentsPerChild = new IntValue(2);
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| 199 |
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| 200 | osBeforeMutationBranch.Name = "Apply OS before mutation?";
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| 201 | osBeforeMutationBranch.ConditionParameter.ActualName = OffspringSelectionBeforeMutationParameter.Name;
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| 202 |
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| 203 | crossover1.Name = "Crossover (placeholder)";
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| 204 | crossover1.OperatorParameter.ActualName = CrossoverParameter.Name;
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| 205 |
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| 206 | uniformSubScopesProcessor2.Parallel.Value = true;
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| 207 |
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| 208 | evaluator1.Name = "Evaluator (placeholder)";
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| 209 | evaluator1.OperatorParameter.ActualName = EvaluatorParameter.Name;
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| 210 |
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| 211 | subScopesCounter1.Name = "Increment EvaluatedSolutions";
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| 212 | subScopesCounter1.ValueParameter.ActualName = EvaluatedSolutionsParameter.Name;
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| 213 |
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| 214 | qualityComparer1.Name = "Quality Comparator (placeholder)";
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| 215 | qualityComparer1.OperatorParameter.ActualName = SubScopesQualityComparatorParameter.ActualName;
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| 216 |
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| 217 | subScopesRemover1.RemoveAllSubScopes = true;
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| 218 |
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| 219 | mutationBranch1.ProbabilityParameter.ActualName = MutationProbabilityParameter.Name;
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| 220 | mutationBranch1.RandomParameter.ActualName = RandomParameter.Name;
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| 221 |
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| 222 | mutator1.Name = "Mutator (placeholder)";
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| 223 | mutator1.OperatorParameter.ActualName = MutatorParameter.Name;
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| 224 |
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| 225 | variableCreator1.Name = "MutatedOffspring = true";
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| 226 | variableCreator1.CollectedValues.Add(new ValueParameter<BoolValue>("MutatedOffspring", null, new BoolValue(true), false));
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| 227 |
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| 228 | variableCreator2.Name = "MutatedOffspring = false";
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| 229 | variableCreator2.CollectedValues.Add(new ValueParameter<BoolValue>("MutatedOffspring", null, new BoolValue(false), false));
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| 230 |
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| 231 | conditionalSelector.ConditionParameter.ActualName = "MutatedOffspring";
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| 232 | conditionalSelector.ConditionParameter.Depth = 1;
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| 233 | conditionalSelector.CopySelected.Value = false;
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| 234 |
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| 235 | uniformSubScopesProcessor4.Parallel.Value = true;
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| 236 |
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| 237 | evaluator2.Name = "Evaluator (placeholder)";
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| 238 | evaluator2.OperatorParameter.ActualName = EvaluatorParameter.Name;
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| 239 |
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| 240 | subScopesCounter2.Name = "Increment EvaluatedSolutions";
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| 241 | subScopesCounter2.ValueParameter.ActualName = EvaluatedSolutionsParameter.Name;
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| 242 |
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| 243 | crossover2.Name = "Crossover (placeholder)";
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| 244 | crossover2.OperatorParameter.ActualName = CrossoverParameter.Name;
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| 245 |
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| 246 | mutationBranch2.ProbabilityParameter.ActualName = MutationProbabilityParameter.Name;
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| 247 | mutationBranch2.RandomParameter.ActualName = RandomParameter.Name;
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| 248 |
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| 249 | mutator2.Name = "Mutator (placeholder)";
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| 250 | mutator2.OperatorParameter.ActualName = MutatorParameter.Name;
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| 251 |
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| 252 | uniformSubScopesProcessor6.Parallel.Value = true;
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| 253 |
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| 254 | evaluator3.Name = "Evaluator (placeholder)";
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| 255 | evaluator3.OperatorParameter.ActualName = EvaluatorParameter.Name;
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| 256 |
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| 257 | subScopesCounter3.Name = "Increment EvaluatedSolutions";
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| 258 | subScopesCounter3.ValueParameter.ActualName = EvaluatedSolutionsParameter.Name;
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| 259 |
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| 260 | qualityComparer2.Name = "Quality Comparator (placeholder)";
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| 261 | qualityComparer2.OperatorParameter.ActualName = SubScopesQualityComparatorParameter.ActualName;
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| 262 |
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| 263 | subScopesRemover2.RemoveAllSubScopes = true;
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| 264 |
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| 265 | offspringSelector.Name = "OffspringSelector (placeholder)";
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| 266 | offspringSelector.OperatorParameter.ActualName = OffspringSelectorParameter.Name;
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| 267 |
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| 268 | bestSelector.CopySelected = new BoolValue(false);
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| 269 | bestSelector.MaximizationParameter.ActualName = MaximizationParameter.Name;
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| 270 | bestSelector.NumberOfSelectedSubScopesParameter.ActualName = ElitesParameter.Name;
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| 271 | bestSelector.QualityParameter.ActualName = QualityParameter.Name;
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| 272 |
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| 273 | worstSelector.CopySelected = new BoolValue(false);
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| 274 | worstSelector.MaximizationParameter.ActualName = MaximizationParameter.Name;
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| 275 | worstSelector.NumberOfSelectedSubScopesParameter.ActualName = ElitesParameter.Name;
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| 276 | worstSelector.QualityParameter.ActualName = QualityParameter.Name;
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| 277 |
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| 278 | reevaluateElitesBranch.ConditionParameter.ActualName = "ReevaluateElites";
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| 279 | reevaluateElitesBranch.Name = "Reevaluate elites ?";
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| 280 |
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| 281 | uniformSubScopesProcessor7.Parallel.Value = true;
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| 282 |
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| 283 | evaluator4.Name = "Evaluator (placeholder)";
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| 284 | evaluator4.OperatorParameter.ActualName = EvaluatorParameter.Name;
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| 285 |
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| 286 | subScopesCounter4.Name = "Increment EvaluatedSolutions";
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| 287 | subScopesCounter4.ValueParameter.ActualName = EvaluatedSolutionsParameter.Name;
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| 288 |
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| 289 | conditionalBranch.Name = "Enough children produced?";
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| 290 | conditionalBranch.ConditionParameter.ActualName = "EnoughChildrenGenerated";
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| 291 | conditionalBranch.FalseBranch = selector;
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| 292 | conditionalBranch.TrueBranch = subScopesProcessor3;
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| 293 | #endregion
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| 294 |
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| 295 | #region Create operator graph
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| 296 | OperatorGraph.InitialOperator = selector;
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| 297 | selector.Successor = subScopesProcessor1;
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| 298 | subScopesProcessor1.Operators.Add(new EmptyOperator());
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| 299 | subScopesProcessor1.Operators.Add(childrenCreator);
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| 300 | subScopesProcessor1.Successor = offspringSelector;
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| 301 | childrenCreator.Successor = osBeforeMutationBranch;
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| 302 | osBeforeMutationBranch.TrueBranch = uniformSubScopesProcessor1;
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| 303 | osBeforeMutationBranch.FalseBranch = uniformSubScopesProcessor5;
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| 304 | osBeforeMutationBranch.Successor = null;
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| 305 | uniformSubScopesProcessor1.Operator = crossover1;
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| 306 | uniformSubScopesProcessor1.Successor = uniformSubScopesProcessor2;
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| 307 | crossover1.Successor = null;
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| 308 | uniformSubScopesProcessor2.Operator = evaluator1;
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| 309 | uniformSubScopesProcessor2.Successor = subScopesCounter1;
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| 310 | evaluator1.Successor = qualityComparer1;
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| 311 | qualityComparer1.Successor = subScopesRemover1;
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| 312 | subScopesRemover1.Successor = null;
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| 313 | subScopesCounter1.Successor = uniformSubScopesProcessor3;
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| 314 | uniformSubScopesProcessor3.Operator = mutationBranch1;
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| 315 | uniformSubScopesProcessor3.Successor = conditionalSelector;
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| 316 | mutationBranch1.FirstBranch = mutator1;
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| 317 | mutationBranch1.SecondBranch = variableCreator2;
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| 318 | mutationBranch1.Successor = null;
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| 319 | mutator1.Successor = variableCreator1;
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| 320 | variableCreator1.Successor = null;
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| 321 | variableCreator2.Successor = null;
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| 322 | conditionalSelector.Successor = subScopesProcessor2;
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| 323 | subScopesProcessor2.Operators.Add(new EmptyOperator());
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| 324 | subScopesProcessor2.Operators.Add(uniformSubScopesProcessor4);
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| 325 | subScopesProcessor2.Successor = mergingReducer1;
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| 326 | uniformSubScopesProcessor4.Operator = evaluator2;
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| 327 | uniformSubScopesProcessor4.Successor = subScopesCounter2;
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| 328 | evaluator2.Successor = null;
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| 329 | subScopesCounter2.Successor = null;
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| 330 | mergingReducer1.Successor = null;
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| 331 | uniformSubScopesProcessor5.Operator = crossover2;
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| 332 | uniformSubScopesProcessor5.Successor = uniformSubScopesProcessor6;
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| 333 | crossover2.Successor = mutationBranch2;
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| 334 | mutationBranch2.FirstBranch = mutator2;
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| 335 | mutationBranch2.SecondBranch = null;
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| 336 | mutationBranch2.Successor = null;
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| 337 | mutator2.Successor = null;
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| 338 | uniformSubScopesProcessor6.Operator = evaluator3;
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| 339 | uniformSubScopesProcessor6.Successor = subScopesCounter3;
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| 340 | evaluator3.Successor = qualityComparer2;
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| 341 | qualityComparer2.Successor = subScopesRemover2;
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| 342 | subScopesRemover2.Successor = null;
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| 343 | subScopesCounter3.Successor = null;
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| 344 | offspringSelector.Successor = conditionalBranch;
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| 345 | subScopesProcessor3.Operators.Add(bestSelector);
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| 346 | subScopesProcessor3.Operators.Add(worstSelector);
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| 347 | subScopesProcessor3.Successor = mergingReducer2;
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| 348 | bestSelector.Successor = rightReducer;
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| 349 | rightReducer.Successor = reevaluateElitesBranch;
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| 350 | reevaluateElitesBranch.TrueBranch = uniformSubScopesProcessor7;
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| 351 | uniformSubScopesProcessor7.Operator = evaluator4;
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| 352 | uniformSubScopesProcessor7.Successor = subScopesCounter4;
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| 353 | subScopesCounter4.Successor = null;
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| 354 | reevaluateElitesBranch.FalseBranch = null;
|
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| 355 | reevaluateElitesBranch.Successor = null;
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| 356 | worstSelector.Successor = leftReducer;
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| 357 | leftReducer.Successor = null;
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| 358 | mergingReducer2.Successor = null;
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| 359 | #endregion
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| 360 | }
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| 361 |
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| 362 | public override IOperation Apply() {
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| 363 | if (CrossoverParameter.ActualValue == null)
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| 364 | return null;
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|---|
| 365 | return base.Apply();
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|---|
| 366 | }
|
|---|
| 367 | }
|
|---|
| 368 | }
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