[9051] | 1 | #region License Information
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| 2 | /* HeuristicLab
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| 3 | * Copyright (C) 2002-2012 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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[9067] | 23 | using System.Collections.Generic;
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[9051] | 24 | using System.Linq;
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| 25 | using HeuristicLab.Algorithms.GeneticAlgorithm;
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| 26 | using HeuristicLab.Common;
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| 27 | using HeuristicLab.Core;
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| 28 | using HeuristicLab.Data;
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[9182] | 29 | using HeuristicLab.Operators;
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[9077] | 30 | using HeuristicLab.Optimization;
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[9051] | 31 | using HeuristicLab.Parameters;
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| 32 | using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
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[9077] | 33 | using HeuristicLab.Problems.DataAnalysis;
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[9051] | 34 | using HeuristicLab.Problems.DataAnalysis.Symbolic;
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[9077] | 35 | using HeuristicLab.Random;
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[9182] | 36 | using HeuristicLab.Selection;
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[9051] | 37 |
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| 38 | namespace HeuristicLab.Algorithms.DataAnalysis.Symbolic {
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| 39 | [Item("Symbolic DataAnalysis Island Genetic Algorithm", "A symbolic data analysis island genetic algorithm.")]
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[9182] | 40 | [Creatable("Data Analysis")]
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[9051] | 41 | [StorableClass]
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[9067] | 42 | public sealed class SymbolicDataAnalysisIslandGeneticAlgorithm : IslandGeneticAlgorithm {
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| 43 | private const string FixedSamplesParameterName = "NumberOfFixedSamples";
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[9077] | 44 | private const string FixedSamplesPartitionParameterName = "FixedSamplesPartition";
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[9067] | 45 | private const string FixedSamplesPartitionsParameterName = "FixedSamplesPartitions";
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| 46 | private const string RandomSamplesParameterName = "NumberOfRandomSamples";
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[9077] | 47 | private const string EvaluatorParameterName = "IslandEvaluator";
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| 48 | private const string ProblemEvaluatorParameterName = "ProblemEvaluator";
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[9051] | 49 |
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| 50 | #region Problem Properties
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| 51 | public override Type ProblemType {
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| 52 | get { return typeof(ISymbolicDataAnalysisSingleObjectiveProblem); }
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| 53 | }
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| 54 | public new ISymbolicDataAnalysisSingleObjectiveProblem Problem {
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| 55 | get { return (ISymbolicDataAnalysisSingleObjectiveProblem)base.Problem; }
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| 56 | set { base.Problem = value; }
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| 57 | }
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| 58 | #endregion
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| 59 |
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[9067] | 60 | #region parameters
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| 61 | public IFixedValueParameter<IntValue> FixedSamplesParameter {
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| 62 | get { return (IFixedValueParameter<IntValue>)Parameters[FixedSamplesParameterName]; }
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[9051] | 63 | }
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[9067] | 64 | public IValueParameter<ItemArray<IntRange>> FixedSamplesPartitionsParameter {
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| 65 | get { return (IValueParameter<ItemArray<IntRange>>)Parameters[FixedSamplesPartitionsParameterName]; }
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[9051] | 66 | }
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[9067] | 67 | public IFixedValueParameter<IntValue> RandomSamplesParameter {
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| 68 | get { return (IFixedValueParameter<IntValue>)Parameters[RandomSamplesParameterName]; }
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[9051] | 69 | }
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[9077] | 70 | public IValueParameter<ISymbolicDataAnalysisIslandGAEvaluator> EvaluatorParameter {
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| 71 | get { return (IValueParameter<ISymbolicDataAnalysisIslandGAEvaluator>)Parameters[EvaluatorParameterName]; }
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| 72 | }
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| 73 | private ILookupParameter<ISingleObjectiveEvaluator> ProblemEvaluatorParameter {
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| 74 | get { return (ILookupParameter<ISingleObjectiveEvaluator>)Parameters[ProblemEvaluatorParameterName]; }
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| 75 | }
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[9051] | 76 | #endregion
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| 77 |
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[9067] | 78 | #region properties
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| 79 | public int FixedSamples {
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| 80 | get { return FixedSamplesParameter.Value.Value; }
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| 81 | set { FixedSamplesParameter.Value.Value = value; }
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[9051] | 82 | }
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[9067] | 83 | public ItemArray<IntRange> FixedSamplesPartitions {
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| 84 | get { return FixedSamplesPartitionsParameter.Value; }
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| 85 | set { FixedSamplesPartitionsParameter.Value = value; }
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[9051] | 86 | }
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[9067] | 87 | public int RandomSamples {
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| 88 | get { return RandomSamplesParameter.Value.Value; }
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| 89 | set { RandomSamplesParameter.Value.Value = value; }
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[9051] | 90 | }
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| 91 | #endregion
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| 92 |
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| 93 | [StorableConstructor]
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| 94 | private SymbolicDataAnalysisIslandGeneticAlgorithm(bool deserializing) : base(deserializing) { }
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| 95 | [StorableHook(HookType.AfterDeserialization)]
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| 96 | private void AfterDeserialization() {
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[9067] | 97 | RegisterParameterEvents();
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[9051] | 98 | }
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| 99 | private SymbolicDataAnalysisIslandGeneticAlgorithm(SymbolicDataAnalysisIslandGeneticAlgorithm original, Cloner cloner)
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| 100 | : base(original, cloner) {
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[9067] | 101 | RegisterParameterEvents();
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[9051] | 102 | }
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| 103 | public override IDeepCloneable Clone(Cloner cloner) {
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| 104 | return new SymbolicDataAnalysisIslandGeneticAlgorithm(this, cloner);
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| 105 | }
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| 106 |
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| 107 | public SymbolicDataAnalysisIslandGeneticAlgorithm()
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| 108 | : base() {
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[9067] | 109 | Parameters.Add(new FixedValueParameter<IntValue>(FixedSamplesParameterName, "The number of fixed samples used for fitness calculation in each island.", new IntValue(0)));
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| 110 | Parameters.Add(new ValueParameter<ItemArray<IntRange>>(FixedSamplesPartitionsParameterName, "The fixed samples partitions used for fitness calculation for every island."));
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[9077] | 111 | Parameters.Add(new FixedValueParameter<IntValue>(RandomSamplesParameterName, "The number of random samples used for fitness calculation in each island.", new IntValue(0)));
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| 112 | Parameters.Add(new OptionalValueParameter<ISymbolicDataAnalysisIslandGAEvaluator>(EvaluatorParameterName, "The evaluator of the algorithm."));
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| 113 | Parameters.Add(new LookupParameter<ISingleObjectiveEvaluator>(ProblemEvaluatorParameterName, "Internal parameter for name translation", "Evaluator"));
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[9051] | 114 |
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[9172] | 115 | Elites.Value = 0;
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| 116 | ElitesParameter.Hidden = true;
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| 117 |
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[9077] | 118 | ScopeTreeAssigner<IntRange> fixedSamplesPartitionCreator = new ScopeTreeAssigner<IntRange>();
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| 119 | fixedSamplesPartitionCreator.LeftSideParameter.ActualName = FixedSamplesPartitionParameterName;
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| 120 | fixedSamplesPartitionCreator.RightSideParameter.ActualName = FixedSamplesPartitionsParameterName;
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| 121 |
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| 122 | RandomCreator insertionPoint = OperatorGraph.Iterate().OfType<RandomCreator>().Skip(1).First();
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| 123 | fixedSamplesPartitionCreator.Successor = insertionPoint.Successor;
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| 124 | insertionPoint.Successor = fixedSamplesPartitionCreator;
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| 125 |
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[9182] | 126 | //necessary to reevaluate elites
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| 127 | var evaluatorPlaceHolder = new Placeholder();
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| 128 | evaluatorPlaceHolder.OperatorParameter.ActualName = "Evaluator";
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| 129 |
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| 130 | UniformSubScopesProcessor subScopesProcessor = new UniformSubScopesProcessor();
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| 131 | subScopesProcessor.Name = "Reevaluate elites";
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| 132 | subScopesProcessor.Parallel.Value = true;
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| 133 | subScopesProcessor.Operator = evaluatorPlaceHolder;
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| 134 | OperatorGraph.Iterate().OfType<RightReducer>().First().Successor = subScopesProcessor;
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| 135 |
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[9067] | 136 | RegisterParameterEvents();
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| 137 | RecalculateFixedSamplesPartitions();
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| 138 | }
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[9051] | 139 |
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[9172] | 140 | private void RegisterParameterEvents() {
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| 141 | if (Problem != null) Problem.FitnessCalculationPartition.ValueChanged += Problem_Reset;
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| 142 | NumberOfIslandsParameter.ValueChanged += NumberOfIslandsParameter_ValueChanged;
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| 143 | NumberOfIslandsParameter.Value.ValueChanged += (o, ev) => RecalculateFixedSamplesPartitions();
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| 144 | FixedSamplesParameter.Value.ValueChanged += (o, e) => RecalculateFixedSamplesPartitions();
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| 145 | Analyzer.Operators.PropertyChanged += (o, e) => ParameterizeAnalyzers();
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| 146 | }
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| 147 |
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[9077] | 148 | protected override void Problem_EvaluatorChanged(object sender, EventArgs e) {
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| 149 | ParameterizeProblemEvaluator();
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| 150 | base.Problem_EvaluatorChanged(sender, e);
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| 151 | }
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| 152 |
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| 153 | private void ParameterizeProblemEvaluator() {
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| 154 | var regresssionEvaluator = Problem.Evaluator as ISymbolicDataAnalysisEvaluator<IRegressionProblemData>;
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| 155 | if (regresssionEvaluator != null) {
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| 156 | regresssionEvaluator.EvaluationPartitionParameter.ActualName = FixedSamplesPartitionParameterName;
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| 157 | }
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| 158 | var classificationEvaluator = Problem.Evaluator as ISymbolicDataAnalysisEvaluator<IClassificationProblemData>;
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| 159 | if (classificationEvaluator != null) {
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| 160 | classificationEvaluator.EvaluationPartitionParameter.ActualName = FixedSamplesPartitionParameterName;
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| 161 | }
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| 162 | }
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| 163 |
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| 164 | protected override void ParameterizeSolutionsCreator() {
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| 165 | base.ParameterizeSolutionsCreator();
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| 166 | SolutionsCreator.EvaluatorParameter.ActualName = EvaluatorParameterName;
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| 167 | }
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| 168 |
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| 169 | protected override void ParameterizeMainLoop() {
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| 170 | base.ParameterizeMainLoop();
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| 171 | MainLoop.EvaluatorParameter.ActualName = EvaluatorParameterName;
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| 172 | MainLoop.QualityParameter.ActualName = EvaluatorParameter.Value.QualityParameter.ActualName;
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| 173 | }
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| 174 |
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[9182] | 175 |
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[9172] | 176 | private void ParameterizeAnalyzers() {
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| 177 | foreach (var analyzer in Analyzer.Operators.OfType<ISymbolicDataAnalysisAnalyzer>()) {
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| 178 | IParameter evaluatorParameter;
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| 179 | if (analyzer.Parameters.TryGetValue("Evaluator", out evaluatorParameter)) {
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| 180 | ILookupParameter param = evaluatorParameter as ILookupParameter;
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| 181 | if (evaluatorParameter != null) param.ActualName = ProblemEvaluatorParameterName;
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| 182 | }
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| 183 | }
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[9067] | 184 | }
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[9051] | 185 |
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[9067] | 186 | private void NumberOfIslandsParameter_ValueChanged(object sender, EventArgs e) {
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| 187 | NumberOfIslands.ValueChanged += (o, ev) => RecalculateFixedSamplesPartitions();
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| 188 | RecalculateFixedSamplesPartitions();
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[9051] | 189 | }
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| 190 |
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[9067] | 191 | protected override void Problem_Reset(object sender, EventArgs e) {
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[9172] | 192 | FixedSamples = Problem.FitnessCalculationPartition.Size / NumberOfIslands.Value;
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| 193 | RandomSamples = Problem.FitnessCalculationPartition.Size / NumberOfIslands.Value;
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[9067] | 194 | RecalculateFixedSamplesPartitions();
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[9077] | 195 | ParameterizeProblemEvaluator();
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[9067] | 196 | base.Problem_Reset(sender, e);
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[9051] | 197 | }
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| 198 |
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| 199 | protected override void OnProblemChanged() {
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[9172] | 200 | Problem.FitnessCalculationPartition.ValueChanged += Problem_Reset;
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| 201 | FixedSamples = Problem.FitnessCalculationPartition.Size / NumberOfIslands.Value;
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| 202 | RandomSamples = Problem.FitnessCalculationPartition.Size / NumberOfIslands.Value;
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[9077] | 203 |
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| 204 | if (Problem is IRegressionProblem) {
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| 205 | var evaluator = new SymbolicDataAnalysisIslandGAEvaluator<IRegressionProblemData>();
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| 206 | evaluator.RandomSamplesParameter.ActualName = RandomSamplesParameterName;
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| 207 | EvaluatorParameter.Value = evaluator;
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| 208 | } else if (Problem is IClassificationProblem) {
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| 209 | var evaluator = new SymbolicDataAnalysisIslandGAEvaluator<IClassificationProblemData>();
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| 210 | evaluator.RandomSamplesParameter.ActualName = RandomSamplesParameterName;
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| 211 | EvaluatorParameter.Value = evaluator;
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| 212 | } else
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| 213 | EvaluatorParameter.Value = null;
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| 214 |
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[9172] | 215 | ParameterizeProblemEvaluator();
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[9077] | 216 | ParameterizeStochasticOperatorForIsland(EvaluatorParameter.Value);
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| 217 |
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[9067] | 218 | RecalculateFixedSamplesPartitions();
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[9077] | 219 | base.OnProblemChanged();
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[9051] | 220 | }
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| 221 |
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[9067] | 222 | private void RecalculateFixedSamplesPartitions() {
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| 223 | if (Problem == null) {
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| 224 | FixedSamplesPartitions = new ItemArray<IntRange>(Enumerable.Repeat(new IntRange(), NumberOfIslands.Value));
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| 225 | return;
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| 226 | }
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| 227 | var samplesStart = Problem.FitnessCalculationPartition.Start;
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| 228 | var samplesEnd = Problem.FitnessCalculationPartition.End;
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| 229 | var totalSamples = Problem.FitnessCalculationPartition.Size;
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| 230 | var fixedSamples = FixedSamples;
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| 231 | var islands = NumberOfIslands.Value;
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[9051] | 232 |
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[9067] | 233 | int offset = 0;
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| 234 | //fixed samples partition do not overlap
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| 235 | if (((double)totalSamples) / fixedSamples <= islands) {
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| 236 | offset = totalSamples / islands;
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| 237 | } else {
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| 238 | offset = (totalSamples - fixedSamples) / (islands - 1);
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[9051] | 239 | }
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[9067] | 240 |
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| 241 | List<IntRange> partitions = new List<IntRange>();
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| 242 | for (int i = 0; i < islands; i++) {
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| 243 | var partitionStart = samplesStart + offset * i;
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| 244 | partitions.Add(new IntRange(partitionStart, partitionStart + fixedSamples));
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[9051] | 245 | }
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[9067] | 246 |
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| 247 | //it can be the case that the last partitions exceeds the allowed samples
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| 248 | //move the last partition forward.
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| 249 | int exceedsSamples = partitions[partitions.Count - 1].End - samplesEnd;
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| 250 | if (exceedsSamples > 0) {
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| 251 | partitions[partitions.Count - 1].Start -= exceedsSamples;
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| 252 | partitions[partitions.Count - 1].End -= exceedsSamples;
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[9051] | 253 | }
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[9067] | 254 | FixedSamplesPartitions = new ItemArray<IntRange>(partitions);
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[9051] | 255 | }
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| 256 |
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| 257 | }
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| 258 | }
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