#region License Information
/* HeuristicLab
* Copyright (C) 2002-2008 Heuristic and Evolutionary Algorithms Laboratory (HEAL)
*
* This file is part of HeuristicLab.
*
* HeuristicLab is free software: you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation, either version 3 of the License, or
* (at your option) any later version.
*
* HeuristicLab is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with HeuristicLab. If not, see .
*/
#endregion
using System;
using System.Collections.Generic;
using System.Linq;
using System.Text;
using HeuristicLab.Core;
using System.Xml;
using System.Diagnostics;
using HeuristicLab.DataAnalysis;
using HeuristicLab.Operators;
using HeuristicLab.Random;
using HeuristicLab.Selection;
using HeuristicLab.Logging;
using HeuristicLab.Data;
using HeuristicLab.Operators.Programmable;
using HeuristicLab.Selection.OffspringSelection;
using HeuristicLab.Evolutionary;
namespace HeuristicLab.GP.StructureIdentification {
public class OffspringSelectionGP : StandardGP {
public virtual int MaxEvaluatedSolutions {
get { return GetVariableInjector().GetVariable("MaxEvaluatedSolutions").GetValue().Data; }
set { GetVariableInjector().GetVariable("MaxEvaluatedSolutions").GetValue().Data = value; }
}
public virtual double SelectionPressureLimit {
get { return GetVariableInjector().GetVariable("SelectionPressureLimit").GetValue().Data; }
set { GetVariableInjector().GetVariable("SelectionPressureLimit").GetValue().Data = value; }
}
public virtual double ComparisonFactor {
get { return GetVariableInjector().GetVariable("ComparisonFactor").GetValue().Data; }
set { GetVariableInjector().GetVariable("ComparisonFactor").GetValue().Data = value; }
}
public virtual double SuccessRatioLimit {
get { return GetVariableInjector().GetVariable("SuccessRatioLimit").GetValue().Data; }
set { GetVariableInjector().GetVariable("SuccessRatioLimit").GetValue().Data = value; }
}
public override int MaxGenerations {
get { throw new NotSupportedException(); }
set { /* ignore */ }
}
public override int TournamentSize {
get { throw new NotSupportedException(); }
set { /* ignore */ }
}
public OffspringSelectionGP()
: base() {
PopulationSize = 1000;
Parents = 20;
MaxEvaluatedSolutions = 1000000;
SelectionPressureLimit = 300;
ComparisonFactor = 1.0;
SuccessRatioLimit = 1.0;
}
protected internal override IOperator CreateGlobalInjector() {
VariableInjector injector = (VariableInjector)base.CreateGlobalInjector();
injector.RemoveVariable("TournamentSize");
injector.RemoveVariable("MaxGenerations");
injector.AddVariable(new HeuristicLab.Core.Variable("MaxEvaluatedSolutions", new IntData()));
injector.AddVariable(new HeuristicLab.Core.Variable("ComparisonFactor", new DoubleData()));
injector.AddVariable(new HeuristicLab.Core.Variable("SelectionPressureLimit", new DoubleData()));
injector.AddVariable(new HeuristicLab.Core.Variable("SuccessRatioLimit", new DoubleData()));
return injector;
}
protected internal override IOperator CreateSelector() {
CombinedOperator selector = new CombinedOperator();
selector.Name = "Selector";
SequentialProcessor seq = new SequentialProcessor();
seq.Name = "Selector";
EmptyOperator emptyOp = new EmptyOperator();
ProportionalSelector femaleSelector = new ProportionalSelector();
femaleSelector.GetVariableInfo("Selected").ActualName = "Parents";
femaleSelector.GetVariableValue("CopySelected", null, false).Data = true;
RandomSelector maleSelector = new RandomSelector();
maleSelector.GetVariableInfo("Selected").ActualName = "Parents";
maleSelector.GetVariableValue("CopySelected", null, false).Data = true;
SequentialSubScopesProcessor seqSubScopesProc = new SequentialSubScopesProcessor();
RightChildReducer rightChildReducer = new RightChildReducer();
SubScopesMixer mixer = new SubScopesMixer();
seqSubScopesProc.AddSubOperator(femaleSelector);
seqSubScopesProc.AddSubOperator(emptyOp);
seq.AddSubOperator(maleSelector);
seq.AddSubOperator(seqSubScopesProc);
seq.AddSubOperator(rightChildReducer);
seq.AddSubOperator(mixer);
selector.OperatorGraph.AddOperator(seq);
selector.OperatorGraph.InitialOperator = seq;
return selector;
}
protected internal override IOperator CreateChildCreater() {
CombinedOperator childCreater = new CombinedOperator();
childCreater.Name = "Create children";
SequentialProcessor main = new SequentialProcessor();
SequentialProcessor seq = new SequentialProcessor();
SequentialProcessor offspringSelectionSeq = new SequentialProcessor();
OperatorExtractor selector = new OperatorExtractor();
selector.Name = "Selector (extr.)";
selector.GetVariableInfo("Operator").ActualName = "Selector";
SequentialSubScopesProcessor seqSubScopesProc = new SequentialSubScopesProcessor();
EmptyOperator emptyOp = new EmptyOperator();
OffspringSelector offspringSelector = new OffspringSelector();
ChildrenInitializer childInitializer = new ChildrenInitializer();
UniformSequentialSubScopesProcessor individualProc = new UniformSequentialSubScopesProcessor();
SequentialProcessor individualSeqProc = new SequentialProcessor();
OperatorExtractor crossover = new OperatorExtractor();
crossover.Name = "Crossover (extr.)";
crossover.GetVariableInfo("Operator").ActualName = "Crossover";
StochasticBranch cond = new StochasticBranch();
cond.GetVariableInfo("Probability").ActualName = "MutationRate";
OperatorExtractor manipulator = new OperatorExtractor();
manipulator.Name = "Manipulator (extr.)";
manipulator.GetVariableInfo("Operator").ActualName = "Manipulator";
OperatorExtractor evaluator = new OperatorExtractor();
evaluator.Name = "Evaluator (extr.)";
evaluator.GetVariableInfo("Operator").ActualName = "Evaluator";
Counter evalCounter = new Counter();
evalCounter.GetVariableInfo("Value").ActualName = "EvaluatedSolutions";
WeightedOffspringFitnessComparer offspringFitnessComparer = new WeightedOffspringFitnessComparer();
SubScopesRemover parentScopesRemover = new SubScopesRemover();
Sorter sorter = new Sorter();
sorter.GetVariableInfo("Descending").ActualName = "Maximization";
sorter.GetVariableInfo("Value").ActualName = "Quality";
UniformSequentialSubScopesProcessor validationEvaluator = new UniformSequentialSubScopesProcessor();
MeanSquaredErrorEvaluator validationQualityEvaluator = new MeanSquaredErrorEvaluator();
validationQualityEvaluator.Name = "ValidationMeanSquaredErrorEvaluator";
validationQualityEvaluator.GetVariableInfo("MSE").ActualName = "ValidationQuality";
validationQualityEvaluator.GetVariableInfo("SamplesStart").ActualName = "ValidationSamplesStart";
validationQualityEvaluator.GetVariableInfo("SamplesEnd").ActualName = "ValidationSamplesEnd";
main.AddSubOperator(seq);
seq.AddSubOperator(selector);
seq.AddSubOperator(seqSubScopesProc);
seqSubScopesProc.AddSubOperator(emptyOp);
seqSubScopesProc.AddSubOperator(offspringSelectionSeq);
seq.AddSubOperator(offspringSelector);
offspringSelector.AddSubOperator(seq);
offspringSelectionSeq.AddSubOperator(childInitializer);
offspringSelectionSeq.AddSubOperator(individualProc);
offspringSelectionSeq.AddSubOperator(sorter);
individualProc.AddSubOperator(individualSeqProc);
individualSeqProc.AddSubOperator(crossover);
individualSeqProc.AddSubOperator(cond);
cond.AddSubOperator(manipulator);
individualSeqProc.AddSubOperator(evaluator);
individualSeqProc.AddSubOperator(evalCounter);
individualSeqProc.AddSubOperator(offspringFitnessComparer);
individualSeqProc.AddSubOperator(parentScopesRemover);
SequentialSubScopesProcessor seqSubScopesProc2 = new SequentialSubScopesProcessor();
main.AddSubOperator(seqSubScopesProc2);
seqSubScopesProc2.AddSubOperator(emptyOp);
SequentialProcessor newGenProc = new SequentialProcessor();
newGenProc.AddSubOperator(sorter);
newGenProc.AddSubOperator(validationEvaluator);
seqSubScopesProc2.AddSubOperator(newGenProc);
validationEvaluator.AddSubOperator(validationQualityEvaluator);
childCreater.OperatorGraph.AddOperator(main);
childCreater.OperatorGraph.InitialOperator = main;
return childCreater;
}
protected internal override IOperator CreateLoopCondition(IOperator loop) {
SequentialProcessor seq = new SequentialProcessor();
seq.Name = "Loop Condition";
LessThanComparator generationsComparator = new LessThanComparator();
generationsComparator.GetVariableInfo("LeftSide").ActualName = "EvaluatedSolutions";
generationsComparator.GetVariableInfo("RightSide").ActualName = "MaxEvaluatedSolutions";
generationsComparator.GetVariableInfo("Result").ActualName = "EvaluatedSolutionsCondition";
LessThanComparator selPresComparator = new LessThanComparator();
selPresComparator.GetVariableInfo("LeftSide").ActualName = "SelectionPressure";
selPresComparator.GetVariableInfo("RightSide").ActualName = "SelectionPressureLimit";
selPresComparator.GetVariableInfo("Result").ActualName = "SelectionPressureCondition";
ConditionalBranch generationsCond = new ConditionalBranch();
generationsCond.GetVariableInfo("Condition").ActualName = "EvaluatedSolutionsCondition";
ConditionalBranch selPresCond = new ConditionalBranch();
selPresCond.GetVariableInfo("Condition").ActualName = "SelectionPressureCondition";
seq.AddSubOperator(generationsComparator);
seq.AddSubOperator(selPresComparator);
seq.AddSubOperator(generationsCond);
generationsCond.AddSubOperator(selPresCond);
selPresCond.AddSubOperator(loop);
return seq;
}
protected internal override IOperator CreateLoggingOperator() {
CombinedOperator loggingOperator = new CombinedOperator();
loggingOperator.Name = "Logging";
SequentialProcessor seq = new SequentialProcessor();
DataCollector collector = new DataCollector();
ItemList names = collector.GetVariable("VariableNames").GetValue>();
names.Add(new StringData("BestQuality"));
names.Add(new StringData("AverageQuality"));
names.Add(new StringData("WorstQuality"));
names.Add(new StringData("BestValidationQuality"));
names.Add(new StringData("AverageValidationQuality"));
names.Add(new StringData("WorstValidationQuality"));
names.Add(new StringData("EvaluatedSolutions"));
names.Add(new StringData("SelectionPressure"));
QualityLogger qualityLogger = new QualityLogger();
QualityLogger validationQualityLogger = new QualityLogger();
validationQualityLogger.Name = "ValidationQualityLogger";
validationQualityLogger.GetVariableInfo("Quality").ActualName = "ValidationQuality";
validationQualityLogger.GetVariableInfo("QualityLog").ActualName = "ValidationQualityLog";
seq.AddSubOperator(collector);
seq.AddSubOperator(qualityLogger);
seq.AddSubOperator(validationQualityLogger);
loggingOperator.OperatorGraph.AddOperator(seq);
loggingOperator.OperatorGraph.InitialOperator = seq;
return loggingOperator;
}
public override IEditor CreateEditor() {
return new OffspringSelectionGpEditor(this);
}
public override IView CreateView() {
return new OffspringSelectionGpEditor(this);
}
public override object Clone(IDictionary clonedObjects) {
OffspringSelectionGP clone = (OffspringSelectionGP)base.Clone(clonedObjects);
clone.SelectionPressureLimit = SelectionPressureLimit;
clone.SuccessRatioLimit = SuccessRatioLimit;
clone.ComparisonFactor = ComparisonFactor;
return clone;
}
}
}