#region License Information
/* HeuristicLab
* Copyright (C) 2002-2010 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 HeuristicLab.Common;
using HeuristicLab.Core;
using HeuristicLab.Data;
using HeuristicLab.Optimization;
using HeuristicLab.Parameters;
using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
namespace HeuristicLab.Problems.DataAnalysis.Regression.Symbolic {
[Item("Symbolic Regression Problem (multi objective)", "Represents a multi objective symbolic regression problem.")]
[Creatable("Problems")]
[StorableClass]
public class MultiObjectiveSymbolicRegressionProblem : SymbolicRegressionProblemBase, IMultiObjectiveProblem {
#region Parameter Properties
public ValueParameter MaximizationParameter {
get { return (ValueParameter)Parameters["Maximization"]; }
}
IParameter IMultiObjectiveProblem.MaximizationParameter {
get { return MaximizationParameter; }
}
public new ValueParameter EvaluatorParameter {
get { return (ValueParameter)Parameters["Evaluator"]; }
}
IParameter IProblem.EvaluatorParameter {
get { return EvaluatorParameter; }
}
#endregion
#region Properties
public new IMultiObjectiveSymbolicRegressionEvaluator Evaluator {
get { return EvaluatorParameter.Value; }
set { EvaluatorParameter.Value = value; }
}
IMultiObjectiveEvaluator IMultiObjectiveProblem.Evaluator {
get { return EvaluatorParameter.Value; }
}
IEvaluator IProblem.Evaluator {
get { return EvaluatorParameter.Value; }
}
#endregion
[StorableConstructor]
protected MultiObjectiveSymbolicRegressionProblem(bool deserializing) : base(deserializing) { }
protected MultiObjectiveSymbolicRegressionProblem(MultiObjectiveSymbolicRegressionProblem original, Cloner cloner)
: base(original, cloner) {
RegisterParameterEvents();
RegisterParameterValueEvents();
}
public MultiObjectiveSymbolicRegressionProblem()
: base() {
var evaluator = new MultiObjectiveSymbolicRegressionMeanSquaredErrorEvaluator();
Parameters.Add(new ValueParameter("Maximization", "Set to false as the error of the regression model should be minimized.", new BoolArray(new bool[] { false, false })));
Parameters.Add(new ValueParameter("Evaluator", "The operator which should be used to evaluate symbolic regression solutions.", evaluator));
evaluator.QualitiesParameter.ActualName = "TrainingRSquared/Size";
ParameterizeEvaluator();
RegisterParameterEvents();
RegisterParameterValueEvents();
}
public override IDeepCloneable Clone(Cloner cloner) {
return new MultiObjectiveSymbolicRegressionProblem(this, cloner);
}
private void RegisterParameterValueEvents() {
EvaluatorParameter.ValueChanged += new EventHandler(EvaluatorParameter_ValueChanged);
}
private void RegisterParameterEvents() {
}
#region event handling
protected override void OnDataAnalysisProblemChanged(EventArgs e) {
base.OnDataAnalysisProblemChanged(e);
// paritions could be changed
ParameterizeEvaluator();
}
protected override void OnSolutionParameterNameChanged(EventArgs e) {
ParameterizeEvaluator();
}
protected override void OnEvaluatorChanged(EventArgs e) {
base.OnEvaluatorChanged(e);
ParameterizeEvaluator();
RaiseEvaluatorChanged(e);
}
#endregion
#region event handlers
private void EvaluatorParameter_ValueChanged(object sender, EventArgs e) {
OnEvaluatorChanged(e);
}
#endregion
#region Helpers
[StorableHook(HookType.AfterDeserialization)]
private void AfterDeserializationHook() {
RegisterParameterEvents();
RegisterParameterValueEvents();
}
private void ParameterizeEvaluator() {
Evaluator.SymbolicExpressionTreeParameter.ActualName = SolutionCreator.SymbolicExpressionTreeParameter.ActualName;
Evaluator.RegressionProblemDataParameter.ActualName = DataAnalysisProblemDataParameter.Name;
Evaluator.SamplesStartParameter.Value = TrainingSamplesStart;
Evaluator.SamplesEndParameter.Value = TrainingSamplesEnd;
}
#endregion
}
}