#region License Information
/* HeuristicLab
* Copyright (C) 2002-2012 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.Linq;
using HeuristicLab.Common;
using HeuristicLab.Core;
using HeuristicLab.Data;
using HeuristicLab.Encodings.ParameterConfigurationEncoding;
using HeuristicLab.Operators;
using HeuristicLab.Optimization;
using HeuristicLab.Parameters;
using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
namespace HeuristicLab.Problems.MetaOptimization {
///
/// An analyzer that records the best parameter configuration.
///
[Item("BestParameterConfigurationAnalyzer", "An analyzer that records the best parameter configuration.")]
[StorableClass]
public sealed class BestParameterConfigurationAnalyzer : SingleSuccessorOperator, IAnalyzer {
public bool EnabledByDefault {
get { return true; }
}
public ScopeTreeLookupParameter ParameterConfigurationParameter {
get { return (ScopeTreeLookupParameter)Parameters["ParameterConfigurationTree"]; }
}
public ScopeTreeLookupParameter QualityParameter {
get { return (ScopeTreeLookupParameter)Parameters["Quality"]; }
}
public LookupParameter BestSolutionParameter {
get { return (LookupParameter)Parameters["BestSolution"]; }
}
public ValueLookupParameter ResultsParameter {
get { return (ValueLookupParameter)Parameters["Results"]; }
}
public LookupParameter BestKnownQualityParameter {
get { return (LookupParameter)Parameters["BestKnownQuality"]; }
}
public LookupParameter BestKnownSolutionParameter {
get { return (LookupParameter)Parameters["BestKnownSolution"]; }
}
//public LookupParameter PopulationParameter {
// get { return (LookupParameter)Parameters["Population"]; }
//}
public LookupParameter MaximizationParameter {
get { return (LookupParameter)Parameters["Maximization"]; }
}
#region Constructors and Cloning
public BestParameterConfigurationAnalyzer()
: base() {
Parameters.Add(new ScopeTreeLookupParameter("ParameterConfigurationTree", ""));
Parameters.Add(new ScopeTreeLookupParameter("Quality", ""));
Parameters.Add(new LookupParameter("BestSolution", ""));
Parameters.Add(new ValueLookupParameter("Results", ""));
Parameters.Add(new LookupParameter("BestKnownQuality", ""));
Parameters.Add(new LookupParameter("BestKnownSolution", ""));
//Parameters.Add(new LookupParameter("Population", ""));
Parameters.Add(new LookupParameter("Maximization", "Set to false if the problem should be minimized."));
}
[StorableConstructor]
private BestParameterConfigurationAnalyzer(bool deserializing) : base(deserializing) { }
private BestParameterConfigurationAnalyzer(BestParameterConfigurationAnalyzer original, Cloner cloner) : base(original, cloner) { }
public override IDeepCloneable Clone(Cloner cloner) {
return new BestParameterConfigurationAnalyzer(this, cloner);
}
#endregion
public override IOperation Apply() {
ItemArray qualities = QualityParameter.ActualValue;
ResultCollection results = ResultsParameter.ActualValue;
DoubleValue bestKnownQuality = BestKnownQualityParameter.ActualValue;
ItemArray parameterTrees = ParameterConfigurationParameter.ActualValue;
bool maximization = MaximizationParameter.ActualValue.Value;
int idxBest;
if (maximization)
idxBest = qualities.Select((x, index) => new { index, x.Value }).OrderBy(x => x.Value).Last().index;
else
idxBest = qualities.Select((x, index) => new { index, x.Value }).OrderBy(x => x.Value).First().index;
ParameterConfigurationTree best = parameterTrees[idxBest];
IRun bestRun = new Run();
best.CollectResultValues(bestRun.Results);
best.CollectParameterValues(bestRun.Parameters);
if (bestKnownQuality == null ||
(!maximization && (qualities[idxBest].Value < bestKnownQuality.Value) ||
(maximization && (qualities[idxBest].Value > bestKnownQuality.Value)))) {
BestKnownQualityParameter.ActualValue = new DoubleValue(qualities[idxBest].Value);
BestKnownSolutionParameter.ActualValue = bestRun;
}
if (BestSolutionParameter.ActualValue == null) {
BestSolutionParameter.ActualValue = bestRun;
results.Add(new Result("Best Parameter Settings", bestRun));
} else {
BestSolutionParameter.ActualValue = bestRun;
results["Best Parameter Settings"].Value = bestRun;
}
// population (TODO: extract into PopulationAnalyzer)
//int i = 0;
//RunCollection rc = new RunCollection();
//foreach (ParameterConfigurationTree pt in (maximization ? parameterTrees.OrderByDescending(x => x.Quality) : parameterTrees.OrderBy(x => x.Quality))) {
// rc.Add(pt.ToRun(string.Format("Individual {0} ({1})", i, pt.ParameterInfoString), true));
// i++;
//}
//if (PopulationParameter.ActualValue == null) {
// PopulationParameter.ActualValue = rc;
// results.Add(new Result("Population", rc));
//} else {
// PopulationParameter.ActualValue = rc;
// results["Population"].Value = rc;
//}
return base.Apply();
}
}
}