using System.Linq;
using HeuristicLab.Common;
using HeuristicLab.Core;
using HeuristicLab.Data;
using HeuristicLab.Operators;
using HeuristicLab.Optimization;
using HeuristicLab.Parameters;
using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
using System.Collections.Generic;
using System;
namespace HeuristicLab.Problems.MetaOptimization {
///
/// TODO An operator for analyzing the best solution of Traveling Salesman Problems given in path representation using city coordinates.
///
[Item("BestParameterConfigurationAnalyzer", "")]
[StorableClass]
public sealed class BestParameterConfigurationAnalyzer : SingleSuccessorOperator, IAnalyzer {
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 ProblemQualityReferencesParameter {
get { return (LookupParameter)Parameters["ProblemQualityReferences"]; }
}
public LookupParameter> ProblemsParameter {
get { return (LookupParameter>)Parameters[MetaOptimizationProblem.ProblemsParameterName]; }
}
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("ProblemQualityReferences", ""));
Parameters.Add(new LookupParameter>(MetaOptimizationProblem.ProblemsParameterName));
}
[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);
}
public override IOperation Apply() {
ItemArray qualities = QualityParameter.ActualValue;
ResultCollection results = ResultsParameter.ActualValue;
DoubleValue bestKnownQuality = BestKnownQualityParameter.ActualValue;
ItemArray parameterTrees = ParameterConfigurationParameter.ActualValue;
int idxBest = qualities.Select((x, index) => new { index, x.Value }).OrderBy(x => x.Value).First().index;
ParameterConfigurationTree best = (ParameterConfigurationTree)parameterTrees[idxBest];
IRun bestRun = new Run();
best.CollectResultValues(bestRun.Results);
best.CollectParameterValues(bestRun.Parameters);
if (bestKnownQuality == null || qualities[idxBest].Value < bestKnownQuality.Value) { // todo: respect Maximization:true/false
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
int i = 0;
RunCollection rc = new RunCollection();
foreach (ParameterConfigurationTree pt in parameterTrees.OrderBy(x => x.AverageQualityNormalized)) { // todo: respect Maximization:true/false
IRun run = new Run();
run.Name = string.Format("Individuum ({0})", i);
pt.CollectResultValues(run.Results);
pt.CollectParameterValues(run.Parameters);
rc.Add(run);
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();
}
}
}