using System.Linq;
using HeuristicLab.Analysis;
using HeuristicLab.Common;
using HeuristicLab.Core;
using HeuristicLab.Data;
using HeuristicLab.Operators;
using HeuristicLab.Optimization;
using HeuristicLab.Parameters;
using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
namespace HeuristicLab.Problems.MetaOptimization {
///
/// TODO
///
[Item("PMOProblemQualitiesAnalyzer", "")]
[StorableClass]
public sealed class PMOProblemQualitiesAnalyzer : 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 ValueLookupParameter ResultsParameter {
get { return (ValueLookupParameter)Parameters["Results"]; }
}
public LookupParameter> ProblemsParameter {
get { return (LookupParameter>)Parameters[MetaOptimizationProblem.ProblemsParameterName]; }
}
public LookupParameter MaximizationParameter {
get { return (LookupParameter)Parameters["Maximization"]; }
}
public PMOProblemQualitiesAnalyzer()
: base() {
Parameters.Add(new ScopeTreeLookupParameter("ParameterConfigurationTree", ""));
Parameters.Add(new ScopeTreeLookupParameter("Quality", ""));
Parameters.Add(new ValueLookupParameter("Results", ""));
Parameters.Add(new LookupParameter>(MetaOptimizationProblem.ProblemsParameterName));
Parameters.Add(new LookupParameter("Maximization", "Set to false if the problem should be minimized."));
}
[StorableConstructor]
private PMOProblemQualitiesAnalyzer(bool deserializing) : base(deserializing) { }
private PMOProblemQualitiesAnalyzer(PMOProblemQualitiesAnalyzer original, Cloner cloner) : base(original, cloner) { }
public override IDeepCloneable Clone(Cloner cloner) {
return new PMOProblemQualitiesAnalyzer(this, cloner);
}
public override IOperation Apply() {
ItemArray qualities = QualityParameter.ActualValue;
ResultCollection results = ResultsParameter.ActualValue;
ItemArray parameterTrees = ParameterConfigurationParameter.ActualValue;
bool maximization = MaximizationParameter.ActualValue.Value;
int idxBest;
int idxWorst;
if (maximization) {
idxBest = qualities.Select((x, index) => new { index, x.Value }).OrderBy(x => x.Value).Last().index;
idxWorst = qualities.Select((x, index) => new { index, x.Value }).OrderBy(x => x.Value).First().index;
} else {
idxBest = qualities.Select((x, index) => new { index, x.Value }).OrderBy(x => x.Value).First().index;
idxWorst = qualities.Select((x, index) => new { index, x.Value }).OrderBy(x => x.Value).Last().index;
}
int problemCount = ProblemsParameter.ActualValue.Count;
double[][] problemQualities = GetProblemQualities(parameterTrees, problemCount);
for (int i = 0; i < problemCount; i++) {
DataTable problemQualitiesDataTable;
string resultKey = "Problem." + i;
if (!results.ContainsKey(resultKey)) {
problemQualitiesDataTable = new DataTable();
problemQualitiesDataTable.Name = resultKey + " Qualities";
results.Add(new Result(resultKey, problemQualitiesDataTable));
} else {
problemQualitiesDataTable = results[resultKey].Value as DataTable;
}
AddValue(problemQualitiesDataTable, parameterTrees[idxBest].AverageQualities[i], "BestQuality", "BestQuality");
AddValue(problemQualitiesDataTable, problemQualities[i].Average(), "AverageQuality", "BestQuality");
AddValue(problemQualitiesDataTable, parameterTrees[idxWorst].AverageQualities[i], "WorstQuality", "BestQuality");
}
return base.Apply();
}
private static double[][] GetProblemQualities(ItemArray parameterTrees, int problemCount) {
double[][] problemQualities = new double[problemCount][];
for (int i = 0; i < problemCount; i++) {
problemQualities[i] = new double[parameterTrees.Length];
for (int j = 0; j < parameterTrees.Length; j++) {
problemQualities[i][j] = parameterTrees[j].AverageQualities[i];
}
}
return problemQualities;
}
private static void AddValue(DataTable table, double data, string name, string description) {
DataRow row;
table.Rows.TryGetValue(name, out row);
if (row == null) {
row = new DataRow(name, description);
row.Values.Add(data);
table.Rows.Add(row);
} else {
row.Values.Add(data);
}
}
}
}