source: branches/FitnessLandscapeAnalysis/HeuristicLab.Analysis.FitnessLandscape/Analysis/QualityTrailSummarizer.cs @ 7128

#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 <http://www.gnu.org/licenses/>.
 */
#endregion

using System.Linq;
using HeuristicLab.Analysis.FitnessLandscape.DataTables;
using HeuristicLab.Common;
using HeuristicLab.Core;
using HeuristicLab.Data;
using HeuristicLab.Operators;
using HeuristicLab.Optimization.Operators;
using HeuristicLab.Parameters;
using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
using System;

namespace HeuristicLab.Analysis.FitnessLandscape.Analysis {

  [StorableClass]
  public class QualityTrailSummarizer : AlgorithmOperator, IQualityTrailAnalyzer {

    #region Parameters
    public LookupParameter<DataTable> QualityTrailParameter {
      get { return (LookupParameter<DataTable>)Parameters["Quality Trail"]; }
    }
    public LookupParameter<QualityTrailSummaryTable> QualityTrailSummaryParameter {
      get { return (LookupParameter<QualityTrailSummaryTable>)Parameters["QualityTrailSummary"]; }
    }
    public LookupParameter<VariableCollection> ResultsParameter {
      get { return (LookupParameter<VariableCollection>)Parameters["Results"]; }
    }
    #endregion

    #region Construction & Cloning
    [StorableConstructor]
    protected QualityTrailSummarizer(bool deserializing) : base(deserializing) { }
    protected QualityTrailSummarizer(QualityTrailSummarizer original, Cloner cloner) : base(original, cloner) { }

    public QualityTrailSummarizer() {
      Parameters.Add(new LookupParameter<DataTable>("Quality Trail", "The quality of the solution"));
      Parameters.Add(new LookupParameter<QualityTrailSummaryTable>("QualityTrailSummary", "Maximum nr of steps between statistically significantly correlated quality values"));
      Parameters.Add(new LookupParameter<VariableCollection>("Results", "The collection of all results of this algorithm"));

      var resultsCollector = new ResultsCollector();
      resultsCollector.CollectedValues.Add(new LookupParameter<DataTable>(QualityTrailSummaryParameter.Name));

      OperatorGraph.InitialOperator = resultsCollector;
    }

    public override IDeepCloneable Clone(Cloner cloner) {
      return new QualityTrailSummarizer(this, cloner);
    }
    #endregion

    public override IOperation Apply() {
      QualityTrailSummaryTable qualityTrailSummary = CreateQualitytrailSummaryTable();
      DataTable qualityTrail = QualityTrailParameter.ActualValue;
      if (qualityTrail != null && qualityTrail.Rows.Count > 1) {
        var values = qualityTrail.Rows.First().Values;        
        DistributionAnalyzer analyzer = new DistributionAnalyzer(values);
        qualityTrailSummary.Rows["Value Quantiles"].Values.AddRange(new[] { 0, 0.25, 0.5, 0.75, 1 }.Select(q => analyzer[q]));
        double variance, kurtosis, skewness, mean;
        for (int i = 0; i < 4; i++) {
          int minIndex = (int)Math.Round(i*values.Count*0.25);
          int maxIndex = (int)Math.Round((i+1)*values.Count*0.25);
          alglib.samplemoments(
            values.GetRange(minIndex, maxIndex - minIndex).ToArray(),
            out mean, out variance, out skewness, out kurtosis);
          qualityTrailSummary.Rows["Epoch Averages"].Values.Add(mean);
          qualityTrailSummary.Rows["Epoch Variances"].Values.Add(variance);
          qualityTrailSummary.Rows["Epoch Skewnesses"].Values.Add(skewness);
          qualityTrailSummary.Rows["Epoch Kurtoses"].Values.Add(kurtosis);
        }
      }
      return base.Apply();
    }

    private QualityTrailSummaryTable CreateQualitytrailSummaryTable() {
      QualityTrailSummaryTable qualityTrailSummary = new QualityTrailSummaryTable("Quality Trail Summary");
      QualityTrailSummaryParameter.ActualValue = qualityTrailSummary;
      qualityTrailSummary.Rows.Add(new DataRow("Value Quantiles"));
      qualityTrailSummary.Rows.Add(new DataRow("Epoch Averages"));
      qualityTrailSummary.Rows.Add(new DataRow("Epoch Variances"));
      qualityTrailSummary.Rows.Add(new DataRow("Epoch Skewnesses"));
      qualityTrailSummary.Rows.Add(new DataRow("Epoch Kurtoses"));
      return qualityTrailSummary;
    }

  }
}