source: branches/FitnessLandscapeAnalysis/HeuristicLab.Analysis.FitnessLandscape/Analysis/Aggregators/InformationAnalysisAggregator.cs @ 13365

using System;
using System.Collections.Generic;
using System.Drawing;
using System.Linq;
using HeuristicLab.Analysis.FitnessLandscape.DataTables;
using HeuristicLab.Common;
using HeuristicLab.Core;
using HeuristicLab.Optimization;
using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;

namespace HeuristicLab.Analysis.FitnessLandscape {

  [Item("InformationAnalysis Aggregator", "Aggregates information anlyses.")]
  [StorableClass]
  public class InformationAnalysisAggregator : Aggregator<InformationAnalysisTable> {

    [StorableConstructor]
    protected InformationAnalysisAggregator(bool deserializing) : base(deserializing) { }
    protected InformationAnalysisAggregator(InformationAnalysisAggregator original, Cloner cloner) : base(original, cloner) { }
    public InformationAnalysisAggregator() { }
    public override IDeepCloneable Clone(Cloner cloner) {
      return new InformationAnalysisAggregator(this, cloner);
    }

    public override IResult CreateResult() {
      return new Result("Information Analysis Summary", Aggregate(items, 10));
    }

    private class InformationAnalysis : IComparable<InformationAnalysis> {
      public double Delta { get; private set; }
      public double InformationContent { get; private set; }
      public double PartialInformationContent { get; private set; }
      public double DensityBasinInformation { get; private set; }
      public InformationAnalysis(double delta, double informationContent, double partialInformationContent, double densityBasinInformation) {
        Delta = delta;
        InformationContent = informationContent;
        PartialInformationContent = partialInformationContent;
        DensityBasinInformation = densityBasinInformation;
      }

      public int CompareTo(InformationAnalysis ia) {
        return Delta.CompareTo(ia.Delta);
      }

    }

    public static DataTable Aggregate(List<InformationAnalysisTable> informationAnalysisTables, int nQuantiles) {
      var values = new List<InformationAnalysis>();
      foreach (var table in informationAnalysisTables) {
        List<double> deltas = table.Rows["Quality Delta"].Values.ToList();
        for (int i = 0; i < deltas.Count; i++) {
          values.Add(new InformationAnalysis(
            deltas[i],
            table.Rows["Information Content"].Values[i],
            table.Rows["Partial Information Content"].Values[i],
            table.Rows["Density Basin Information"].Values[i]));
        }
      }
      values.Sort();
      Rows informationContent = new Rows("Information Content", Color.Red);
      Rows partialInformationContent = new Rows("Partial Information Content", Color.FromArgb(255, 0, 255));
      Rows densityBasinInformation = new Rows("Density Basin Information", Color.FromArgb(0, 255, 0));
      Rows qualityDelta = new Rows("Quality Delta", Color.Blue, true);
      var aggregatedValues = new List<InformationAnalysis>();
      var valueIt = values.GetEnumerator();
      int it = 0;
      for (int q = 0; q < nQuantiles; q++) {
        aggregatedValues.Clear();
        for (; it < values.Count * (q + 1) / nQuantiles && valueIt.MoveNext(); it++)
          aggregatedValues.Add(valueIt.Current);
        if (aggregatedValues.Count == 0)
          break;
        informationContent.AppendValues(aggregatedValues.Select(v => v.InformationContent));
        partialInformationContent.AppendValues(aggregatedValues.Select(v => v.PartialInformationContent));
        densityBasinInformation.AppendValues(aggregatedValues.Select(v => v.DensityBasinInformation));
        qualityDelta.AppendValues(aggregatedValues.Select(v => v.Delta));
      }
      DataTable summaryTable = new DataTable("Information Analysis Summary");
      informationContent.Incorporate(summaryTable);
      partialInformationContent.Incorporate(summaryTable);
      densityBasinInformation.Incorporate(summaryTable);
      qualityDelta.Incorporate(summaryTable);
      return summaryTable;
    }

    private class Rows {

      private DataRow MinRow, AvgRow, MaxRow;

      public Rows(string name, Color baseColor) {
        MaxRow = new DataRow(name + " Max");
        AvgRow = new DataRow(name + " Avg");
        MinRow = new DataRow(name + " Min");
        MaxRow.VisualProperties.Color = baseColor;
        AvgRow.VisualProperties.Color = Color.FromArgb(
          (int)Math.Round(baseColor.R * 0.75), 
          (int)Math.Round(baseColor.G * 0.75), 
          (int)Math.Round(baseColor.B * 0.75));
        MinRow.VisualProperties.Color = Color.FromArgb(
          (int)Math.Round(baseColor.R * 0.5),
          (int)Math.Round(baseColor.G * 0.5),
          (int)Math.Round(baseColor.B * 0.5));
      }

      public Rows(string name, Color baseColor, bool secondYAxis) : this(name, baseColor) {
        MinRow.VisualProperties.SecondYAxis = secondYAxis;
        AvgRow.VisualProperties.SecondYAxis = secondYAxis;
        MaxRow.VisualProperties.SecondYAxis = secondYAxis;
      }

      public void AppendValues(IEnumerable<double> values) {
        MinRow.Values.Add(values.Min());
        AvgRow.Values.Add(values.Average());
        MaxRow.Values.Add(values.Max());
      }

      public void Incorporate(DataTable table) {
        table.Rows.Add(MinRow);
        table.Rows.Add(AvgRow);
        table.Rows.Add(MaxRow);
      }
    }    
  }
}