source: branches/2895_PushGP_GenealogyAnalysis/HeuristicLab.Problems.ProgramSynthesis.GenealogyAnalysis/Analyzers/SelectionSchemeAnalyzer.cs @ 16568

#region License Information
/* HeuristicLab
 * Copyright (C) 2002-2015 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;
using HeuristicLab.Common;
using HeuristicLab.Core;
using HeuristicLab.Data;
using HeuristicLab.Optimization;
using HeuristicLab.Parameters;
using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;

namespace HeuristicLab.Problems.ProgramSynthesis {
  [Item("SelectionSchemeAnalyzer", "An analyzer which gives information about the relative amount of individuals that get selected each generation")]
  [StorableClass]
  public class SelectionSchemeAnalyzer : EvolutionTrackingAnalyzer {
    private const string StoreHistoryParameterName = "StoreHistory";

    public IFixedValueParameter<BoolValue> StoreHistoryParameter {
      get { return (IFixedValueParameter<BoolValue>)Parameters[StoreHistoryParameterName]; }
    }

    public SelectionSchemeAnalyzer() {
      UpdateCounterParameter.ActualName = "SelectionSchemeAnalyzerUpdateCounter";
      Parameters.Add(new FixedValueParameter<BoolValue>(StoreHistoryParameterName, new BoolValue(false)));
    }

    public bool StoreHistory { get { return StoreHistoryParameter.Value.Value; } }

    [StorableConstructor]
    protected SelectionSchemeAnalyzer(bool deserializing) : base(deserializing) { }

    protected SelectionSchemeAnalyzer(SelectionSchemeAnalyzer original, Cloner cloner) : base(original, cloner) { }

    public override IDeepCloneable Clone(Cloner cloner) {
      return new SelectionSchemeAnalyzer(this, cloner);
    }

    public override IOperation Apply() {
      int updateInterval = UpdateIntervalParameter.Value.Value;
      IntValue updateCounter = UpdateCounterParameter.ActualValue;
      // if counter does not yet exist then initialize it with update interval
      // to make sure the solutions are analyzed on the first application of this operator
      if (updateCounter == null) {
        updateCounter = new IntValue(0);
        UpdateCounterParameter.ActualValue = updateCounter;
      }
      updateCounter.Value++;
      //analyze solutions only every 'updateInterval' times
      if (updateCounter.Value != updateInterval) return base.Apply();
      updateCounter.Value = 0;

      if (PopulationGraph == null)
        return base.Apply();
      double selectionRatio = 1;

      if (Generations.Value > 0) {
        var previousRank = PopulationGraph.GetByRank(Generation.Value - 1);
        selectionRatio = (double)previousRank.Count(x => x.OutDegree > 0) / PopulationSize.Value;
      }

      // the selection ratio represents the percentage of the old population that survived to reproduce
      DataTable table;
      if (!Results.ContainsKey("SelectionRatio")) {
        table = new DataTable("Selection ratio");
        Results.Add(new Result("SelectionRatio", table));
        var row = new DataRow("Selection ratio") { VisualProperties = { StartIndexZero = true } };
        row.Values.Add(selectionRatio);
        table.Rows.Add(row);
      } else {
        table = (DataTable)Results["SelectionRatio"].Value;
        table.Rows["Selection ratio"].Values.Add(selectionRatio);
      }
      DataTable contributionCountTable;
      var contributions = PopulationGraph.GetByRank(Generation.Value - 1).OrderByDescending(x => x.Quality).Select(x => (double)x.OutDegree);
      if (Results.ContainsKey("ContributionCount")) {
        contributionCountTable = (DataTable)Results["ContributionCount"].Value;

        var row = contributionCountTable.Rows["Contribution count"];
        row.Values.Replace(contributions);
      } else {
        contributionCountTable = new DataTable("Contribution count");
        Results.Add(new Result("ContributionCount", contributionCountTable));
        var row = new DataRow("Contribution count") {
          VisualProperties = { StartIndexZero = true, ChartType = DataRowVisualProperties.DataRowChartType.Columns }
        };
        row.Values.AddRange(contributions);
        contributionCountTable.Rows.Add(row);
      }

      if (StoreHistory) {
        DataTableHistory history;
        if (Results.ContainsKey("ContributionCountHistory")) {
          history = (DataTableHistory)Results["ContributionCountHistory"].Value;
        } else {
          history = new DataTableHistory();
          Results.Add(new Result("ContributionCountHistory", history));
        }
        history.Add((DataTable)contributionCountTable.Clone());
      }
      return base.Apply();
    }
  }
}