source: branches/2989_MovingPeaksBenchmark/HeuristicLab.Problems.MovingPeaksBenchmark/3.3/Analyzers/BestMovingPeaksBenchmarkSolutionAnalyzer.cs @ 16611

#region License Information
/* HeuristicLab
 * Copyright (C) 2002-2019 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;
using System.Linq;
using HeuristicLab.Analysis;
using HeuristicLab.Common;
using HeuristicLab.Core;
using HeuristicLab.Data;
using HeuristicLab.Encodings.RealVectorEncoding;
using HeuristicLab.Operators;
using HeuristicLab.Optimization;
using HeuristicLab.Parameters;
using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;

namespace HeuristicLab.Problems.MovingPeaksBenchmark {
  /// <summary>
  /// An operator for analyzing the best solution for a SingleObjectiveTestFunction problem.
  /// </summary>
  [Item("BestMovingPeaksBenchmarkSolutionAnalyzer", "An operator for analyzing the best solution for a Moving Peaks Benchmark problem.")]
  [StorableClass]
  public class BestMovingPeaksBenchmarkSolutionAnalyzer : SingleSuccessorOperator, IBestMovingPeaksBenchmarkSolutionAnalyzer {
    public virtual bool EnabledByDefault {
      get { return true; }
    }

    public LookupParameter<BoolValue> MaximizationParameter {
      get { return (LookupParameter<BoolValue>)Parameters["Maximization"]; }
    }
    public ScopeTreeLookupParameter<RealVector> RealVectorParameter {
      get { return (ScopeTreeLookupParameter<RealVector>)Parameters["RealVector"]; }
    }
    ILookupParameter IBestMovingPeaksBenchmarkSolutionAnalyzer.RealVectorParameter {
      get { return RealVectorParameter; }
    }
    public ScopeTreeLookupParameter<DoubleValue> QualityParameter {
      get { return (ScopeTreeLookupParameter<DoubleValue>)Parameters["Quality"]; }
    }
    ILookupParameter IBestMovingPeaksBenchmarkSolutionAnalyzer.QualityParameter {
      get { return QualityParameter; }
    }
    public ILookupParameter<RealVector> BestKnownSolutionParameter {
      get { return (ILookupParameter<RealVector>)Parameters["BestKnownSolution"]; }
    }
    public ILookupParameter<DoubleValue> BestKnownQualityParameter {
      get { return (ILookupParameter<DoubleValue>)Parameters["BestKnownQuality"]; }
    }
    public IValueLookupParameter<ResultCollection> ResultsParameter {
      get { return (IValueLookupParameter<ResultCollection>)Parameters["Results"]; }
    }

    [StorableConstructor]
    protected BestMovingPeaksBenchmarkSolutionAnalyzer(bool deserializing) : base(deserializing) { }
    protected BestMovingPeaksBenchmarkSolutionAnalyzer(BestMovingPeaksBenchmarkSolutionAnalyzer original, Cloner cloner) : base(original, cloner) { }
    public BestMovingPeaksBenchmarkSolutionAnalyzer()
      : base() {
      Parameters.Add(new LookupParameter<BoolValue>("Maximization", "True if the problem is a maximization problem."));
      Parameters.Add(new ScopeTreeLookupParameter<RealVector>("RealVector", "The SingleObjectiveTestFunction solutions from which the best solution should be visualized."));
      Parameters.Add(new ScopeTreeLookupParameter<DoubleValue>("Quality", "The qualities of the SingleObjectiveTestFunction solutions which should be visualized."));
      Parameters.Add(new LookupParameter<RealVector>("BestKnownSolution", "The best known solution."));
      Parameters.Add(new LookupParameter<DoubleValue>("BestKnownQuality", "The quality of the best known solution."));
      Parameters.Add(new ValueLookupParameter<ResultCollection>("Results", "The result collection where the SingleObjectiveTestFunction solution should be stored."));

      MaximizationParameter.Hidden = true;
      RealVectorParameter.Hidden = true;
      QualityParameter.Hidden = true;
      BestKnownSolutionParameter.Hidden = true;
      BestKnownQualityParameter.Hidden = true;
      ResultsParameter.Hidden = true;
    }

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

    public override IOperation Apply() {
      ItemArray<RealVector> realVectors = RealVectorParameter.ActualValue;
      ItemArray<DoubleValue> qualities = QualityParameter.ActualValue;
      bool max = MaximizationParameter.ActualValue.Value;
      DoubleValue bestKnownQuality = BestKnownQualityParameter.ActualValue;

      int i = -1;
      if (!max) i = qualities.Select((x, index) => new { index, x.Value }).OrderBy(x => x.Value).First().index;
      else i = qualities.Select((x, index) => new { index, x.Value }).OrderByDescending(x => x.Value).First().index;

      if (bestKnownQuality == null ||
          max && qualities[i].Value > bestKnownQuality.Value
          || !max && qualities[i].Value < bestKnownQuality.Value) {
        BestKnownQualityParameter.ActualValue = new DoubleValue(qualities[i].Value);
        BestKnownSolutionParameter.ActualValue = (RealVector)realVectors[i].Clone();
      }

      RealVector best = (RealVector)realVectors[i].Clone();
      RealVector bestKnown = (RealVector)BestKnownSolutionParameter.ActualValue.Clone();
      ResultCollection results = ResultsParameter.ActualValue;
      IResult bestSolution, bestKnownSolution;
      if (!results.TryGetValue("Best Solution", out bestSolution)) {
        bestSolution = new Result("Best Solution", best);
        results.Add(bestSolution);
      } else {
        bestSolution.Value = best;
      }
      if (!results.TryGetValue("Best Known Solution", out bestKnownSolution)) {
        bestKnownSolution = new Result("Best Known Solution", bestKnown);
        results.Add(bestKnownSolution);
      } else {
        bestKnownSolution.Value = bestKnown;
      }

      double distanceToOptimum = 0;
      for (int j = 0; j < best.Length; j++) {
        distanceToOptimum += (best[j] - bestKnown[j]) * (best[j] - bestKnown[j]);
      }
      distanceToOptimum = Math.Sqrt(distanceToOptimum);

      IResult distanceTable;
      if (!results.TryGetValue("Distance to Optimum", out distanceTable)) {
        DataTable table = new DataTable("Distance to Optimum");
        table.Rows.Add(new DataRow("Distance to Optimum"));
        table.Rows["Distance to Optimum"].VisualProperties.StartIndexZero = true;
        distanceTable = new Result("Distance to Optimum", table);
        results.Add(distanceTable);
      }
      (distanceTable.Value as DataTable).Rows["Distance to Optimum"].Values.Add(distanceToOptimum);

      IResult offlineErrorTable;
      if (!results.TryGetValue("Offline Error Chart", out offlineErrorTable)) {
        DataTable table = new DataTable("Offline Error");
        table.Rows.Add(new DataRow("Offline Error"));
        table.Rows["Offline Error"].VisualProperties.StartIndexZero = true;
        offlineErrorTable = new Result("Offline Error Chart", table);
        results.Add(offlineErrorTable);
      }
      (offlineErrorTable.Value as DataTable).Rows["Offline Error"].Values.Add((results["Offline Error"].Value as DoubleValue).Value);

      return base.Apply();
    }
  }
}