source: branches/HeuristicLab.Problems.MultiObjectiveTestFunctions/HeuristicLab.Problems.MultiObjectiveTestFunctions/3.3/Analyzers/CrowdingAnalyzer.cs @ 14044

#region License Information
/* HeuristicLab
 * Copyright (C) 2002-2016 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.Common;
using HeuristicLab.Core;
using HeuristicLab.Data;
using HeuristicLab.Optimization;
using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;

namespace HeuristicLab.Problems.MultiObjectiveTestFunctions {
  [StorableClass]
  [Item("CrowdingAnalyzer", "The mean crowding distance for each point of the Front (see Multi-Objective Performance Metrics - Shodhganga for more information)")]
  public class CrowdingAnalyzer : MOTFAnalyzer {

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

    public CrowdingAnalyzer() { }

    public override IOperation Apply() {
      var results = ResultsParameter.ActualValue;
      var qualities = QualitiesParameter.ActualValue;
      var testFunction = TestFunctionParameter.ActualValue;
      int objectives = qualities[0].Length;

      if (!results.ContainsKey("Crowding")) results.Add(new Result("Crowding", new DoubleValue()));
      var resultValue = (DoubleValue)results["Crowding"].Value;

      var crowdingDistance = Crowding.Calculate(qualities.Select(x => x.ToArray()), testFunction.Bounds(objectives));
      resultValue.Value = crowdingDistance;

      return base.Apply();
    }

  }
}