source: stable/HeuristicLab.Optimization/3.3/BasicProblems/Operators/MultiObjectiveAnalyzer.cs

#region License Information
/* HeuristicLab
 * Copyright (C) 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.Collections.Generic;
using System.Linq;
using HeuristicLab.Common;
using HeuristicLab.Core;
using HeuristicLab.Data;
using HeuristicLab.Operators;
using HeuristicLab.Parameters;
using HEAL.Attic;

namespace HeuristicLab.Optimization {
  [Item("Multi-objective Analyzer", "Calls the Analyze method of the problem definition.")]
  [StorableType("903FE3D1-3179-4EA5-A7E1-63DE26239F9B")]
  public class MultiObjectiveAnalyzer : SingleSuccessorOperator, IMultiObjectiveAnalysisOperator, IStochasticOperator {
    public bool EnabledByDefault { get { return true; } }

    public ILookupParameter<IEncoding> EncodingParameter {
      get { return (ILookupParameter<IEncoding>)Parameters["Encoding"]; }
    }

    public IScopeTreeLookupParameter<DoubleArray> QualitiesParameter {
      get { return (IScopeTreeLookupParameter<DoubleArray>)Parameters["Qualities"]; }
    }

    public ILookupParameter<ResultCollection> ResultsParameter {
      get { return (ILookupParameter<ResultCollection>)Parameters["Results"]; }
    }

    public ILookupParameter<IRandom> RandomParameter {
      get { return (ILookupParameter<IRandom>)Parameters["Random"]; }
    }

    public Action<Individual[], double[][], ResultCollection, IRandom> AnalyzeAction { get; set; }

    [StorableConstructor]
    protected MultiObjectiveAnalyzer(StorableConstructorFlag _) : base(_) { }
    protected MultiObjectiveAnalyzer(MultiObjectiveAnalyzer original, Cloner cloner) : base(original, cloner) { }
    public MultiObjectiveAnalyzer() {
      Parameters.Add(new LookupParameter<IRandom>("Random", "The random number generator to use."));
      Parameters.Add(new LookupParameter<IEncoding>("Encoding", "An item that holds the problem's encoding."));
      Parameters.Add(new ScopeTreeLookupParameter<DoubleArray>("Qualities", "The qualities of the parameter vector."));
      Parameters.Add(new LookupParameter<ResultCollection>("Results", "The results collection to write to."));
    }

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

    public override IOperation Apply() {
      var encoding = EncodingParameter.ActualValue;
      var results = ResultsParameter.ActualValue;
      var random = RandomParameter.ActualValue;

      IEnumerable<IScope> scopes = new[] { ExecutionContext.Scope };
      for (var i = 0; i < QualitiesParameter.Depth; i++)
        scopes = scopes.Select(x => (IEnumerable<IScope>)x.SubScopes).Aggregate((a, b) => a.Concat(b));

      var individuals = scopes.Select(encoding.GetIndividual).ToArray();
      AnalyzeAction(individuals, QualitiesParameter.ActualValue.Select(x => x.ToArray()).ToArray(), results, random);
      return base.Apply();
    }
  }
}