source: branches/1614_GeneralizedQAP/HeuristicLab.Analysis.FitnessLandscape/3.3/ProblemCharacteristicAnalysis/GQAP/GQAPCharacteristicCalculator.cs @ 17573

#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;
using System.Collections.Generic;
using System.Linq;
using HEAL.Attic;
using HeuristicLab.Common;
using HeuristicLab.Core;
using HeuristicLab.Data;
using HeuristicLab.Optimization;
using HeuristicLab.Problems.GeneralizedQuadraticAssignment;

namespace HeuristicLab.Analysis.FitnessLandscape {
  [Item("GQAP Characteristic Calculator", "")]
  [StorableType("B587BC90-028E-4E8F-A4A6-5CD6677D5369")]
  public sealed class GQAPCharacteristicCalculator : CharacteristicCalculator {

    [StorableConstructor]
    private GQAPCharacteristicCalculator(StorableConstructorFlag _) : base(_) { }
    private GQAPCharacteristicCalculator(GQAPCharacteristicCalculator original, Cloner cloner) : base(original, cloner) { }
    public GQAPCharacteristicCalculator() {
      characteristics.AddRange(new[] {
        "Dimension", "MNRatio",
        "FlowDominance", "DistanceDominance",
        "FlowSparsity", "DistanceSparsity",
        "DemandDominance", "CapacityDominance",
        "Utilization", "BasicFeasibility",
      }.Select(x => new StringValue(x)).ToList());
    }

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

    public override bool CanCalculate() {
      return Problem is GQAP;
    }

    public override IEnumerable<IResult> Calculate() {
      var gqap = Problem as GQAP;
      if (gqap == null) throw new ArgumentException("Instance is not of type GQAP");
      var inst = gqap.ProblemInstance;
      foreach (var chara in characteristics.CheckedItems.Select(x => x.Value.Value)) {
        if (chara == "Dimension")
          yield return new Result(chara, new IntValue(inst.Demands.Length));
        if (chara == "MNRatio")
          yield return new Result(chara, new DoubleValue(inst.Capacities.Length / (double)inst.Demands.Length));
        if (chara == "FlowDominance")
          yield return new Result(chara, new DoubleValue(DoubleMatrixCharacteristicCalculator.CoeffVariationNonZeroes(inst.Weights)));
        if (chara == "DistanceDominance")
          yield return new Result(chara, new DoubleValue(DoubleMatrixCharacteristicCalculator.CoeffVariationNonZeroes(inst.Distances)));
        if (chara == "FlowSparsity")
          yield return new Result(chara, new DoubleValue(DoubleMatrixCharacteristicCalculator.Sparsity(inst.Weights)));
        if (chara == "DistanceSparsity")
          yield return new Result(chara, new DoubleValue(DoubleMatrixCharacteristicCalculator.Sparsity(inst.Distances)));
        if (chara == "DemandDominance")
          yield return new Result(chara, new DoubleValue(inst.Demands.StandardDeviation() / inst.Demands.Average()));
        if (chara == "CapacityDominance")
          yield return new Result(chara, new DoubleValue(inst.Capacities.StandardDeviation() / inst.Capacities.Average()));
        if (chara == "Utilization")
          yield return new Result(chara, new DoubleValue(inst.Demands.Sum() / inst.Capacities.Sum()));
        if (chara == "BasicFeasibility")
          yield return new Result(chara, new DoubleValue(inst.Demands.Select(d => inst.Capacities.Count(c => d <= c)).Average() / inst.Capacities.Length));
      }
    }
  }
}