source: addons/HeuristicLab.Problems.BioBoost/HeuristicLab.Problems.BioBoost/3.3/Operators/Mutation/DistanceBasedIntegerVectorMutator.cs @ 15711

#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 HeuristicLab.BioBoost.ProblemDescription;
using HeuristicLab.Common;
using HeuristicLab.Core;
using HeuristicLab.Data;
using HeuristicLab.Encodings.IntegerVectorEncoding;
using HeuristicLab.Parameters;
using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
using System;
using System.Linq;

namespace HeuristicLab.BioBoost.Operators.Mutation {
  [StorableClass]
  public class DistanceBasedIntegerVectorMutator : IntegerVectorManipulator {


    #region Parameters
    public LookupParameter<DistanceMatrix> DistanceMatrixParameter { get { return (LookupParameter<DistanceMatrix>) Parameters["DistanceMatrix"]; } }
    public ValueParameter<BoolValue> DistanceMatrixInProblemDataParameter { get { return (ValueParameter<BoolValue>) Parameters["DistanceMatrixInProblemData"]; } }
    public ILookupParameter<BioBoostProblemData> ProblemDataParameter { get { return (ILookupParameter<BioBoostProblemData>) Parameters["ProblemData"]; } }
    public ILookupParameter<IntArray> ViableSourcesParameter { get { return (ILookupParameter<IntArray>) Parameters["ViableSources"]; } }
    public ILookupParameter<IntArray> ViableTargetsParameter { get { return (ILookupParameter<IntArray>) Parameters["ViableTargets"]; } }
    public IValueLookupParameter<DoubleValue> MaximumDistanceParameter { get { return (IValueLookupParameter<DoubleValue>) Parameters["MaximumDistance"]; } }

    #endregion

    #region Parameter Values
    public DistanceMatrix DistanceMatrix {
      get {
        if (DistanceMatrixInProblemData) {
          return ((IValueParameter<DistanceMatrix>) ProblemData.Parameters[DistanceMatrixParameter.ActualName]).Value;
        } else {
          return DistanceMatrixParameter.ActualValue;
        }
      }
    }
    public bool DistanceMatrixInProblemData { get { return DistanceMatrixInProblemDataParameter.Value.Value; } }
    public BioBoostProblemData ProblemData { get { return ProblemDataParameter.ActualValue; } }
    public IntArray ViableSources { get { return ViableSourcesParameter.ActualValue; } }
    public IntArray ViableTargets { get { return ViableTargetsParameter.ActualValue; } }
    public double MaximumDistance { get { return MaximumDistanceParameter.ActualValue.Value;  } }
    #endregion

    #region Construction & Cloning
    [StorableConstructor]
    protected DistanceBasedIntegerVectorMutator(bool isDeserializing) : base(isDeserializing) {}
    protected DistanceBasedIntegerVectorMutator(DistanceBasedIntegerVectorMutator orig, Cloner cloner) : base(orig, cloner) {}
    public DistanceBasedIntegerVectorMutator() {
      Parameters.Add(new LookupParameter<DistanceMatrix>("DistanceMatrix", "The distance matrix to use", "StreetDistanceMatrix")); // TODO: check this
      Parameters.Add(new ValueParameter<BoolValue>("DistanceMatrixInProblemData", "Whether to look for the distance matrix in problem data or in scope.", new BoolValue(true)));
      Parameters.Add(new LookupParameter<BioBoostProblemData>("ProblemData", "Contains fixed values describing the problem."));
      Parameters.Add(new LookupParameter<IntArray>("ViableSources", "A list with all indices of viable source regions."));
      Parameters.Add(new LookupParameter<IntArray>("ViableTargets", "A list with all indices of viable target regions."));
      Parameters.Add(new ValueLookupParameter<DoubleValue>("MaximumDistance", "the maximum distance from source to target allowed for mutation", new DoubleValue(Double.MaxValue)));
    }
    public override IDeepCloneable Clone(Cloner cloner) {
      return new DistanceBasedIntegerVectorMutator(this, cloner);
    }

    [StorableHook(HookType.AfterDeserialization)]
    private void AfterDeserialization() {
      if (!Parameters.ContainsKey("ViableSources"))
        Parameters.Add(new LookupParameter<IntArray>("ViableSources", "A list with all indices of viable source regions."));
      if (!Parameters.ContainsKey("ViableTargets"))
        Parameters.Add(new LookupParameter<IntArray>("ViableTargets", "A list with all indices of viable target regions."));
      if (!Parameters.ContainsKey("MaximumDistance"))
        Parameters.Add(new ValueLookupParameter<DoubleValue>("MaximumDistance", "the maximum distance from source to target allowed for mutation", new DoubleValue(Double.MaxValue)));
    }
    #endregion

    protected override void Manipulate(IRandom random, IntegerVector integerVector) {
      var sources = ViableSources ?? new IntArray(Enumerable.Range(0, integerVector.Length).ToArray());
      var targets = ViableTargets ?? new IntArray(Enumerable.Range(0, integerVector.Length).ToArray());
      var source = random.Next(sources.Length);
      var target = integerVector[sources[source]];
      var neighborDistances = new double[0].Select((d, idx) => new {index = idx, distance = d}).ToList();
      var distances = DistanceMatrix;
      var maxDistance = 0d;
      for (int j = 0; j < targets.Length; j++) {
        if (distances[source, targets[j]] > MaximumDistance) continue;
        var dist = distances[target, targets[j]];
        neighborDistances.Add(new {index = targets[j], distance = dist});
        maxDistance = Math.Max(dist, maxDistance);
      }
      neighborDistances = neighborDistances.Select(p => new {p.index, distance = maxDistance - p.distance}).ToList();
      neighborDistances.Sort((a, b) => b.distance.CompareTo(a.distance));
      var totalDistance = neighborDistances.Sum(p => p.distance);
      var threshold = random.NextDouble()*totalDistance;
      var sum = 0d;
      var index = 0;
      while (index < neighborDistances.Count && sum < threshold) {
        sum += neighborDistances[index].distance;
        index++;
      }
      if (index < 0 || index >= neighborDistances.Count) {
        integerVector[sources[source]] = sources[source];  // reset to local transport if no choices exist
      } else {
        integerVector[sources[source]] = neighborDistances[index].index;
      }
    }

  }
}