source: branches/LearningClassifierSystems/HeuristicLab.Problems.CombinedIntegerVectorClassification/3.3/CombinedIntegerVectorClassificationProblemData.cs @ 9844

#region License Information
/* HeuristicLab
 * Copyright (C) 2002-2012 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.Encodings.CombinedIntegerVectorEncoding;
using HeuristicLab.Encodings.ConditionActionEncoding;
using HeuristicLab.Parameters;
using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
using HeuristicLab.Problems.ConditionActionClassification;
using HeuristicLab.Problems.DataAnalysis;

namespace HeuristicLab.Problems.CombinedIntegerVectorClassification {
  [StorableClass]
  [Item("CombinedIntegerVectorClassificationProblemData", "A problem data for LCS.")]
  public class CombinedIntegerVectorClassificationProblemData : ConditionActionClassificationProblemData, ICombinedIntegerVectorClassificationProblemData {

    #region parameter properites
    public IFixedValueParameter<IntValue> LengthParameter {
      get { return (IFixedValueParameter<IntValue>)Parameters["Length"]; }
    }
    public IFixedValueParameter<IntValue> ActionLengthParameter {
      get { return (IFixedValueParameter<IntValue>)Parameters["ActionLength"]; }
    }
    public IValueParameter<IntMatrix> BoundsParameter {
      get { return (IValueParameter<IntMatrix>)Parameters["Bounds"]; }
    }
    #endregion

    #region properties
    public IntValue Length {
      get { return LengthParameter.Value; }
    }
    public IntValue ActionLength {
      get { return ActionLengthParameter.Value; }
    }
    public IntMatrix Bounds {
      get { return BoundsParameter.Value; }
    }
    public CombinedIntegerVectorComparer ConcreteClassifierComparer {
      get { return new CombinedIntegerVectorComparer(); }
    }
    public override IClassifierComparer ClassifierComparer {
      get { return ConcreteClassifierComparer; }
    }
    #endregion

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

    public CombinedIntegerVectorClassificationProblemData(Dataset dataset, IEnumerable<string> allowedConditionVariables, IEnumerable<string> allowedActionVariables) :
      base(dataset, allowedConditionVariables, allowedActionVariables) {
      Parameters.Add(new FixedValueParameter<IntValue>("Length", "", new IntValue(allowedConditionVariables.Count() + allowedActionVariables.Count())));
      Parameters.Add(new FixedValueParameter<IntValue>("ActionLength", "", new IntValue(allowedActionVariables.Count())));
      Parameters.Add(new ValueParameter<IntMatrix>("Bounds", "", GetBoundsMatrix(dataset, allowedConditionVariables, allowedActionVariables)));
    }

    private IntMatrix GetBoundsMatrix(Dataset dataset, IEnumerable<string> conditionVariables, IEnumerable<string> actionVariables) {
      IntMatrix bounds = new IntMatrix(conditionVariables.Count() + actionVariables.Count(), 2);
      int index = 0;
      foreach (var variable in conditionVariables) {
        var values = dataset.GetDoubleValues(variable);
        bounds[index, 0] = (int)values.Min();
        bounds[index, 1] = (int)values.Max() + 2;
        index++;
      }
      foreach (var variable in actionVariables) {
        var values = dataset.GetDoubleValues(variable);
        bounds[index, 0] = (int)values.Min();
        bounds[index, 1] = (int)values.Max() + 1;
        index++;
      }
      return bounds;
    }

    public override IInput FetchInput(int rowNumber) {
      if (!fetchInputCache.ContainsKey(rowNumber)) {
        int[] elements = new int[Length.Value];
        var variableNamesList = Dataset.VariableNames.ToList();
        int elementIndex = 0;
        for (int i = 0; i < variableNamesList.Count; i++) {
          if (AllowedConditionVariables.Contains(variableNamesList[i])) {
            elements[elementIndex] = int.Parse(Dataset.GetValue(rowNumber, i));
            elementIndex++;
          }
        }
        for (int i = 0; i < variableNamesList.Count; i++) {
          if (AllowedActionVariables.Contains(variableNamesList[i])) {
            elements[elementIndex] = int.Parse(Dataset.GetValue(rowNumber, i));
            elementIndex++;
          }
        }
        if (elementIndex != Length.Value) {
          throw new ArgumentException("Length of classifier is not equal to the number of allowed condition + action variables.");
        }
        fetchInputCache.Add(rowNumber, new CombinedIntegerVector(elements, ActionLengthParameter.Value.Value, BoundsParameter.Value));
      }
      return fetchInputCache[rowNumber];
    }

    public override IAction FetchAction(int rowNumber) {
      return (FetchInput(rowNumber) as IClassifier).Action;
    }

    protected override void ActionConditionVariablesChanged() {
      ActionLength.Value = AllowedActionVariables.Count();
      Length.Value = AllowedConditionVariables.Count() + ActionLength.Value;
      BoundsParameter.Value = GetBoundsMatrix(Dataset, AllowedConditionVariables, AllowedActionVariables);
    }
  }
}