source: branches/LearningClassifierSystems/HeuristicLab.Optimization.Operators.LCS/3.3/Discretizer/UniformWidthDiscretizer.cs @ 9385

#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.Persistence.Default.CompositeSerializers.Storable;

namespace HeuristicLab.Optimization.Operators.LCS {
  [StorableClass]
  [Item("UniformWidthDiscretizer", "")]
  public class UniformWidthDiscretizer : Item, IDiscretizer {

    [Storable]
    private int bins;

    [Storable]
    private IDictionary<string, IList<double>> variableMicroItervals;

    [StorableConstructor]
    protected UniformWidthDiscretizer(bool deserializing) : base(deserializing) { }
    protected UniformWidthDiscretizer(UniformWidthDiscretizer original, Cloner cloner)
      : base(original, cloner) {
    }
    public UniformWidthDiscretizer()
      : base() {
      bins = 5;
    }
    public UniformWidthDiscretizer(int bins)
      : base() {
      variableMicroItervals = new Dictionary<string, IList<double>>();
      this.bins = bins;
    }
    public override IDeepCloneable Clone(Cloner cloner) {
      return new UniformWidthDiscretizer(this, cloner);
    }

    public int NumberOfMicroIntervals(string attribute) {
      return bins;
    }

    public IEnumerable<double> discretizeValues(string attribute, IEnumerable<double> values) {
      if (variableMicroItervals.ContainsKey(attribute)) {
        throw new ArgumentException("Values of attribute " + attribute + " are already set.");
      }

      double min = values.Min();
      double max = values.Max();

      double intervalWidth = (max - min) / bins;
      List<double> cutPoints = new List<double>(bins - 1);
      double val = min;
      for (int i = 0; i < bins - 1; i++) {
        val += intervalWidth;
        cutPoints.Add(val);
      }

      variableMicroItervals[attribute] = cutPoints;

      return cutPoints;
    }

    public IEnumerable<double> GetCutPoints(string attribute) {
      return variableMicroItervals[attribute];
    }
  }
}