#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 .
*/
#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> 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>();
this.bins = bins;
}
public override IDeepCloneable Clone(Cloner cloner) {
return new UniformWidthDiscretizer(this, cloner);
}
public int NumberOfMicroIntervals(string attribute) {
return bins;
}
public IEnumerable discretizeValues(string attribute, IEnumerable 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 cutPoints = new List(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 GetCutPoints(string attribute) {
return variableMicroItervals[attribute];
}
}
}