#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 .
*/
#endregion
using System;
using System.Collections.Generic;
using System.Linq;
using HeuristicLab.Common;
using HeuristicLab.Core;
using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
using HeuristicLab.Problems.DataAnalysis;
namespace HeuristicLab.Algorithms.DataAnalysis {
[Obsolete("Use transformation classes in Problems.DataAnalysis instead")]
[StorableClass]
[Item(Name = "Scaling", Description = "Contains information about scaling of variables for data-analysis algorithms.")]
public class Scaling : Item {
[Storable]
private Dictionary> scalingParameters = new Dictionary>();
[StorableConstructor]
protected Scaling(bool deserializing) : base(deserializing) { }
protected Scaling(Scaling original, Cloner cloner)
: base(original, cloner) {
foreach (var pair in original.scalingParameters)
scalingParameters.Add(pair.Key, Tuple.Create(pair.Value.Item1, pair.Value.Item2));
}
public Scaling(IDataset ds, IEnumerable variables, IEnumerable rows) {
foreach (var variable in variables) {
var values = ds.GetDoubleValues(variable, rows);
var min = values.Where(x => !double.IsNaN(x)).Min();
var max = values.Where(x => !double.IsNaN(x)).Max();
scalingParameters[variable] = Tuple.Create(min, max);
}
}
public override IDeepCloneable Clone(Cloner cloner) {
return new Scaling(this, cloner);
}
public IEnumerable GetScaledValues(IDataset ds, string variable, IEnumerable rows) {
double min = scalingParameters[variable].Item1;
double max = scalingParameters[variable].Item2;
if (min.IsAlmost(max)) return rows.Select(i => 0.0); // return enumerable of zeros
return ds.GetDoubleValues(variable, rows).Select(x => (x - min) / (max - min)); // scale to range [0..1]
}
public void GetScalingParameters(string variable, out double min, out double max) {
min = scalingParameters[variable].Item1;
max = scalingParameters[variable].Item2;
}
}
}