#region License Information
/* HeuristicLab
* Copyright (C) 2002-2014 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.Linq;
using HeuristicLab.Common;
using HeuristicLab.Core;
using HeuristicLab.Optimization;
using HeuristicLab.Parameters;
using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;
using HeuristicLab.Problems.DataAnalysis;
namespace HeuristicLab.Algorithms.DataAnalysis {
[Item("Random", "Initializes the matrix randomly.")]
[StorableClass]
public sealed class RandomInitializer : NcaInitializer, IStochasticOperator {
public ILookupParameter RandomParameter {
get { return (ILookupParameter)Parameters["Random"]; }
}
[StorableConstructor]
private RandomInitializer(bool deserializing) : base(deserializing) { }
private RandomInitializer(RandomInitializer original, Cloner cloner) : base(original, cloner) { }
public RandomInitializer()
: base() {
Parameters.Add(new LookupParameter("Random", "The random number generator to use."));
}
public override IDeepCloneable Clone(Cloner cloner) {
return new RandomInitializer(this, cloner);
}
public override double[,] Initialize(IClassificationProblemData data, int dimensions) {
var attributes = data.AllowedInputVariables.Count();
var random = RandomParameter.ActualValue;
var matrix = new double[attributes, dimensions];
for (int i = 0; i < attributes; i++)
for (int j = 0; j < dimensions; j++)
matrix[i, j] = random.NextDouble();
return matrix;
}
}
}