1  #region License Information


2  /* HeuristicLab


3  * Copyright (C) 20022012 Heuristic and Evolutionary Algorithms Laboratory (HEAL)


4  *


5  * This file is part of HeuristicLab.


6  *


7  * HeuristicLab is free software: you can redistribute it and/or modify


8  * it under the terms of the GNU General Public License as published by


9  * the Free Software Foundation, either version 3 of the License, or


10  * (at your option) any later version.


11  *


12  * HeuristicLab is distributed in the hope that it will be useful,


13  * but WITHOUT ANY WARRANTY; without even the implied warranty of


14  * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the


15  * GNU General Public License for more details.


16  *


17  * You should have received a copy of the GNU General Public License


18  * along with HeuristicLab. If not, see <http://www.gnu.org/licenses/>.


19  */


20  #endregion


21 


22  using System;


23  using System.Collections.Generic;


24  using HeuristicLab.Common;


25  using HeuristicLab.Core;


26  using HeuristicLab.Persistence.Default.CompositeSerializers.Storable;


27 


28  namespace HeuristicLab.Algorithms.DataAnalysis {


29  [StorableClass]


30  [Item(Name = "CovarianceConst",


31  Description = "Constant covariance function for Gaussian processes.")]


32  public class CovarianceConst : Item, ICovarianceFunction {


33  [Storable]


34  private double sf2;


35  public double Scale { get { return sf2; } }


36 


37  [StorableConstructor]


38  protected CovarianceConst(bool deserializing)


39  : base(deserializing) {


40  }


41 


42  protected CovarianceConst(CovarianceConst original, Cloner cloner)


43  : base(original, cloner) {


44  this.sf2 = original.sf2;


45  }


46 


47  public CovarianceConst()


48  : base() {


49  }


50 


51  public override IDeepCloneable Clone(Cloner cloner) {


52  return new CovarianceConst(this, cloner);


53  }


54 


55  public int GetNumberOfParameters(int numberOfVariables) {


56  return 1;


57  }


58 


59  public void SetParameter(double[] hyp) {


60  if (hyp.Length != 1) throw new ArgumentException("CovarianceConst has only one hyperparameter", "k");


61  this.sf2 = Math.Exp(2 * hyp[0]);


62  }


63 


64 


65  public double GetCovariance(double[,] x, int i, int j) {


66  return sf2;


67  }


68 


69  public IEnumerable<double> GetGradient(double[,] x, int i, int j) {


70  yield return 2 * sf2;


71  }


72 


73  public double GetCrossCovariance(double[,] x, double[,] xt, int i, int j) {


74  return sf2;


75  }


76  }


77  }

