1  #region License Information


2  /* HeuristicLab


3  * Copyright (C) 20022015 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 HeuristicLab.Common;


24  using HeuristicLab.Core;


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


26 


27  namespace HeuristicLab.Algorithms.DataAnalysis {


28  [StorableClass]


29  [Item(Name = "CovarianceLinear", Description = "Linear covariance function for Gaussian processes.")]


30  public sealed class CovarianceLinear : Item, ICovarianceFunction {


31  [StorableConstructor]


32  private CovarianceLinear(bool deserializing) : base(deserializing) { }


33  private CovarianceLinear(CovarianceLinear original, Cloner cloner)


34  : base(original, cloner) {


35  }


36  public CovarianceLinear()


37  : base() {


38  }


39 


40  public override IDeepCloneable Clone(Cloner cloner) {


41  return new CovarianceLinear(this, cloner);


42  }


43 


44  public int GetNumberOfParameters(int numberOfVariables) {


45  return 0;


46  }


47 


48  public void SetParameter(double[] p) {


49  if (p.Length > 0) throw new ArgumentException("No parameters are allowed for the linear covariance function.");


50  }


51 


52  public ParameterizedCovarianceFunction GetParameterizedCovarianceFunction(double[] p, int[] columnIndices) {


53  if (p.Length > 0) throw new ArgumentException("No parameters are allowed for the linear covariance function.");


54  // create functions


55  var cov = new ParameterizedCovarianceFunction();


56  cov.Covariance = (x, i, j) => Util.ScalarProd(x, i, j, columnIndices, 1.0);


57  cov.CrossCovariance = (x, xt, i, j) => Util.ScalarProd(x, i, xt, j, columnIndices, 1.0);


58  cov.CovarianceGradient = (x, i, j) => new double[0];


59  return cov;


60  }


61  }


62  }

