text: // $Id$
  // Copyright (C) 2002 Klaas Gadeyne <first dot last at gmail dot com>
  // Copyright (C) 2008 Tinne De Laet <first dot last at mech dot kuleuven dot be>
  //
  // This program is free software; you can redistribute it and/or modify
  // it under the terms of the GNU Lesser General Public License as published by
  // the Free Software Foundation; either version 2.1 of the License, or
  // (at your option) any later version.
  //
  // This program 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 Lesser General Public License for more details.
  //
  // You should have received a copy of the GNU Lesser General Public License
  // along with this program; if not, write to the Free Software
  // Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA  02110-1301  USA.
  //
  
  #ifndef __CONDITIONAL_GAUSSIAN__
  #define __CONDITIONAL_GAUSSIAN__
  
  #include "conditionalpdf.h"
  
  namespace BFL
  {
    /// Abstract Class representing all Conditional gaussians
    /** This class inherits only from ConditionalPdf<ColumnVector,
        ColumnVector>.
  
        So this class represents all Pdf's of the type
        \f[ P ( A | B, C, D, ... ) \f] where
        \f[ \mu_A = f(B,C,D, ...) \f] and
        \f[ \Sigma_A = g(B,C,D, ...) \f] and
  
        \f[ A = N(\mu_A, \Sigma_A) \f]
  
        f and g are not necessarily analytical functions
    */
    class ConditionalGaussian : public ConditionalPdf<MatrixWrapper::ColumnVector, MatrixWrapper::ColumnVector>
      {
      public:
        /// Constructor
        /**
  	 @param dim Dimension of state
  	 @param num_conditional_arguments The number of conditional
  	 arguments.
        */
        ConditionalGaussian(int dim = 0, int num_conditional_arguments=0);
  
        // Default Copy constructor will do
  
        /// Destructor
        virtual ~ConditionalGaussian();
  
        ///Clone function
        virtual ConditionalGaussian* Clone() const;
  
        // implemented virtuals!
        virtual Probability ProbabilityGet(const MatrixWrapper::ColumnVector& input) const;
        virtual bool SampleFrom (Sample<MatrixWrapper::ColumnVector>& sample, const SampleMthd method=SampleMthd::DEFAULT, void * args=NULL) const;
        virtual bool SampleFrom (std::vector<Sample<MatrixWrapper::ColumnVector> >& samples, const unsigned int num_samples,
  			       const SampleMthd method=SampleMthd::DEFAULT, void * args=NULL) const;
  
      protected:
        // variables to avoid allocation on the heap during sampling
        mutable ColumnVector _diff;
        mutable ColumnVector _Mu;
        mutable Matrix _Low_triangle;
        mutable ColumnVector _samples;
        mutable ColumnVector _SampleValue;
  
      };
  
  } // End namespace BFL
  
  #endif // __CONDITIONAL_GAUSSIAN__
  
  