itkGaussianMembershipFunction.h

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 *
 *  Copyright Insight Software Consortium
 *
 *  Licensed under the Apache License, Version 2.0 (the "License");
 *  you may not use this file except in compliance with the License.
 *  You may obtain a copy of the License at
 *
 *         http://www.apache.org/licenses/LICENSE-2.0.txt
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 *  distributed under the License is distributed on an "AS IS" BASIS,
 *  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 *  See the License for the specific language governing permissions and
 *  limitations under the License.
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 *=========================================================================*/
#ifndef __itkGaussianMembershipFunction_h
#define __itkGaussianMembershipFunction_h

#include "itkMatrix.h"
#include "itkMembershipFunctionBase.h"

namespace itk
{
namespace Statistics
{
template< class TMeasurementVector >
class ITK_EXPORT GaussianMembershipFunction:
  public MembershipFunctionBase< TMeasurementVector >
{
public:
  typedef GaussianMembershipFunction                   Self;
  typedef MembershipFunctionBase< TMeasurementVector > Superclass;
  typedef SmartPointer< Self >                         Pointer;
  typedef SmartPointer< const Self >                   ConstPointer;

  itkTypeMacro(GaussianMembershipFunction, MembershipFunction);
  itkNewMacro(Self);

  typedef typename Superclass::Pointer MembershipFunctionPointer;

  typedef TMeasurementVector MeasurementVectorType;

  typedef typename Superclass::MeasurementVectorSizeType MeasurementVectorSizeType;

  typedef typename itk::NumericTraits< MeasurementVectorType >::RealType MeasurementVectorRealType;
  typedef MeasurementVectorRealType MeanVectorType;

  typedef VariableSizeMatrix< double > CovarianceMatrixType;

  void SetMean(const MeanVectorType & mean);

  itkGetConstReferenceMacro(Mean, MeanVectorType);

  void SetCovariance(const CovarianceMatrixType & cov);

  /* Get the covariance matrix. Covariance matrix is a
  VariableSizeMatrix of doubles. */
  itkGetConstReferenceMacro(Covariance, CovarianceMatrixType);

  /* Get the inverse covariance matrix. Covariance matrix is a
  VariableSizeMatrix of doubles. */
  itkGetConstReferenceMacro(InverseCovariance, CovarianceMatrixType);

  double Evaluate(const MeasurementVectorType & measurement) const;

  MembershipFunctionPointer Clone() const;

protected:
  GaussianMembershipFunction(void);
  virtual ~GaussianMembershipFunction(void) {}
  void PrintSelf(std::ostream & os, Indent indent) const;

private:
  GaussianMembershipFunction(const Self &);   //purposely not implemented
  void operator=(const Self &); //purposely not implemented

  MeanVectorType       m_Mean;            // mean
  CovarianceMatrixType m_Covariance;      // covariance matrix

  // inverse covariance matrix. automatically calculated
  // when covariace matirx is set.
  CovarianceMatrixType m_InverseCovariance;

  // pre_factor (normalization term). automatically calculated
  // when covariace matirx is set.
  double m_PreFactor;

  bool m_CovarianceNonsingular;
};
} // end of namespace Statistics
} // end namespace itk

#ifndef ITK_MANUAL_INSTANTIATION
#include "itkGaussianMembershipFunction.hxx"
#endif

#endif