itkGaussianMembershipFunction.h

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/*=========================================================================
 *
 *  Copyright NumFOCUS
 *
 *  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
 *
 *         https://www.apache.org/licenses/LICENSE-2.0.txt
 *
 *  Unless required by applicable law or agreed to in writing, software
 *  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.
 *
 *=========================================================================*/
#ifndef itkGaussianMembershipFunction_h
#define itkGaussianMembershipFunction_h
 
#include "itkMatrix.h"
#include "itkMembershipFunctionBase.h"
 
namespace itk
{
namespace Statistics
{
template <typename TMeasurementVector>
class ITK_TEMPLATE_EXPORT GaussianMembershipFunction : public MembershipFunctionBase<TMeasurementVector>
{
public:
  ITK_DISALLOW_COPY_AND_MOVE(GaussianMembershipFunction);
 
  using Self = GaussianMembershipFunction;
  using Superclass = MembershipFunctionBase<TMeasurementVector>;
  using Pointer = SmartPointer<Self>;
  using ConstPointer = SmartPointer<const Self>;
 
  itkOverrideGetNameOfClassMacro(GaussianMembershipFunction);
  itkNewMacro(Self);
  using MembershipFunctionPointer = typename Superclass::Pointer;
 
  using MeasurementVectorType = TMeasurementVector;
 
  using typename Superclass::MeasurementVectorSizeType;
 
  using MeasurementVectorRealType = typename itk::NumericTraits<MeasurementVectorType>::RealType;
  using MeanVectorType = MeasurementVectorRealType;
 
  using CovarianceMatrixType = VariableSizeMatrix<double>;
 
  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 override;
 
  typename LightObject::Pointer
  InternalClone() const override;
 
protected:
  GaussianMembershipFunction();
  ~GaussianMembershipFunction() override = default;
  void
  PrintSelf(std::ostream & os, Indent indent) const override;
 
private:
  MeanVectorType       m_Mean{};       // mean
  CovarianceMatrixType m_Covariance{}; // covariance matrix
 
  // inverse covariance matrix. automatically calculated
  // when covariance matrix is set.
  CovarianceMatrixType m_InverseCovariance{};
 
  // pre_factor (normalization term). automatically calculated
  // when covariance matrix is set.
  double m_PreFactor{};
 
  bool m_CovarianceNonsingular{};
};
} // end of namespace Statistics
} // end namespace itk
 
#ifndef ITK_MANUAL_INSTANTIATION
#  include "itkGaussianMembershipFunction.hxx"
#endif
 
#endif