itkGaussianMembershipFunction.h

Go to the documentation of this file.

/*=========================================================================
 *
 *  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
 *
 *  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_ASSIGN(GaussianMembershipFunction);

  using Self = GaussianMembershipFunction;
  using Superclass = MembershipFunctionBase< TMeasurementVector >;
  using Pointer = SmartPointer< Self >;
  using ConstPointer = SmartPointer< const Self >;

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

  using MembershipFunctionPointer = typename Superclass::Pointer;

  using MeasurementVectorType = TMeasurementVector;

  using MeasurementVectorSizeType = 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 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