itkMahalanobisDistanceMetric.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
 *
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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 itkMahalanobisDistanceMetric_h
#define itkMahalanobisDistanceMetric_h
 
#include "vnl/vnl_vector.h"
#include "vnl/vnl_vector_ref.h"
#include "vnl/vnl_transpose.h"
#include "vnl/vnl_matrix.h"
#include "vnl/algo/vnl_matrix_inverse.h"
#include "vnl/algo/vnl_determinant.h"
#include "itkArray.h"
 
#include "itkDistanceMetric.h"
 
namespace itk
{
namespace Statistics
{
template <typename TVector>
class ITK_TEMPLATE_EXPORT MahalanobisDistanceMetric : public DistanceMetric<TVector>
{
public:
  using Self = MahalanobisDistanceMetric;
  using Superclass = DistanceMetric<TVector>;
  using Pointer = SmartPointer<Self>;
  using ConstPointer = SmartPointer<const Self>;
 
  itkOverrideGetNameOfClassMacro(MahalanobisDistanceMetric);
  itkNewMacro(Self);
  using typename Superclass::MeasurementVectorType;
 
  using typename Superclass::MeasurementVectorSizeType;
 
  using MeanVectorType = typename Superclass::OriginType;
 
  using CovarianceMatrixType = vnl_matrix<double>;
 
  void SetMeasurementVectorSize(MeasurementVectorSizeType) override;
 
  void
  SetMean(const MeanVectorType & mean);
 
  const MeanVectorType &
  GetMean() const;
 
  void
  SetCovariance(const CovarianceMatrixType & cov);
 
  itkGetConstReferenceMacro(Covariance, CovarianceMatrixType);
 
  void
  SetInverseCovariance(const CovarianceMatrixType & invcov);
 
  itkGetConstReferenceMacro(InverseCovariance, CovarianceMatrixType);
 
  double
  Evaluate(const MeasurementVectorType & measurement) const override;
 
  double
  Evaluate(const MeasurementVectorType & x1, const MeasurementVectorType & x2) const override;
 
  itkSetMacro(Epsilon, double);
  itkGetConstMacro(Epsilon, double);
  itkSetMacro(DoubleMax, double);
  itkGetConstMacro(DoubleMax, double);
 
protected:
  MahalanobisDistanceMetric();
  ~MahalanobisDistanceMetric() override = default;
  void
  PrintSelf(std::ostream & os, Indent indent) const override;
 
private:
  MeanVectorType       m_Mean{};       // mean
  CovarianceMatrixType m_Covariance{}; // covariance matrix
 
  // inverse covariance matrix which is automatically calculated
  // when covariance matrix is set.  This speeds up the GetProbability()
  CovarianceMatrixType m_InverseCovariance{};
 
  double m_Epsilon{ 1e-100 };
  double m_DoubleMax{ 1e+20 };
 
  void
  CalculateInverseCovariance();
};
} // end of namespace Statistics
} // end namespace itk
 
#ifndef ITK_MANUAL_INSTANTIATION
#  include "itkMahalanobisDistanceMetric.hxx"
#endif
 
#endif