/*=========================================================================
 *
 *  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 itkVectorThresholdSegmentationLevelSetFunction_h
#define itkVectorThresholdSegmentationLevelSetFunction_h

#include "itkSegmentationLevelSetFunction.h"
#include "itkNumericTraits.h"
#include "itkMahalanobisDistanceMembershipFunction.h"
namespace itk
{
/** \class VectorThresholdSegmentationLevelSetFunction
 *
 * \brief This function is used in VectorThresholdSegmentationLevelSetImageFilter to
 * segment structures in images based on the Mahalanobis distance.
 *
 *   \par CREDITS
 *   This class was contributed to ITK by Stefan Lindenau
 *   https://www.itk.org/pipermail/insight-users/2003-December/005969.html
 *
 * \par  SegmentationLevelSetFunction is a subclass of the generic LevelSetFunction.
 * It useful for segmentations based on intensity values in an image.  It works
 * by constructing a speed term (feature image) with positive values inside an
 * intensity window (between a low and high threshold) and negative values
 * outside that intensity window.  The evolving level set front will lock onto
 * regions that are at the edges of the intensity window.
 *
 *
 *  \par
 *  Image \f$ f(x) \f$ is thresholded pixel by pixel using threshold \f$T\f$
 *  according to the following formula.
 *
 *  \par
 *  \f[
 *           f(x) = T - MahalanobisDistance(x)
 *  \f]
 *
 *  \sa SegmentationLevelSetImageFunction
 *  \sa ThresholdSegmentationLevelSetImageFilter
 *  \sa MahalanobisDistanceMembershipFunction
 * \ingroup ITKLevelSets
 */
template <typename TImageType, typename TFeatureImageType>
class ITK_TEMPLATE_EXPORT VectorThresholdSegmentationLevelSetFunction
  : public SegmentationLevelSetFunction<TImageType, TFeatureImageType>
{
public:
  ITK_DISALLOW_COPY_AND_MOVE(VectorThresholdSegmentationLevelSetFunction);

  /** Standard class type aliases. */
  using Self = VectorThresholdSegmentationLevelSetFunction;
  using Superclass = SegmentationLevelSetFunction<TImageType, TFeatureImageType>;
  using Pointer = SmartPointer<Self>;
  using ConstPointer = SmartPointer<const Self>;
  using FeatureImageType = TFeatureImageType;

  /** Method for creation through the object factory. */
  itkNewMacro(Self);

  /** \see LightObject::GetNameOfClass() */
  itkOverrideGetNameOfClassMacro(VectorThresholdSegmentationLevelSetFunction);

  /** Extract some parameters from the superclass. */
  using typename Superclass::ImageType;
  using typename Superclass::ScalarValueType;
  using typename Superclass::FeatureScalarType;
  using typename Superclass::RadiusType;

  /** Extract some parameters from the superclass. */
  static constexpr unsigned int ImageDimension = Superclass::ImageDimension;

  /** Extract the number of components in the vector pixel type . */
  using FeatureImagePixelType = typename FeatureImageType::PixelType;
  static constexpr unsigned int NumberOfComponents = FeatureImagePixelType::Dimension;

  using MahalanobisFunctionType = Statistics::MahalanobisDistanceMembershipFunction<FeatureScalarType>;
  using MahalanobisFunctionPointer = typename MahalanobisFunctionType::Pointer;
  using MeanVectorType = typename MahalanobisFunctionType::MeanVectorType;
  using CovarianceMatrixType = typename MahalanobisFunctionType::CovarianceMatrixType;

  /** Set/Get mean and covariance */
  void
  SetMean(const MeanVectorType & mean)
  {
    m_Mahalanobis->SetMean(mean);
  }
  const MeanVectorType &
  GetMean() const
  {
    return m_Mahalanobis->GetMean();
  }

  void
  SetCovariance(const CovarianceMatrixType & cov)
  {
    m_Mahalanobis->SetCovariance(cov);
  }
  const CovarianceMatrixType &
  GetCovariance() const
  {
    return m_Mahalanobis->GetCovariance();
  }

  /** Set/Get the threshold value for the MahalanobisDistance */
  void
  SetThreshold(ScalarValueType thr)
  {
    m_Threshold = thr;
  }

  ScalarValueType
  GetThreshold()
  {
    return m_Threshold;
  }

  void
  CalculateSpeedImage() override;

  void
  Initialize(const RadiusType & r) override
  {
    Superclass::Initialize(r);

    this->SetAdvectionWeight(ScalarValueType{});
    this->SetPropagationWeight(-1.0 * NumericTraits<ScalarValueType>::OneValue());
    this->SetCurvatureWeight(NumericTraits<ScalarValueType>::OneValue());
  }

protected:
  VectorThresholdSegmentationLevelSetFunction()
  {
    MeanVectorType       mean(NumberOfComponents);
    CovarianceMatrixType covariance(NumberOfComponents, NumberOfComponents);

    mean.Fill(typename FeatureScalarType::ValueType{});
    covariance.Fill(typename FeatureScalarType::ValueType{});

    m_Mahalanobis = MahalanobisFunctionType::New();
    m_Mahalanobis->SetMean(mean);
    m_Mahalanobis->SetCovariance(covariance);

    this->SetAdvectionWeight(0.0);
    this->SetPropagationWeight(1.0);
    this->SetThreshold(1.8);
  }

  ~VectorThresholdSegmentationLevelSetFunction() override = default;

  void
  PrintSelf(std::ostream & os, Indent indent) const override
  {
    Superclass::PrintSelf(os, indent);
    os << indent << "MahalanobisFunction: " << m_Mahalanobis << std::endl;
    os << indent << "ThresholdValue: " << m_Threshold << std::endl;
  }

  MahalanobisFunctionPointer m_Mahalanobis{};
  ScalarValueType            m_Threshold{};
};
} // end namespace itk

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

#endif
