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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 itkManifoldParzenWindowsPointSetFunction_h
#define itkManifoldParzenWindowsPointSetFunction_h
#include "itkPointSetFunction.h"
#include "itkGaussianMembershipFunction.h"
#include "itkMatrix.h"
#include "itkPointSet.h"
#include "itkPointsLocator.h"
#include "itkVector.h"
#include "itkMultiThreaderBase.h"
#include <vector>
namespace itk
{
/** \class ManifoldParzenWindowsPointSetFunction
* \brief Point set function based on n-dimensional parzen windowing.
*
* This class allows evaluating a function derived from a point set
* by creating a continuous distribution using manifold parzen windowing.
* Each point is associated with a Gaussian and local shape can
* be encoded in the covariance matrix.
*
* \ingroup ITKMetricsv4
*/
template <typename TPointSet, typename TOutput = double, typename TCoordRep = double>
class ITK_TEMPLATE_EXPORT ManifoldParzenWindowsPointSetFunction : public PointSetFunction<TPointSet, TOutput, TCoordRep>
{
public:
ITK_DISALLOW_COPY_AND_MOVE(ManifoldParzenWindowsPointSetFunction);
using Self = ManifoldParzenWindowsPointSetFunction;
using Superclass = PointSetFunction<TPointSet, TOutput, TCoordRep>;
using Pointer = SmartPointer<Self>;
using ConstPointer = SmartPointer<const Self>;
/** Method for creation through the object factory. */
itkNewMacro(Self);
/** Extract dimension from output image. */
static constexpr unsigned int PointDimension = TPointSet::PointDimension;
using typename Superclass::InputPointSetType;
using typename Superclass::InputPointType;
/** Point set type alias support */
using PointSetType = TPointSet;
using PointType = typename PointSetType::PointType;
using PointsContainer = typename PointSetType::PointsContainer;
using PointIdentifier = typename PointsContainer::ElementIdentifier;
/** Other type alias */
using RealType = TOutput;
using OutputType = TOutput;
using CoordinateType = TCoordRep;
using CoordRepType = CoordinateType;
/** Typedef for points locator class to speed up finding neighboring points */
using PointsLocatorType = PointsLocator<PointsContainer>;
using NeighborsIdentifierType = typename PointsLocatorType::NeighborsIdentifierType;
using GaussianType = typename Statistics::GaussianMembershipFunction<PointType>;
using GaussianPointer = typename GaussianType::Pointer;
using GaussianConstPointer = typename GaussianType::ConstPointer;
using GaussianContainerType = std::vector<GaussianPointer>;
using CovarianceMatrixType = typename GaussianType::CovarianceMatrixType;
/** Helper functions */
/**
* Set the covariance K neighborhood. For a given point the closest K
* points are used to construct the corresponding covariance reflecting
* the local point set structure. Default = 5.
*/
itkSetMacro(CovarianceKNeighborhood, unsigned int);
/** Get the covariance k neighborhood size. Default = 5.*/
itkGetConstMacro(CovarianceKNeighborhood, unsigned int);
/**
* Set the evaluation K neighborhood. To evaluate the manifold parzen
* windows function, one could sum the value contributed by each Gaussian or
* to speed calculation, we could sum the value contributed by the nearest
* K Gaussians. Default = 50.
*/
itkSetMacro(EvaluationKNeighborhood, unsigned int);
/** Get the evaluation K neighborhood. Default = 50.*/
itkGetConstMacro(EvaluationKNeighborhood, unsigned int);
/**
* Set the regularization sigma. To avoid singular covariance matrices,
* a regularization sigma value is added to the diagonal. Default = 1.0.
*/
itkSetMacro(RegularizationSigma, RealType);
/** Get the regularization sigma. Default = 1.0. */
itkGetConstMacro(RegularizationSigma, RealType);
/**
* Set the kernel sigma. In constructing the covariance from k neighbors,
* a Gaussian is used to weight more strongly the closest neighbors. This
* defines that weighting Gaussian. Default = 1.0.
*/
itkSetMacro(KernelSigma, RealType);
/** Get the kernel sigma. Default = 1.0. */
itkGetConstMacro(KernelSigma, RealType);
/**
* Normalize covariance by the sum of the weights of the nearest neighbors.
* Default = true.
*/
itkSetMacro(Normalize, bool);
/**
* Normalize covariance by the sum of the weights of the nearest neighbors.
* Default = true.
*/
itkGetConstMacro(Normalize, bool);
/**
* Normalize covariance by the sum of the weights of the nearest neighbors.
* Default = true.
*/
itkBooleanMacro(Normalize);
/**
* Construct covariances using the local neighborhood point set structure.
* Otherwise, the Gaussian for each point is characterized by the value
* of m_RegularizationSigma. Default = true.
*/
itkSetMacro(UseAnisotropicCovariances, bool);
/**
* Construct covariances using the local neighborhood point set structure.
* Otherwise, the Gaussian for each point is characterized by the value
* of m_RegularizationSigma. Default = true.
*/
itkGetConstMacro(UseAnisotropicCovariances, bool);
/**
* Construct covariances using the local neighborhood point set structure.
* Otherwise, the Gaussian for each point is characterized by the value
* of m_RegularizationSigma. Default = true.
*/
itkBooleanMacro(UseAnisotropicCovariances);
/** Set the input point set */
void
SetInputPointSet(const InputPointSetType *) override;
/** Evaluate function value at specified point */
TOutput
Evaluate(const InputPointType &) const override;
/** Get Gaussian corresponding to a specific point */
GaussianConstPointer GetGaussian(PointIdentifier) const;
/** Get the points locator describing the point set neighborhood */
itkGetModifiableObjectMacro(PointsLocator, PointsLocatorType);
protected:
ManifoldParzenWindowsPointSetFunction();
~ManifoldParzenWindowsPointSetFunction() override = default;
void
PrintSelf(std::ostream & os, Indent indent) const override;
void
GenerateData();
private:
typename PointsLocatorType::Pointer m_PointsLocator{};
unsigned int m_CovarianceKNeighborhood{ 5 };
unsigned int m_EvaluationKNeighborhood{ 50 };
RealType m_RegularizationSigma{};
RealType m_KernelSigma{};
GaussianContainerType m_Gaussians{};
bool m_Normalize{ true };
bool m_UseAnisotropicCovariances{ true };
MultiThreaderBase::Pointer m_MultiThreader{};
};
} // end namespace itk
#ifndef ITK_MANUAL_INSTANTIATION
# include "itkManifoldParzenWindowsPointSetFunction.hxx"
#endif
#endif
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