itkGaussianMixtureModelComponent.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
 *
 *         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 itkGaussianMixtureModelComponent_h
#define itkGaussianMixtureModelComponent_h
 
#include "itkMixtureModelComponentBase.h"
#include "itkGaussianMembershipFunction.h"
#include "itkWeightedMeanSampleFilter.h"
#include "itkWeightedCovarianceSampleFilter.h"
 
namespace itk
{
namespace Statistics
{
template <typename TSample>
class ITK_TEMPLATE_EXPORT GaussianMixtureModelComponent : public MixtureModelComponentBase<TSample>
{
public:
  using Self = GaussianMixtureModelComponent;
  using Superclass = MixtureModelComponentBase<TSample>;
  using Pointer = SmartPointer<Self>;
  using ConstPointer = SmartPointer<const Self>;
 
  itkTypeMacro(GaussianMixtureModelComponent, MixtureModelComponentBase);
  itkNewMacro(Self);
 
  using MeasurementVectorType = typename Superclass::MeasurementVectorType;
  using MeasurementVectorSizeType = typename Superclass::MeasurementVectorSizeType;
  using MembershipFunctionType = typename Superclass::MembershipFunctionType;
  using WeightArrayType = typename Superclass::WeightArrayType;
  using ParametersType = typename Superclass::ParametersType;
 
  using NativeMembershipFunctionType = GaussianMembershipFunction<MeasurementVectorType>;
 
  using MeanEstimatorType = WeightedMeanSampleFilter<TSample>;
  using CovarianceEstimatorType = WeightedCovarianceSampleFilter<TSample>;
 
  using MeanVectorType = typename MeanEstimatorType::OutputType;
 
  using CovarianceMatrixType = typename CovarianceEstimatorType::OutputType;
 
  void
  SetSample(const TSample * sample) override;
 
  void
  SetParameters(const ParametersType & parameters) override;
 
protected:
  GaussianMixtureModelComponent();
  ~GaussianMixtureModelComponent() override = default;
  void
  PrintSelf(std::ostream & os, Indent indent) const override;
 
  double
  CalculateParametersChange();
 
  void
  GenerateData() override;
 
private:
  typename NativeMembershipFunctionType::Pointer m_GaussianMembershipFunction;
 
  typename MeanEstimatorType::MeasurementVectorType m_Mean;
 
  typename CovarianceEstimatorType::MatrixType m_Covariance;
 
  typename MeanEstimatorType::Pointer m_MeanEstimator;
 
  typename CovarianceEstimatorType::Pointer m_CovarianceEstimator;
}; // end of class
} // end of namespace Statistics
} // end of namespace itk
 
#ifndef ITK_MANUAL_INSTANTIATION
#  include "itkGaussianMixtureModelComponent.hxx"
#endif
 
#endif