STYLE: Declare ImageGaussianModelEstimator::m_Covariance as unique_ptr

Also defaulted the destructor of `ImageGaussianModelEstimator`.

Author: N-Dekker

Modules/Segmentation/Classifiers/include/itkImageGaussianModelEstimator.h

@@ -20,6 +20,7 @@
 
 #include <cmath>
 #include <cfloat>
+#include <memory> // For unique_ptr.
 
 #include "vnl/vnl_vector.h"
 #include "vnl/vnl_matrix.h"
@@ -124,7 +125,7 @@ class ITK_TEMPLATE_EXPORT ImageGaussianModelEstimator : public ImageModelEstimat
 
 protected:
   ImageGaussianModelEstimator() = default;
-  ~ImageGaussianModelEstimator() override;
+  ~ImageGaussianModelEstimator() override = default;
   void
   PrintSelf(std::ostream & os, Indent indent) const override;
 
@@ -151,9 +152,9 @@ class ITK_TEMPLATE_EXPORT ImageGaussianModelEstimator : public ImageModelEstimat
   void
   EstimateGaussianModelParameters();
 
-  MatrixType   m_NumberOfSamples;
-  MatrixType   m_Means;
-  MatrixType * m_Covariance{ nullptr };
+  MatrixType                    m_NumberOfSamples;
+  MatrixType                    m_Means;
+  std::unique_ptr<MatrixType[]> m_Covariance{ nullptr };
 
   TrainingImagePointer m_TrainingImage;
 };

Modules/Segmentation/Classifiers/include/itkImageGaussianModelEstimator.hxx

@@ -20,17 +20,11 @@
 
 #include "itkMath.h"
 #include "itkNumericTraits.h"
+#include "itkMakeUniqueForOverwrite.h"
 
 namespace itk
 {
 
-template <typename TInputImage, typename TMembershipFunction, typename TTrainingImage>
-ImageGaussianModelEstimator<TInputImage, TMembershipFunction, TTrainingImage>::~ImageGaussianModelEstimator()
-{
-  delete[] m_Covariance;
-}
-
-
 template <typename TInputImage, typename TMembershipFunction, typename TTrainingImage>
 void
 ImageGaussianModelEstimator<TInputImage, TMembershipFunction, TTrainingImage>::PrintSelf(std::ostream & os,
@@ -40,7 +34,7 @@ ImageGaussianModelEstimator<TInputImage, TMembershipFunction, TTrainingImage>::P
 
   os << indent << "NumberOfSamples: " << m_NumberOfSamples << std::endl;
   os << indent << "Means: " << m_Means << std::endl;
-  os << indent << "Covariance: " << m_Covariance << std::endl;
+  os << indent << "Covariance: " << m_Covariance.get() << std::endl;
 
   itkPrintSelfObjectMacro(TrainingImage);
 }
@@ -139,10 +133,8 @@ ImageGaussianModelEstimator<TInputImage, TMembershipFunction, TTrainingImage>::E
   m_NumberOfSamples.set_size(numberOfModels, 1);
   m_NumberOfSamples.fill(0);
 
-  // Delete previous allocation first
-  delete[] m_Covariance;
   // Number of covariance matrices are equal to the number of classes
-  m_Covariance = (MatrixType *)new MatrixType[numberOfModels];
+  m_Covariance = make_unique_for_overwrite<MatrixType[]>(numberOfModels);
 
   for (unsigned int i = 0; i < numberOfModels; ++i)
   {