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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 itkCurvatureFlowImageFilter_hxx
#define itkCurvatureFlowImageFilter_hxx
#include "itkMacro.h"
namespace itk
{
template <typename TInputImage, typename TOutputImage>
CurvatureFlowImageFilter<TInputImage, TOutputImage>::CurvatureFlowImageFilter()
{
this->SetNumberOfIterations(0);
m_TimeStep = 0.05f;
typename CurvatureFlowFunctionType::Pointer cffp;
cffp = CurvatureFlowFunctionType::New();
this->SetDifferenceFunction(static_cast<FiniteDifferenceFunctionType *>(cffp.GetPointer()));
}
template <typename TInputImage, typename TOutputImage>
void
CurvatureFlowImageFilter<TInputImage, TOutputImage>::PrintSelf(std::ostream & os, Indent indent) const
{
Superclass::PrintSelf(os, indent);
os << indent << "TimeStep: " << static_cast<typename NumericTraits<TimeStepType>::PrintType>(m_TimeStep) << std::endl;
}
template <typename TInputImage, typename TOutputImage>
void
CurvatureFlowImageFilter<TInputImage, TOutputImage>::InitializeIteration()
{
// update variables in the equation object
auto * f = dynamic_cast<CurvatureFlowFunctionType *>(this->GetDifferenceFunction().GetPointer());
if (!f)
{
itkExceptionMacro("DifferenceFunction not of type CurvatureFlowFunction");
}
f->SetTimeStep(m_TimeStep);
// call superclass's version
this->Superclass::InitializeIteration();
// progress feedback
if (this->GetNumberOfIterations() != 0)
{
this->UpdateProgress((static_cast<float>(this->GetElapsedIterations())) /
(static_cast<float>(this->GetNumberOfIterations())));
}
}
template <typename TInputImage, typename TOutputImage>
void
CurvatureFlowImageFilter<TInputImage, TOutputImage>::GenerateInputRequestedRegion()
{
// call the superclass's implementation
Superclass::GenerateInputRequestedRegion();
// get pointers to the input and output
typename Superclass::InputImagePointer inputPtr = const_cast<InputImageType *>(this->GetInput());
OutputImagePointer outputPtr = this->GetOutput();
if (!inputPtr || !outputPtr)
{
return;
}
// set the input requested region to be the same as
// the output requested region
inputPtr->SetRequestedRegion(outputPtr->GetRequestedRegion());
}
template <typename TInputImage, typename TOutputImage>
void
CurvatureFlowImageFilter<TInputImage, TOutputImage>::EnlargeOutputRequestedRegion(DataObject * ptr)
{
// convert DataObject pointer to OutputImageType pointer
OutputImageType * outputPtr;
outputPtr = dynamic_cast<OutputImageType *>(ptr);
// get input image pointer
typename Superclass::InputImagePointer inputPtr = const_cast<InputImageType *>(this->GetInput());
if (!inputPtr || !outputPtr)
{
return;
}
// Get the size of the neighborhood on which we are going to operate. This
// radius is supplied by the difference function we are using.
typename FiniteDifferenceFunctionType::RadiusType radius = this->GetDifferenceFunction()->GetRadius();
for (unsigned int j = 0; j < ImageDimension; ++j)
{
radius[j] *= this->GetNumberOfIterations();
}
/**
* NewOutputRequestedRegion = OldOutputRequestedRegion +
* radius * m_NumberOfIterations padding on each edge
*/
typename OutputImageType::RegionType outputRequestedRegion = outputPtr->GetRequestedRegion();
outputRequestedRegion.PadByRadius(radius);
outputRequestedRegion.Crop(outputPtr->GetLargestPossibleRegion());
outputPtr->SetRequestedRegion(outputRequestedRegion);
}
} // end namespace itk
#endif
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