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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.
*
*=========================================================================*/
#include <iostream>
#include "itkDisplacementFieldJacobianDeterminantFilter.h"
#include "itkNullImageToImageFilterDriver.hxx"
#include "itkStdStreamStateSave.h"
#include "itkTestingMacros.h"
static bool
TestDisplacementJacobianDeterminantValue()
{
bool testPassed = true;
constexpr unsigned int ImageDimension = 2;
using VectorType = itk::Vector<float, ImageDimension>;
using FieldType = itk::Image<VectorType, ImageDimension>;
// In this case, the image to be warped is also a vector field.
using VectorImageType = FieldType;
std::cout << "Create the dispacementfield image pattern." << std::endl;
VectorImageType::RegionType region;
// NOTE: Making the image size much larger than necessary in order to get
// some meaningful time measurements. Simulate a 256x256x256 image.
VectorImageType::SizeType size = { { 4096, 4096 } };
region.SetSize(size);
auto dispacementfield = VectorImageType::New();
dispacementfield->SetLargestPossibleRegion(region);
dispacementfield->SetBufferedRegion(region);
dispacementfield->Allocate();
VectorType values;
values[0] = 0;
values[1] = 0;
using Iterator = itk::ImageRegionIteratorWithIndex<VectorImageType>;
for (Iterator inIter(dispacementfield, region); !inIter.IsAtEnd(); ++inIter)
{
const unsigned int i = inIter.GetIndex()[0];
const unsigned int j = inIter.GetIndex()[1];
values[0] = 0.125 * i * i + 0.125 * j;
values[1] = 0.125 * i * j + 0.25 * j;
inIter.Set(values);
// std::cout << "Setting: " << values << " at " << inIter.GetIndex() << std::endl;
}
// Displacement field:
//|-------------------------------------------|
//| [0.25;0.5] | [0.375;0.75] | [0.75;1] |
//|-------------------------------------------|
//| [0.125;0.25] | [0.25;0.375] | [0.625;0.5] |
//|-------------------------------------------|
//| [0.0;0.0] | [0.125;0.0] | [0.5;0] |
//|-------------------------------------------|
//
// J(1,1) = [ (.625-.125)/2 (.5-.25)/2; (.375-.125)/2 (.75-0.0)/2] =[ .25 .125; .125 .375]
// det((J+I)(1,1))=((.25+1.0)*(.375+1.0))-(.125*.125) = 1.703125;
const float expectedJacobianDeterminant = (((.25 + 1.0) * (.375 + 1.0)) - (.125 * .125));
using FilterType = itk::DisplacementFieldJacobianDeterminantFilter<VectorImageType, float>;
auto filter = FilterType::New();
ITK_EXERCISE_BASIC_OBJECT_METHODS(filter, DisplacementFieldJacobianDeterminantFilter, ImageToImageFilter);
bool useImageSpacing = true;
#if !defined(ITK_FUTURE_LEGACY_REMOVE)
if (useImageSpacing)
{
filter->SetUseImageSpacingOn();
}
else
{
filter->SetUseImageSpacingOff();
}
#endif
ITK_TEST_SET_GET_BOOLEAN(filter, UseImageSpacing, useImageSpacing);
filter->SetInput(dispacementfield);
filter->Update();
itk::Image<float, 2>::Pointer output = filter->GetOutput();
VectorImageType::IndexType index;
index[0] = 1;
index[1] = 1;
float jacobianDeterminant = output->GetPixel(index);
// std::cout << "Output " << output->GetPixel(index) << std::endl;
double epsilon = 1e-13;
if (itk::Math::abs(jacobianDeterminant - expectedJacobianDeterminant) > epsilon)
{
std::cerr.precision(static_cast<int>(itk::Math::abs(std::log10(epsilon))));
std::cerr << "Test failed!" << std::endl;
std::cerr << "Error in pixel value at index [" << index << "]" << std::endl;
std::cerr << "Expected value " << jacobianDeterminant << std::endl;
std::cerr << " differs from " << expectedJacobianDeterminant;
std::cerr << " by more than " << epsilon << std::endl;
testPassed = false;
}
else
{
std::cout << "Test passed." << std::endl;
}
return testPassed;
}
int
itkDisplacementFieldJacobianDeterminantFilterTest(int, char *[])
{
// Save the format stream variables for std::cout
// They will be restored when coutState goes out of scope
// scope.
itk::StdStreamStateSave coutState(std::cout);
bool ValueTestPassed = TestDisplacementJacobianDeterminantValue();
try
{
using VectorType = itk::Vector<float, 3>;
using VectorImageType = itk::Image<VectorType, 3>;
using ScalarVectorImageType = itk::Image<float, 3>;
// Set up filter
using FilterType = itk::DisplacementFieldJacobianDeterminantFilter<VectorImageType, float>;
auto filter = FilterType::New();
ITK_EXERCISE_BASIC_OBJECT_METHODS(filter, DisplacementFieldJacobianDeterminantFilter, ImageToImageFilter);
// Run the test
itk::Size<3> sz;
sz[0] = 100;
sz[1] = 100;
sz[2] = 100;
itk::NullImageToImageFilterDriver<VectorImageType, ScalarVectorImageType> test1;
test1.SetImageSize(sz);
test1.SetFilter(filter);
test1.Execute();
filter->Print(std::cout);
// Run the test again with ImageSpacingOn
bool useImageSpacing = true;
ITK_TEST_SET_GET_BOOLEAN(filter, UseImageSpacing, useImageSpacing);
test1.Execute();
filter->Print(std::cout);
// Run the test again with specified weights
typename FilterType::WeightsType weights{ { { 1.0, 2.0, 3.0 } } };
filter->SetDerivativeWeights(weights);
ITK_TEST_SET_GET_VALUE(weights, filter->GetDerivativeWeights());
test1.Execute();
filter->Print(std::cout);
}
catch (const itk::ExceptionObject & err)
{
std::cerr << err << std::endl;
return EXIT_FAILURE;
}
if (ValueTestPassed == false)
{
return EXIT_FAILURE;
}
std::cout << "Test finished." << std::endl;
return EXIT_SUCCESS;
}
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