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ENH: Add ComputeSpatialJacobianDeterminantImageOfAffineTransform GTest #768

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ENH: Add ComputeSpatialJacobianDeterminantImageOfAffineTransform GTest #768

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63 changes: 62 additions & 1 deletion Core/Main/GTesting/itkTransformixFilterGTest.cxx
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Original file line number Diff line number Diff line change
Expand Up @@ -1241,7 +1241,7 @@ GTEST_TEST(itkTransformixFilter, SetCompositeTransformOfTranslationAndScale)


// Tests ComputeSpatialJacobianDeterminantImage and ComputeSpatialJacobianMatrixImage on a simple translation.
GTEST_TEST(itkTransformixFilter, ComputeSpatialJacobianDeterminantImage)
GTEST_TEST(itkTransformixFilter, ComputeSpatialJacobianDeterminantImageOfTranslationTransform)
{
using PixelType = float;
constexpr unsigned int ImageDimension{ 2 };
Expand Down Expand Up @@ -1291,3 +1291,64 @@ GTEST_TEST(itkTransformixFilter, ComputeSpatialJacobianDeterminantImage)
EXPECT_EQ(matrix, expectedMatrix);
}
}


// Tests ComputeSpatialJacobianDeterminantImage and ComputeSpatialJacobianMatrixImage on a simple affine transformation.
GTEST_TEST(itkTransformixFilter, ComputeSpatialJacobianDeterminantImageOfAffineTransform)
{
using PixelType = float;
constexpr unsigned int ImageDimension{ 2 };

using SizeType = itk::Size<ImageDimension>;
const SizeType imageSize{ { 5, 6 } };

using ImageType = itk::Image<PixelType, ImageDimension>;
using TransformixFilterType = itk::TransformixFilter<ImageType>;

elx::DefaultConstruct<ImageType> movingImage{};
movingImage.SetRegions(imageSize);
movingImage.Allocate(true);

elx::DefaultConstruct<itk::AffineTransform<double, ImageDimension>> transform{};
transform.SetOffset(itk::MakeVector(1.0, -2.0));
transform.Scale(2.0);

elx::DefaultConstruct<TransformixFilterType> transformixFilter{};
transformixFilter.SetMovingImage(&movingImage);
transformixFilter.SetTransform(&transform);
transformixFilter.SetTransformParameterObject(
CreateParameterObject({ // Parameters in alphabetic order:
{ "Direction", CreateDefaultDirectionParameterValues<ImageDimension>() },
{ "Index", ParameterValuesType(ImageDimension, "0") },
{ "Origin", ParameterValuesType(ImageDimension, "0") },
{ "ResampleInterpolator", { "FinalLinearInterpolator" } },
{ "Size", ConvertToParameterValues(imageSize) },
{ "Spacing", ParameterValuesType(ImageDimension, "1") } }));
transformixFilter.Update();

const auto determinantImage = transformixFilter.ComputeSpatialJacobianDeterminantImage();
const auto matrixImage = transformixFilter.ComputeSpatialJacobianMatrixImage();

const itk::ImageRegion<ImageDimension> expectedBufferedRegion({}, imageSize);
EXPECT_EQ(DerefSmartPointer(determinantImage).GetBufferedRegion(), expectedBufferedRegion);
EXPECT_EQ(DerefSmartPointer(matrixImage).GetBufferedRegion(), expectedBufferedRegion);

const auto & expectedMatrix = transform.GetMatrix().GetVnlMatrix();
const auto expectedDeterminant = vnl_det(expectedMatrix);

for (const auto determinant : itk::MakeImageBufferRange(determinantImage.GetPointer()))
{
EXPECT_EQ(determinant, expectedDeterminant);
}

constexpr auto expectedNumberOfElements = ImageDimension * ImageDimension;
const auto * const expectedData = expectedMatrix.data_block();
static_assert(decltype(expectedMatrix){}.size() == expectedNumberOfElements, "Check expected size");

for (const auto & actualMatrix : itk::MakeImageBufferRange(matrixImage.GetPointer()))
{
static_assert(decltype(actualMatrix.GetVnlMatrix()){}.size() == expectedNumberOfElements, "Check actual size");
EXPECT_TRUE(
std::equal(expectedData, expectedData + expectedNumberOfElements, actualMatrix.GetVnlMatrix().data_block()));
}
}