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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 "itkCovarianceImageFunction.h"
#include "itkImageFunction.h"
#include "itkTestingMacros.h"
int
itkCovarianceImageFunctionTest(int, char *[])
{
constexpr unsigned int Dimension = 3;
using PixelComponentType = unsigned char;
constexpr unsigned int VectorDimension = 4;
using PixelType = itk::FixedArray<PixelComponentType, VectorDimension>;
using ImageType = itk::Image<PixelType, Dimension>;
using FunctionType = itk::CovarianceImageFunction<ImageType>;
// Create and allocate the image
auto image = ImageType::New();
ImageType::SizeType size;
ImageType::IndexType start;
ImageType::RegionType region;
size[0] = 20;
size[1] = 20;
size[2] = 20;
ImageType::IndexValueType imageValue = 0;
start.Fill(imageValue);
region.SetIndex(start);
region.SetSize(size);
image->SetRegions(region);
image->Allocate();
ImageType::PixelType initialValue;
initialValue[0] = 11;
initialValue[1] = 13;
initialValue[2] = 17;
initialValue[3] = 19;
image->FillBuffer(initialValue);
auto function = FunctionType::New();
ITK_EXERCISE_BASIC_OBJECT_METHODS(function, CovarianceImageFunction, ImageFunction);
function->SetInputImage(image);
unsigned int neighborhoodRadius = 5;
function->SetNeighborhoodRadius(neighborhoodRadius);
ITK_TEST_SET_GET_VALUE(neighborhoodRadius, function->GetNeighborhoodRadius());
ImageType::IndexType index;
index[0] = 10;
index[1] = 10;
index[2] = 10;
FunctionType::OutputType covariance;
covariance = function->EvaluateAtIndex(index);
std::cout << "function->EvaluateAtIndex( index ): " << covariance << std::endl;
// Test Evaluate
FunctionType::PointType point;
point[0] = 25;
point[1] = 25;
point[2] = 25;
FunctionType::OutputType covariance2;
covariance2 = function->Evaluate(point);
std::cout << "function->Evaluate(point): " << covariance2 << std::endl;
// Test EvaluateAtContinuousIndex
FunctionType::ContinuousIndexType cindex;
cindex[0] = 25;
cindex[1] = 25;
cindex[2] = 25;
FunctionType::OutputType covariance3;
covariance3 = function->EvaluateAtContinuousIndex(cindex);
std::cout << "function->EvaluateAtContinuousIndex(cindex): " << covariance3 << std::endl;
// Since the input image is constant, the covariance should be equal to
// the initial value
for (unsigned int ix = 0; ix < VectorDimension; ++ix)
{
for (unsigned int iy = 0; iy < VectorDimension; ++iy)
{
// Covariance must be zero in this image with constant values
if (!itk::Math::FloatAlmostEqual(itk::Math::abs(covariance[ix][iy]),
static_cast<FunctionType::OutputType::element_type>(imageValue),
10,
10e-7))
{
std::cerr << "Error in covariance computation" << std::endl;
return EXIT_FAILURE;
}
}
}
std::cout << "Test PASSED ! " << std::endl;
return EXIT_SUCCESS;
}
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