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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 "itkGaussianSpatialFunction.h"
#include "itkMath.h"
#include "itkTestingMacros.h"
int
itkGaussianSpatialFunctionTest(int argc, char * argv[])
{
if (argc < 3)
{
std::cerr << "Missing parameters." << std::endl;
std::cerr << "Usage: " << itkNameOfTestExecutableMacro(argv) << " scale normalized" << std::endl;
return EXIT_FAILURE;
}
constexpr unsigned int Dimension = 3;
using PixeltType = double;
using GaussianSpatialFunctionType = itk::GaussianSpatialFunction<PixeltType, Dimension>;
using ArrayType = GaussianSpatialFunctionType::ArrayType;
using InputType = GaussianSpatialFunctionType::InputType;
// Create and initialize the Spatial function
auto gaussianSpatialFunction = GaussianSpatialFunctionType::New();
ITK_EXERCISE_BASIC_OBJECT_METHODS(gaussianSpatialFunction, GaussianSpatialFunction, SpatialFunction);
ArrayType mean;
mean[0] = 13;
mean[1] = 17;
mean[2] = 19;
gaussianSpatialFunction->SetMean(mean);
ITK_TEST_SET_GET_VALUE(mean, gaussianSpatialFunction->GetMean());
ArrayType sigma;
sigma[0] = 5;
sigma[1] = 7;
sigma[2] = 9;
gaussianSpatialFunction->SetSigma(sigma);
ITK_TEST_SET_GET_VALUE(sigma, gaussianSpatialFunction->GetSigma());
double scale = std::stod(argv[1]);
gaussianSpatialFunction->SetScale(scale);
ITK_TEST_SET_GET_VALUE(scale, gaussianSpatialFunction->GetScale());
auto normalized = static_cast<bool>(std::stoi(argv[2]));
gaussianSpatialFunction->SetNormalized(normalized);
ITK_TEST_SET_GET_VALUE(normalized, gaussianSpatialFunction->GetNormalized());
if (normalized)
{
gaussianSpatialFunction->NormalizedOn();
ITK_TEST_SET_GET_VALUE(true, gaussianSpatialFunction->GetNormalized());
}
else
{
gaussianSpatialFunction->NormalizedOff();
ITK_TEST_SET_GET_VALUE(false, gaussianSpatialFunction->GetNormalized());
}
// Test the evaluation of the Gaussian spatial function
//
// Evaluate it at the center of the Gaussian
InputType point;
point[0] = mean[0];
point[1] = mean[1];
point[2] = mean[2];
double computedValueAtMean = gaussianSpatialFunction->Evaluate(point);
double expectedValueAtMean = 1.0;
if (gaussianSpatialFunction->GetNormalized())
{
const double oneDimensionalFactor = std::sqrt(2.0 * itk::Math::pi);
const double factor = oneDimensionalFactor * oneDimensionalFactor * oneDimensionalFactor;
expectedValueAtMean = scale / (sigma[0] * sigma[1] * sigma[2] * factor);
}
else
{
constexpr double oneDimensionalFactor = 1.0;
const double factor = oneDimensionalFactor * oneDimensionalFactor * oneDimensionalFactor;
expectedValueAtMean = scale / factor;
}
if (itk::Math::NotAlmostEquals(expectedValueAtMean, computedValueAtMean))
{
std::cerr << "Test failed!" << std::endl;
std::cerr << "Error in Evaluate at point " << point << std::endl;
std::cerr << "Expected value " << expectedValueAtMean << std::endl;
std::cerr << " differs from " << computedValueAtMean << std::endl;
return EXIT_FAILURE;
}
std::cerr << "Test finished." << std::endl;
return EXIT_SUCCESS;
}
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