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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 "itkWin32Header.h"
#include <fstream>
#include "itkImageToNeighborhoodSampleAdaptor.h"
#include "itkSubsample.h"
#include "itkImageFileWriter.h"
#include "itkZeroFluxNeumannBoundaryCondition.h"
#include "itkGaussianRandomSpatialNeighborSubsampler.h"
#include "itkMath.h"
int
itkGaussianRandomSpatialNeighborSubsamplerTest(int argc, char * argv[])
{
std::cout << "GaussianRandomSpatialNeighborSubsampler Test \n \n";
std::string outFile = "";
if (argc > 1)
{
outFile = argv[1];
}
using FloatImage = itk::Image<float, 2>;
using RegionType = FloatImage::RegionType;
using IndexType = FloatImage::IndexType;
using SizeType = FloatImage::SizeType;
using BoundaryCondition = itk::ZeroFluxNeumannBoundaryCondition<FloatImage>;
using AdaptorType = itk::Statistics::ImageToNeighborhoodSampleAdaptor<FloatImage, BoundaryCondition>;
using SamplerType = itk::Statistics::GaussianRandomSpatialNeighborSubsampler<AdaptorType, RegionType>;
using WriterType = itk::ImageFileWriter<FloatImage>;
auto inImage = FloatImage::New();
SizeType sz;
sz.Fill(35);
IndexType idx;
idx.Fill(0);
RegionType region{ idx, sz };
inImage->SetRegions(region);
inImage->AllocateInitialized();
auto sample = AdaptorType::New();
sample->SetImage(inImage);
auto sampler_orig = SamplerType::New();
sampler_orig->SetSample(sample);
sampler_orig->SetSampleRegion(region);
sampler_orig->SetRadius(20);
sampler_orig->SetNumberOfResultsRequested(50);
sampler_orig->SetVariance(25);
sampler_orig->SetSeed(100);
sampler_orig->CanSelectQueryOff();
// test clone mechanism
SamplerType::Pointer sampler = sampler_orig->Clone().GetPointer();
if (sampler->GetSample() != sampler_orig->GetSample())
{
std::cerr << "Clone did not copy the sample correctly!" << std::endl;
return EXIT_FAILURE;
}
if (sampler->GetSampleRegion() != sampler_orig->GetSampleRegion())
{
std::cerr << "Clone did not copy the region correctly!" << std::endl;
return EXIT_FAILURE;
}
if (sampler->GetRadius() != sampler_orig->GetRadius())
{
std::cerr << "Clone did not copy the radius correctly!" << std::endl;
return EXIT_FAILURE;
}
if (sampler->GetNumberOfResultsRequested() != sampler_orig->GetNumberOfResultsRequested())
{
std::cerr << "Clone did not copy the number of results requested correctly!" << std::endl;
return EXIT_FAILURE;
}
if (itk::Math::NotExactlyEquals(sampler->GetVariance(), sampler_orig->GetVariance()))
{
std::cerr << "Clone did not copy the variance correctly!" << std::endl;
return EXIT_FAILURE;
}
if (sampler->GetSeed() != sampler_orig->GetSeed())
{
std::cerr << "Clone did not copy the seed correctly!" << std::endl;
return EXIT_FAILURE;
}
if (sampler->GetCanSelectQuery() != sampler_orig->GetCanSelectQuery())
{
std::cerr << "Clone did not copy CanSelectQuery correctly!" << std::endl;
return EXIT_FAILURE;
}
SamplerType::SubsamplePointer subsample = SamplerType::SubsampleType::New();
sampler->Search(612, subsample);
for (SamplerType::SubsampleConstIterator sIt = subsample->Begin(); sIt != subsample->End(); ++sIt)
{
IndexType index;
index = sIt.GetMeasurementVector()[0].GetIndex();
inImage->SetPixel(index, 255);
}
if (!outFile.empty())
{
auto writer = WriterType::New();
writer->SetFileName(outFile);
writer->SetInput(inImage);
try
{
writer->Update();
}
catch (const itk::ExceptionObject & excp)
{
std::cerr << excp << std::endl;
}
}
std::cout << "Test passed." << std::endl;
return EXIT_SUCCESS;
}
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