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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 "itkMeanSampleFilter.h"
#include "itkListSample.h"
#include "itkSubsample.h"
int
itkSubsampleTest3(int, char *[])
{
std::cout << "MeanSampleFilter test \n \n";
constexpr unsigned int MeasurementVectorSize = 2;
constexpr unsigned int numberOfMeasurementVectors = 5;
unsigned int counter;
using MeasurementVectorType = itk::FixedArray<float, MeasurementVectorSize>;
using SampleType = itk::Statistics::ListSample<MeasurementVectorType>;
auto sample = SampleType::New();
sample->SetMeasurementVectorSize(MeasurementVectorSize);
MeasurementVectorType measure;
// reset counter
counter = 0;
while (counter < numberOfMeasurementVectors)
{
for (unsigned int i = 0; i < MeasurementVectorSize; ++i)
{
measure[i] = counter;
}
sample->PushBack(measure);
counter++;
}
using SubsampleType = itk::Statistics::Subsample<SampleType>;
auto subsample = SubsampleType::New();
subsample->SetSample(sample);
// Initialize the subsample with all the samples
subsample->InitializeWithAllInstances();
using FilterType = itk::Statistics::MeanSampleFilter<SubsampleType>;
auto filter = FilterType::New();
filter->SetInput(subsample);
try
{
filter->Update();
}
catch (const itk::ExceptionObject & excp)
{
std::cerr << "Exception caught: " << excp << std::endl;
}
const FilterType::MeasurementVectorDecoratedType * decorator = filter->GetOutput();
FilterType::MeasurementVectorType meanOutput = decorator->Get();
FilterType::MeasurementVectorType mean;
mean[0] = 2.0;
mean[1] = 2.0;
std::cout << meanOutput[0] << ' ' << mean[0] << ' ' << meanOutput[1] << ' ' << mean[1] << ' ' << std::endl;
FilterType::MeasurementVectorType::ValueType epsilon = 1e-6;
if ((itk::Math::abs(meanOutput[0] - mean[0]) > epsilon) || (itk::Math::abs(meanOutput[1] - mean[1]) > epsilon))
{
std::cerr << "The result is not what is expected" << std::endl;
return EXIT_FAILURE;
}
// Clear and repopulate the subsample container
subsample->Clear();
// add only the first half of instances of the sample
for (SampleType::InstanceIdentifier id = 0; id < static_cast<SampleType::InstanceIdentifier>(sample->Size() / 2);
id++)
{
subsample->AddInstance(id);
}
std::cout << "Subsample size: " << subsample->Size() << std::endl;
try
{
filter->Update();
}
catch (const itk::ExceptionObject & excp)
{
std::cerr << "Exception caught: " << excp << std::endl;
}
decorator = filter->GetOutput();
meanOutput = decorator->Get();
mean[0] = 0.5;
mean[1] = 0.5;
std::cout << meanOutput[0] << ' ' << mean[0] << ' ' << meanOutput[1] << ' ' << mean[1] << ' ' << std::endl;
if ((itk::Math::abs(meanOutput[0] - mean[0]) > epsilon) || (itk::Math::abs(meanOutput[1] - mean[1]) > epsilon))
{
std::cerr << "The result is not what is expected" << std::endl;
return EXIT_FAILURE;
}
return EXIT_SUCCESS;
}
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