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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 "itkWeightedMeanSampleFilter.h"
#include "itkListSample.h"
constexpr unsigned int MeasurementVectorSize = 2;
using MeasurementVectorType = itk::FixedArray<float, MeasurementVectorSize>;
class WeightedMeanTestFunction : public itk::FunctionBase<MeasurementVectorType, double>
{
public:
/** Standard class type aliases. */
using Self = WeightedMeanTestFunction;
using Superclass = itk::FunctionBase<MeasurementVectorType, double>;
using Pointer = itk::SmartPointer<Self>;
using ConstPointer = itk::SmartPointer<const Self>;
/** \see LightObject::GetNameOfClass() */
itkOverrideGetNameOfClassMacro(WeightedMeanTestFunction);
itkNewMacro(Self);
/** Input type */
using InputType = MeasurementVectorType;
/** Output type */
using OutputType = double;
/**Evaluate at the specified input position */
OutputType
Evaluate(const InputType & input) const override
{
MeasurementVectorType measurements;
// set the weight factor of the measurement
// vector with valuev[2, 2] to 0.5.
measurements.Fill(2.0f);
if (input != measurements)
{
return 0.5;
}
else
{
return 1.0;
}
}
protected:
WeightedMeanTestFunction() = default;
~WeightedMeanTestFunction() override = default;
}; // end of class
int
itkWeightedMeanSampleFilterTest(int, char *[])
{
std::cout << "WeightedMeanSampleFilter test \n \n";
constexpr unsigned int numberOfMeasurementVectors = 5;
unsigned int counter;
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 FilterType = itk::Statistics::WeightedMeanSampleFilter<SampleType>;
auto filter = FilterType::New();
std::cout << filter->GetNameOfClass() << std::endl;
filter->Print(std::cout);
// Invoke update before adding an input. An exception should be
// thrown.
try
{
filter->Update();
std::cerr << "Exception should have been thrown since Update() is invoked without setting an input " << std::endl;
return EXIT_FAILURE;
}
catch (const itk::ExceptionObject & excp)
{
std::cerr << "Exception caught: " << excp << std::endl;
}
if (filter->GetInput() != nullptr)
{
std::cerr << "GetInput() should return nullptr if the input has not been set" << std::endl;
return EXIT_FAILURE;
}
filter->ResetPipeline();
filter->SetInput(sample);
// run the filters without weighting coefficients
try
{
filter->Update();
}
catch (const itk::ExceptionObject & excp)
{
std::cerr << "Exception caught: " << excp << std::endl;
}
const FilterType::MeasurementVectorDecoratedType * decorator = filter->GetOutput();
FilterType::MeasurementVectorRealType meanOutput = decorator->Get();
FilterType::MeasurementVectorRealType mean;
mean[0] = 2.0;
mean[1] = 2.0;
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 << "Wrong result " << std::endl;
std::cerr << meanOutput[0] << ' ' << mean[0] << ' ' << meanOutput[1] << ' ' << mean[1] << ' ' << std::endl;
std::cerr << "The result is not what is expected" << std::endl;
return EXIT_FAILURE;
}
using WeightArrayType = FilterType::WeightArrayType;
WeightArrayType weightArray(sample->Size());
weightArray.Fill(1.0);
filter->SetWeights(weightArray);
try
{
filter->Update();
}
catch (const itk::ExceptionObject & excp)
{
std::cerr << "Exception caught: " << excp << std::endl;
}
decorator = filter->GetOutput();
meanOutput = decorator->Get();
mean[0] = 2.0;
mean[1] = 2.0;
if ((itk::Math::abs(meanOutput[0] - mean[0]) > epsilon) || (itk::Math::abs(meanOutput[1] - mean[1]) > epsilon))
{
std::cerr << "Wrong result " << std::endl;
std::cerr << meanOutput[0] << ' ' << mean[0] << ' ' << meanOutput[1] << ' ' << mean[1] << ' ' << std::endl;
std::cerr << "The result is not what is expected" << std::endl;
return EXIT_FAILURE;
}
// change the weight of the last element to 0.5 and recompute
weightArray[numberOfMeasurementVectors - 1] = 0.5;
filter->SetWeights(weightArray);
try
{
filter->Update();
}
catch (const itk::ExceptionObject & excp)
{
std::cerr << "Exception caught: " << excp << std::endl;
}
decorator = filter->GetOutput();
meanOutput = decorator->Get();
mean[0] = 1.7777778;
mean[1] = 1.7777778;
if ((itk::Math::abs(meanOutput[0] - mean[0]) > epsilon) || (itk::Math::abs(meanOutput[1] - mean[1]) > epsilon))
{
std::cerr << "Wrong result" << std::endl;
std::cerr << meanOutput[0] << ' ' << mean[0] << ' ' << meanOutput[1] << ' ' << mean[1] << ' ' << std::endl;
std::cerr << "The result is not what is expected" << std::endl;
return EXIT_FAILURE;
}
// set the weight using a function
auto weightFunction = WeightedMeanTestFunction::New();
filter->SetWeightingFunction(weightFunction);
try
{
filter->Update();
}
catch (const itk::ExceptionObject & excp)
{
std::cerr << "Exception caught: " << excp << std::endl;
}
decorator = filter->GetOutput();
meanOutput = decorator->Get();
mean[0] = 2.0;
mean[1] = 2.0;
if ((itk::Math::abs(meanOutput[0] - mean[0]) > epsilon) || (itk::Math::abs(meanOutput[1] - mean[1]) > epsilon))
{
std::cerr << "Wrong result" << std::endl;
std::cerr << meanOutput[0] << ' ' << mean[0] << ' ' << meanOutput[1] << ' ' << mean[1] << ' ' << std::endl;
std::cerr << "The result is not what is expected" << std::endl;
return EXIT_FAILURE;
}
std::cout << "Test passed." << std::endl;
return EXIT_SUCCESS;
}
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