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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 "itkGradientDescentOptimizerBasev4.h"
#include "itkImage.h"
#include "itkTestingMacros.h"
/* Create a simple metric to use for testing here. */
template <typename TFixedObject, typename TMovingObject>
class GradientDescentOptimizerBasev4TestMetric : public itk::ObjectToObjectMetricBase
{
public:
ITK_DISALLOW_COPY_AND_MOVE(GradientDescentOptimizerBasev4TestMetric);
/** Standard class type aliases. */
using Self = GradientDescentOptimizerBasev4TestMetric;
using Superclass = itk::ObjectToObjectMetricBase;
using Pointer = itk::SmartPointer<Self>;
using ConstPointer = itk::SmartPointer<const Self>;
using typename Superclass::MeasureType;
using typename Superclass::DerivativeType;
using typename Superclass::ParametersType;
using typename Superclass::ParametersValueType;
itkOverrideGetNameOfClassMacro(GradientDescentOptimizerBasev4TestMetric);
itkNewMacro(Self);
// Pure virtual functions that all Metrics must provide
unsigned int
GetNumberOfParameters() const override
{
return 5;
}
MeasureType
GetValue() const override
{
return itk::NumericTraits<MeasureType>::OneValue();
}
void
GetDerivative(DerivativeType & derivative) const override
{
derivative.Fill(ParametersValueType{});
}
void
GetValueAndDerivative(MeasureType & value, DerivativeType & derivative) const override
{
value = itk::NumericTraits<MeasureType>::OneValue();
derivative.Fill(ParametersValueType{});
}
unsigned int
GetNumberOfLocalParameters() const override
{
return 3;
}
void
UpdateTransformParameters(const DerivativeType &, ParametersValueType) override
{}
const ParametersType &
GetParameters() const override
{
return m_Parameters;
}
void
SetParameters(ParametersType &) override
{}
bool
HasLocalSupport() const override
{
return false;
}
void
Initialize() override
{}
void
PrintSelf(std::ostream & os, itk::Indent indent) const override
{
Superclass::PrintSelf(os, indent);
}
protected:
~GradientDescentOptimizerBasev4TestMetric() override = default;
private:
GradientDescentOptimizerBasev4TestMetric() = default;
ParametersType m_Parameters;
};
/* Define a simple derived optimizer class.
* \class GradientDescentOptimizerBasev4TestOptimizer */
class GradientDescentOptimizerBasev4TestOptimizer : public itk::GradientDescentOptimizerBasev4
{
public:
ITK_DISALLOW_COPY_AND_MOVE(GradientDescentOptimizerBasev4TestOptimizer);
/** Standard "Self" type alias. */
using Self = GradientDescentOptimizerBasev4TestOptimizer;
using Superclass = itk::GradientDescentOptimizerBasev4;
using Pointer = itk::SmartPointer<Self>;
using ConstPointer = itk::SmartPointer<const Self>;
/** Method for creation through the object factory. */
itkNewMacro(Self);
/** \see LightObject::GetNameOfClass() */
itkOverrideGetNameOfClassMacro(GradientDescentOptimizerBasev4TestOptimizer);
/* Provide an override for the pure virtual StartOptimization */
void
StartOptimization(bool doOnlyInitialization = false) override
{
Superclass::StartOptimization(doOnlyInitialization);
std::cout << "StartOptimization called. doOnlyInitialization: " << doOnlyInitialization << std::endl;
}
void
ResumeOptimization() override
{
std::cout << "ResumeOptimization called." << std::endl;
}
void
ModifyGradientByScalesOverSubRange(const IndexRangeType & index) override
{
std::cout << "ModifyGradientByScalesOverSubRange called with index:" << index << std::endl;
}
void
ModifyGradientByLearningRateOverSubRange(const IndexRangeType & index) override
{
std::cout << "ModifyGradientByLearningRateOverSubRange called with index:" << index << std::endl;
}
protected:
GradientDescentOptimizerBasev4TestOptimizer() = default;
~GradientDescentOptimizerBasev4TestOptimizer() override = default;
};
int
itkGradientDescentOptimizerBasev4Test(int, char *[])
{
constexpr int ImageDimension = 2;
using ImageType = itk::Image<double, ImageDimension>;
using MetricType = GradientDescentOptimizerBasev4TestMetric<ImageType, ImageType>;
auto metric = MetricType::New();
auto optimizer = GradientDescentOptimizerBasev4TestOptimizer::New();
bool doEstimateScales = true;
ITK_TEST_SET_GET_BOOLEAN(optimizer, DoEstimateScales, doEstimateScales);
optimizer->SetMetric(metric);
ITK_TEST_SET_GET_VALUE(metric, optimizer->GetMetric());
ITK_TEST_SET_GET_VALUE(0.0, optimizer->GetCurrentMetricValue());
optimizer->SetNumberOfWorkUnits(2);
ITK_TRY_EXPECT_NO_EXCEPTION(optimizer->StartOptimization());
std::cout << "Printing self.." << std::endl;
std::cout << optimizer << std::endl;
std::cout << "Test passed." << std::endl;
return EXIT_SUCCESS;
}
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