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/*=========================================================================
*
* Copyright UMC Utrecht and contributors
*
* 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
*
* http://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 "itkGradientDescentOptimizer2.h"
#include "itkCommand.h"
#include "itkEventObject.h"
#include "itkMacro.h"
namespace itk
{
/**
* ****************** Constructor ************************
*/
GradientDescentOptimizer2 ::GradientDescentOptimizer2()
{
itkDebugMacro("Constructor");
} // end Constructor
/**
* *************** PrintSelf *************************
*/
void
GradientDescentOptimizer2 ::PrintSelf(std::ostream & os, Indent indent) const
{
this->Superclass::PrintSelf(os, indent);
os << indent << "LearningRate: " << this->m_LearningRate << std::endl;
os << indent << "NumberOfIterations: " << this->m_NumberOfIterations << std::endl;
os << indent << "CurrentIteration: " << this->m_CurrentIteration;
os << indent << "Value: " << this->m_Value;
os << indent << "StopCondition: " << this->m_StopCondition;
os << std::endl;
os << indent << "Gradient: " << this->m_Gradient;
os << std::endl;
} // end PrintSelf()
/**
* **************** StartOptimization ********************
*/
void
GradientDescentOptimizer2 ::StartOptimization()
{
this->m_CurrentIteration = 0;
/** Get the number of parameters; checks also if a cost function has been set at all.
* if not: an exception is thrown */
this->GetScaledCostFunction()->GetNumberOfParameters();
/** Initialize the scaledCostFunction with the currently set scales */
this->InitializeScales();
/** Set the current position as the scaled initial position */
this->SetCurrentPosition(this->GetInitialPosition());
this->ResumeOptimization();
} // end StartOptimization()
/**
* ************************ ResumeOptimization *************
*/
void
GradientDescentOptimizer2 ::ResumeOptimization()
{
itkDebugMacro("ResumeOptimization");
this->m_Stop = false;
InvokeEvent(StartEvent());
const unsigned int spaceDimension = this->GetScaledCostFunction()->GetNumberOfParameters();
this->m_Gradient.set_size(spaceDimension); // check this
while (!this->m_Stop)
{
// Check m_CurrentIteration right at the start of the loop, ensuring that
// no step at all is performed when when m_NumberOfIterations is zero.
if (m_CurrentIteration >= m_NumberOfIterations)
{
this->m_StopCondition = MaximumNumberOfIterations;
this->StopOptimization();
break;
}
try
{
this->GetScaledValueAndDerivative(this->GetScaledCurrentPosition(), m_Value, m_Gradient);
}
catch (ExceptionObject & err)
{
this->MetricErrorResponse(err);
}
/** StopOptimization may have been called. */
if (this->m_Stop)
{
break;
}
this->AdvanceOneStep();
/** StopOptimization may have been called. */
if (this->m_Stop)
{
break;
}
this->m_CurrentIteration++;
} // end while
} // end ResumeOptimization()
/**
* ***************** MetricErrorResponse ************************
*/
void
GradientDescentOptimizer2 ::MetricErrorResponse(ExceptionObject & err)
{
/** An exception has occurred. Terminate immediately. */
this->m_StopCondition = MetricError;
this->StopOptimization();
/** Pass exception to caller. */
throw err;
} // end MetricErrorResponse()
/**
* ***************** StopOptimization ************************
*/
void
GradientDescentOptimizer2 ::StopOptimization()
{
itkDebugMacro("StopOptimization");
this->m_Stop = true;
this->InvokeEvent(EndEvent());
} // end StopOptimization()
/**
* ************ AdvanceOneStep ****************************
*/
void
GradientDescentOptimizer2 ::AdvanceOneStep()
{
itkDebugMacro("AdvanceOneStep");
/** Get space dimension. */
const unsigned int spaceDimension = this->GetScaledCostFunction()->GetNumberOfParameters();
/** Get a reference to the previously allocated newPosition. */
ParametersType & newPosition = this->m_ScaledCurrentPosition;
/** Advance one step. */
// single-threaded since it is fastest most of the times
/** Get a reference to the current position. */
const ParametersType & currentPosition = this->GetScaledCurrentPosition();
/** Update the new position. */
for (unsigned int j = 0; j < spaceDimension; ++j)
{
newPosition[j] = currentPosition[j] - this->m_LearningRate * this->m_Gradient[j];
}
this->InvokeEvent(IterationEvent());
} // end AdvanceOneStep()
} // end namespace itk
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