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/*=========================================================================
*
* Copyright Insight Software Consortium
*
* 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.
*
*=========================================================================*/
#ifndef itkConjugateGradientLineSearchOptimizerv4_hxx
#define itkConjugateGradientLineSearchOptimizerv4_hxx
#include "itkConjugateGradientLineSearchOptimizerv4.h"
namespace itk
{
/**
* Default constructor
*/
template<typename TInternalComputationValueType>
ConjugateGradientLineSearchOptimizerv4Template<TInternalComputationValueType>
::ConjugateGradientLineSearchOptimizerv4Template()
{
}
/**
* Destructor
*/
template<typename TInternalComputationValueType>
ConjugateGradientLineSearchOptimizerv4Template<TInternalComputationValueType>
::~ConjugateGradientLineSearchOptimizerv4Template()
{}
/**
*PrintSelf
*/
template<typename TInternalComputationValueType>
void
ConjugateGradientLineSearchOptimizerv4Template<TInternalComputationValueType>
::PrintSelf(std::ostream & os, Indent indent) const
{
Superclass::PrintSelf(os, indent);
}
template<typename TInternalComputationValueType>
void
ConjugateGradientLineSearchOptimizerv4Template<TInternalComputationValueType>
::StartOptimization( bool doOnlyInitialization)
{
this->m_ConjugateGradient.SetSize( this->m_Metric->GetNumberOfParameters() );
this->m_ConjugateGradient.Fill( itk::NumericTraits< TInternalComputationValueType >::ZeroValue() );
this->m_LastGradient.SetSize( this->m_Metric->GetNumberOfParameters() );
this->m_LastGradient.Fill( itk::NumericTraits< TInternalComputationValueType >::ZeroValue() );
Superclass::StartOptimization( doOnlyInitialization );
}
/**
* Advance one Step following the gradient direction
*/
template<typename TInternalComputationValueType>
void
ConjugateGradientLineSearchOptimizerv4Template<TInternalComputationValueType>
::AdvanceOneStep()
{
itkDebugMacro("AdvanceOneStep");
this->ModifyGradientByScales();
if ( this->m_CurrentIteration == 0 )
{
this->EstimateLearningRate();
}
TInternalComputationValueType gamma = itk::NumericTraits< TInternalComputationValueType >::ZeroValue();
TInternalComputationValueType gammaDenom = inner_product( this->m_LastGradient , this->m_LastGradient );
if ( gammaDenom > itk::NumericTraits< TInternalComputationValueType >::epsilon() )
{
gamma = inner_product( this->m_Gradient - this->m_LastGradient , this->m_Gradient ) / gammaDenom;
}
/** Modified Polak-Ribiere restart conditions */
if ( gamma < 0 || gamma > 5 )
{
gamma = 0;
}
this->m_LastGradient = this->m_Gradient;
this->m_ConjugateGradient = this->m_Gradient + this->m_ConjugateGradient * gamma;
this->m_Gradient = this->m_ConjugateGradient;
/* Estimate a learning rate for this step */
this->m_LineSearchIterations = 0;
this->m_LearningRate = this->GoldenSectionSearch( this->m_LearningRate * this->m_LowerLimit ,
this->m_LearningRate , this->m_LearningRate * this->m_UpperLimit );
/* Begin threaded gradient modification of m_Gradient variable. */
this->ModifyGradientByLearningRate();
try
{
/* Pass gradient to transform and let it do its own updating. */
this->m_Metric->UpdateTransformParameters( this->m_Gradient );
}
catch ( ExceptionObject & err )
{
this->m_StopCondition = Superclass::UPDATE_PARAMETERS_ERROR;
this->m_StopConditionDescription << "UpdateTransformParameters error";
this->StopOptimization();
// Pass exception to caller
throw err;
}
this->InvokeEvent( IterationEvent() );
}
}//namespace itk
#endif
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