/*========================================================================= * * 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 "itkMultipleValuedNonLinearVnlOptimizer.h" namespace itk { /** * Constructor */ MultipleValuedNonLinearVnlOptimizer::MultipleValuedNonLinearVnlOptimizer() { m_CostFunctionAdaptor = nullptr; m_UseGradient = true; m_Command = CommandType::New(); m_Command->SetCallbackFunction(this, &MultipleValuedNonLinearVnlOptimizer::IterationReport); m_CachedValue.Fill(0); m_CachedCurrentPosition.Fill(0); m_CachedDerivative.Fill(0); } /** * Destructor */ MultipleValuedNonLinearVnlOptimizer::~MultipleValuedNonLinearVnlOptimizer() { delete m_CostFunctionAdaptor; m_CostFunctionAdaptor = nullptr; } void MultipleValuedNonLinearVnlOptimizer::SetCostFunctionAdaptor(CostFunctionAdaptorType * adaptor) { if (m_CostFunctionAdaptor == adaptor) { return; } delete m_CostFunctionAdaptor; m_CostFunctionAdaptor = adaptor; this->SetUseCostFunctionGradient(m_UseGradient); m_CostFunctionAdaptor->AddObserver(IterationEvent(), m_Command); } const MultipleValuedNonLinearVnlOptimizer::CostFunctionAdaptorType * MultipleValuedNonLinearVnlOptimizer::GetCostFunctionAdaptor() const { return m_CostFunctionAdaptor; } MultipleValuedNonLinearVnlOptimizer::CostFunctionAdaptorType * MultipleValuedNonLinearVnlOptimizer::GetCostFunctionAdaptor() { return m_CostFunctionAdaptor; } /** The purpose of this method is to get around the lack of const * correctness in vnl cost_functions and optimizers */ MultipleValuedNonLinearVnlOptimizer::CostFunctionAdaptorType * MultipleValuedNonLinearVnlOptimizer::GetNonConstCostFunctionAdaptor() const { return m_CostFunctionAdaptor; } void MultipleValuedNonLinearVnlOptimizer::SetUseCostFunctionGradient(bool useGradient) { if (m_CostFunctionAdaptor) { m_CostFunctionAdaptor->SetUseGradient(useGradient); } else { m_UseGradient = useGradient; } } bool MultipleValuedNonLinearVnlOptimizer::GetUseCostFunctionGradient() const { if (m_CostFunctionAdaptor) { return m_CostFunctionAdaptor->GetUseGradient(); } else { return m_UseGradient; } } /** The purpose of this method is to get around the lack of iteration reporting * in VNL optimizers. By interfacing directly with the ITK cost function * adaptor we are generating here Iteration Events. Note the iteration events * here are produce PER EVALUATION of the metric, not per real iteration of the * vnl optimizer. Optimizers that evaluate the metric multiple times at each * iteration will generate a lot more of Iteration events here. */ void MultipleValuedNonLinearVnlOptimizer::IterationReport(const EventObject & event) { const CostFunctionAdaptorType * adaptor = this->GetCostFunctionAdaptor(); m_CachedValue = adaptor->GetCachedValue(); m_CachedDerivative = adaptor->GetCachedDerivative(); m_CachedCurrentPosition = adaptor->GetCachedCurrentParameters(); this->InvokeEvent(event); } /** * PrintSelf */ void MultipleValuedNonLinearVnlOptimizer::PrintSelf(std::ostream & os, Indent indent) const { Superclass::PrintSelf(os, indent); os << indent << "Cached Value: " << m_CachedValue << std::endl; os << indent << "Cached Derivative: " << m_CachedDerivative << std::endl; os << indent << "Cached current positiion: " << m_CachedCurrentPosition << std::endl; os << indent << "Command observer " << m_Command.GetPointer() << std::endl; os << indent << "Cost Function adaptor" << m_CostFunctionAdaptor << std::endl; } } // end namespace itk