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DimensionalityReductionModel.txx 4.14 KiB
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/*=========================================================================
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  Program:   ORFEO Toolbox
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  Language:  C++
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  Date:      $Date$
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  Version:   $Revision$
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  Copyright (c) Centre National d'Etudes Spatiales. All rights reserved.
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  See OTBCopyright.txt for details.
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     This software is distributed WITHOUT ANY WARRANTY; without even
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     the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
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     PURPOSE.  See the above copyright notices for more information.
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=========================================================================*/
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#ifndef DimensionalityReductionModel_txx
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#define DimensionalityReductionModel_txx
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#ifdef _OPENMP
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 # include <omp.h>
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#endif
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#include "DimensionalityReductionModel.h"
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#include "itkMultiThreader.h"
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namespace otb
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{
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template <class TInputValue, class TOutputValue>
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DimensionalityReductionModel<TInputValue,TOutputValue>
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::DimensionalityReductionModel()
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{ this->m_IsDoPredictBatchMultiThreaded=false;}
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template <class TInputValue, class TOutputValue>
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DimensionalityReductionModel<TInputValue,TOutputValue>
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::~DimensionalityReductionModel()
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{}
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template <class TInputValue, class TOutputValue>
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typename DimensionalityReductionModel<TInputValue,TOutputValue>
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::TargetSampleType
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DimensionalityReductionModel<TInputValue,TOutputValue>
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::Predict(const InputSampleType& input) const
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{
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  // Call protected specialization entry point
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  return this->DoPredict(input);
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}
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template <class TInputValue, class TOutputValue>
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typename DimensionalityReductionModel<TInputValue,TOutputValue>
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::TargetListSampleType::Pointer
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DimensionalityReductionModel<TInputValue,TOutputValue>
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::PredictBatch(const InputListSampleType * input) const
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{
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  typename TargetListSampleType::Pointer targets = TargetListSampleType::New();
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  targets->Resize(input->Size());
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  if(m_IsDoPredictBatchMultiThreaded)
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    {
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    // Simply calls DoPredictBatch
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    this->DoPredictBatch(input,0,input->Size(),targets);
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    return targets;
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} else { #ifdef _OPENMP // OpenMP threading here unsigned int nb_threads(0), threadId(0), nb_batches(0); #pragma omp parallel shared(nb_threads,nb_batches) private(threadId) { // Get number of threads configured with ITK omp_set_num_threads(itk::MultiThreader::GetGlobalDefaultNumberOfThreads()); nb_threads = omp_get_num_threads(); threadId = omp_get_thread_num(); nb_batches = std::min(nb_threads,(unsigned int)input->Size()); // Ensure that we do not spawn unncessary threads if(threadId<nb_batches) { unsigned int batch_size = ((unsigned int)input->Size()/nb_batches); unsigned int batch_start = threadId*batch_size; if(threadId == nb_threads-1) { batch_size+=input->Size()%nb_batches; } this->DoPredictBatch(input,batch_start,batch_size,targets); } } #else this->DoPredictBatch(input,0,input->Size(),targets); #endif return targets; } } template <class TInputValue, class TOutputValue> void DimensionalityReductionModel<TInputValue,TOutputValue> ::DoPredictBatch(const InputListSampleType * input, const unsigned int & startIndex, const unsigned int & size, TargetListSampleType * targets) const { assert(input != ITK_NULLPTR); assert(targets != ITK_NULLPTR); assert(input->Size()==targets->Size()&&"Input sample list and target label list do not have the same size."); assert(((quality==ITK_NULLPTR)||(quality->Size()==input->Size()))&&"Quality samples list is not null and does not have the same size as input samples list"); if(startIndex+size>input->Size()) { itkExceptionMacro(<<"requested range ["<<startIndex<<", "<<startIndex+size<<"[ partially outside input sample list range.[0,"<<input->Size()<<"["); } for(unsigned int id = startIndex;id<startIndex+size;++id) { const TargetSampleType target = this->DoPredict(input->GetMeasurementVector(id)); targets->SetMeasurementVector(id,target); } } template <class TInputValue, class TOutputValue> void DimensionalityReductionModel<TInputValue,TOutputValue> ::PrintSelf(std::ostream& os, itk::Indent indent) const { // Call superclass implementation Superclass::PrintSelf(os,indent); }
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} #endif