From d5ed9ebb5054f9f451f72419bda4c35a314beece Mon Sep 17 00:00:00 2001
From: Guillaume Pasero <guillaume.pasero@c-s.fr>
Date: Tue, 5 Dec 2017 12:05:07 +0100
Subject: [PATCH] STYLE: use OTB coding style

---
 .../include/otbAutoencoderModelFactory.h      | 20 +-------
 .../include/otbAutoencoderModelFactory.txx    | 20 ++++----
 .../otbDimensionalityReductionModelFactory.h  |  4 --
 ...otbDimensionalityReductionModelFactory.txx | 51 +++++--------------
 .../otbImageDimensionalityReductionFilter.h   |  1 -
 .../otbImageDimensionalityReductionFilter.txx | 49 +++++++-----------
 6 files changed, 41 insertions(+), 104 deletions(-)

diff --git a/Modules/Learning/DimensionalityReductionLearning/include/otbAutoencoderModelFactory.h b/Modules/Learning/DimensionalityReductionLearning/include/otbAutoencoderModelFactory.h
index eacd2901ef..a9b0065e8c 100644
--- a/Modules/Learning/DimensionalityReductionLearning/include/otbAutoencoderModelFactory.h
+++ b/Modules/Learning/DimensionalityReductionLearning/include/otbAutoencoderModelFactory.h
@@ -20,15 +20,12 @@
 #ifndef otbAutoencoderModelFactory_h
 #define otbAutoencoderModelFactory_h
 
-
-//#include <shark/Models/TiedAutoencoder.h>
-//#include <shark/Models/Autoencoder.h>
 #include "itkObjectFactoryBase.h"
 #include "itkImageIOBase.h"
 
 namespace otb
 {
-	
+
 template <class TInputValue, class TTargetValue, class NeuronType>
 class ITK_EXPORT AutoencoderModelFactory : public itk::ObjectFactoryBase
 {
@@ -63,27 +60,12 @@ protected:
 private:
   AutoencoderModelFactory(const Self &); //purposely not implemented
   void operator =(const Self&); //purposely not implemented
-
 };
 
-
-
-/*
-template <class TInputValue, class TTargetValue>
-using AutoencoderModelFactory = AutoencoderModelFactoryBase<TInputValue, TTargetValue, shark::Autoencoder< shark::TanhNeuron, shark::LinearNeuron>>  ;
-
-
-template <class TInputValue, class TTargetValue>
-using TiedAutoencoderModelFactory = AutoencoderModelFactoryBase<TInputValue, TTargetValue, shark::TiedAutoencoder< shark::TanhNeuron, shark::LinearNeuron>>  ;
-*/
-
 } //namespace otb
 
-
 #ifndef OTB_MANUAL_INSTANTIATION
 #include "otbAutoencoderModelFactory.txx"
 #endif
 
 #endif
-
-
diff --git a/Modules/Learning/DimensionalityReductionLearning/include/otbAutoencoderModelFactory.txx b/Modules/Learning/DimensionalityReductionLearning/include/otbAutoencoderModelFactory.txx
index 0d66ea86e0..c55f718a62 100644
--- a/Modules/Learning/DimensionalityReductionLearning/include/otbAutoencoderModelFactory.txx
+++ b/Modules/Learning/DimensionalityReductionLearning/include/otbAutoencoderModelFactory.txx
@@ -20,7 +20,6 @@
 #ifndef otbAutoencoderModelFactory_txx
 #define otbAutoencoderModelFactory_txx
 
-
 #include "otbAutoencoderModelFactory.h"
 #include "otbAutoencoderModel.h"
 
@@ -32,16 +31,15 @@ namespace otb
 template <class TInputValue, class TOutputValue, class NeuronType>
 AutoencoderModelFactory<TInputValue,TOutputValue, NeuronType>::AutoencoderModelFactory()
 {
-
   std::string classOverride = std::string("DimensionalityReductionModel");
   std::string subclass = std::string("AutoencoderModel");
 
-  this->RegisterOverride(classOverride.c_str(),
-                         subclass.c_str(),
-                         "Shark AE ML Model",
-                         1,
-                         //   itk::CreateObjectFunction<AutoencoderModel<TInputValue,TOutputValue> >::New());
-                         itk::CreateObjectFunction<AutoencoderModel<TInputValue,NeuronType > >::New());
+  this->RegisterOverride(
+    classOverride.c_str(),
+    subclass.c_str(),
+    "Shark AE ML Model",
+    1,
+    itk::CreateObjectFunction<AutoencoderModel<TInputValue,NeuronType > >::New());
 }
 
 template <class TInputValue, class TOutputValue, class NeuronType>
@@ -50,13 +48,15 @@ AutoencoderModelFactory<TInputValue,TOutputValue, NeuronType>::~AutoencoderModel
 }
 
 template <class TInputValue, class TOutputValue, class NeuronType>
-const char* AutoencoderModelFactory<TInputValue,TOutputValue, NeuronType>::GetITKSourceVersion(void) const
+const char*
+AutoencoderModelFactory<TInputValue,TOutputValue, NeuronType>::GetITKSourceVersion(void) const
 {
   return ITK_SOURCE_VERSION;
 }
 
 template <class TInputValue, class TOutputValue, class NeuronType>
-const char* AutoencoderModelFactory<TInputValue,TOutputValue, NeuronType>::GetDescription() const
+const char*
+AutoencoderModelFactory<TInputValue,TOutputValue, NeuronType>::GetDescription() const
 {
   return "Autoencoder model factory";
 }
diff --git a/Modules/Learning/DimensionalityReductionLearning/include/otbDimensionalityReductionModelFactory.h b/Modules/Learning/DimensionalityReductionLearning/include/otbDimensionalityReductionModelFactory.h
index 21c1d8a04a..a96235ccb9 100644
--- a/Modules/Learning/DimensionalityReductionLearning/include/otbDimensionalityReductionModelFactory.h
+++ b/Modules/Learning/DimensionalityReductionLearning/include/otbDimensionalityReductionModelFactory.h
@@ -20,9 +20,7 @@
 #ifndef otbDimensionalityReductionModelFactory_h
 #define otbDimensionalityReductionModelFactory_h
 
-//#include "DimensionalityReductionModel.h"
 #include "otbMachineLearningModelFactoryBase.h"
- 
 #include "otbMachineLearningModel.h" 
 
 namespace otb
@@ -54,7 +52,6 @@ public:
   /** Mode in which the files is intended to be used */
   typedef enum { ReadMode, WriteMode } FileModeType;
 
-
   /** Create the appropriate MachineLearningModel depending on the particulars of the file. */
   static DimensionalityReductionModelTypePointer CreateDimensionalityReductionModel(const std::string& path, FileModeType mode);
 
@@ -74,7 +71,6 @@ private:
   /** Register a single factory, ensuring it has not been registered
     * twice */
   static void RegisterFactory(itk::ObjectFactoryBase * factory);
-
 };
 
 } // end namespace otb
diff --git a/Modules/Learning/DimensionalityReductionLearning/include/otbDimensionalityReductionModelFactory.txx b/Modules/Learning/DimensionalityReductionLearning/include/otbDimensionalityReductionModelFactory.txx
index 65280436ca..f289ab83d9 100644
--- a/Modules/Learning/DimensionalityReductionLearning/include/otbDimensionalityReductionModelFactory.txx
+++ b/Modules/Learning/DimensionalityReductionLearning/include/otbDimensionalityReductionModelFactory.txx
@@ -32,15 +32,12 @@
 
 #include "itkMutexLockHolder.h"
 
-
 namespace otb
 {
 
-
 template <class TInputValue, class TTargetValue>
 using LogAutoencoderModelFactory = AutoencoderModelFactory<TInputValue, TTargetValue, shark::LogisticNeuron>  ;
 
-
 template <class TInputValue, class TTargetValue>
 using SOM2DModelFactory = SOMModelFactory<TInputValue, TTargetValue, 2>  ;
 
@@ -55,7 +52,7 @@ using SOM5DModelFactory = SOMModelFactory<TInputValue, TTargetValue, 5>  ;
 
 
 template <class TInputValue, class TOutputValue>
-typename MachineLearningModel<itk::VariableLengthVector< TInputValue> , itk::VariableLengthVector< TOutputValue>>::Pointer
+typename MachineLearningModel<itk::VariableLengthVector< TInputValue>, itk::VariableLengthVector< TOutputValue> >::Pointer
 DimensionalityReductionModelFactory<TInputValue,TOutputValue>
 ::CreateDimensionalityReductionModel(const std::string& path, FileModeType mode)
 {
@@ -64,7 +61,7 @@ DimensionalityReductionModelFactory<TInputValue,TOutputValue>
   std::list<DimensionalityReductionModelTypePointer> possibleDimensionalityReductionModel;
   std::list<LightObject::Pointer> allobjects =
     itk::ObjectFactoryBase::CreateAllInstance("DimensionalityReductionModel");
- 
+
   for(std::list<LightObject::Pointer>::iterator i = allobjects.begin();
       i != allobjects.end(); ++i)
     {
@@ -75,19 +72,17 @@ DimensionalityReductionModelFactory<TInputValue,TOutputValue>
       }
     else
       {
-	
       std::cerr << "Error DimensionalityReductionModel Factory did not return an DimensionalityReductionModel: "
                 << (*i)->GetNameOfClass()
                 << std::endl;
       }
     }
-  
-for(typename std::list<DimensionalityReductionModelTypePointer>::iterator k = possibleDimensionalityReductionModel.begin();
+
+  for(typename std::list<DimensionalityReductionModelTypePointer>::iterator k = possibleDimensionalityReductionModel.begin();
       k != possibleDimensionalityReductionModel.end(); ++k)
     {
-      if( mode == ReadMode )
+    if( mode == ReadMode )
       {
-		
       if((*k)->CanReadFile(path))
         {
         return *k;
@@ -99,7 +94,6 @@ for(typename std::list<DimensionalityReductionModelTypePointer>::iterator k = po
         {
         return *k;
         }
-
       }
     }
   return ITK_NULLPTR;
@@ -111,20 +105,16 @@ DimensionalityReductionModelFactory<TInputValue,TOutputValue>
 ::RegisterBuiltInFactories()
 {
   itk::MutexLockHolder<itk::SimpleMutexLock> lockHolder(mutex);
-  
-  
 
   RegisterFactory(SOM2DModelFactory<TInputValue,TOutputValue>::New());
   RegisterFactory(SOM3DModelFactory<TInputValue,TOutputValue>::New());
   RegisterFactory(SOM4DModelFactory<TInputValue,TOutputValue>::New());
   RegisterFactory(SOM5DModelFactory<TInputValue,TOutputValue>::New());
-  
+
 #ifdef OTB_USE_SHARK
   RegisterFactory(PCAModelFactory<TInputValue,TOutputValue>::New());
   RegisterFactory(LogAutoencoderModelFactory<TInputValue,TOutputValue>::New());
-  // RegisterFactory(TiedAutoencoderModelFactory<TInputValue,TOutputValue>::New());
 #endif
-  
 }
 
 template <class TInputValue, class TOutputValue>
@@ -151,17 +141,15 @@ DimensionalityReductionModelFactory<TInputValue,TOutputValue>
 
   for (itFac = factories.begin(); itFac != factories.end() ; ++itFac)
     {
-
-	// SOM
-	
-	SOM5DModelFactory<TInputValue,TOutputValue> *som5dFactory =
+    // SOM 5D
+    SOM5DModelFactory<TInputValue,TOutputValue> *som5dFactory =
       dynamic_cast<SOM5DModelFactory<TInputValue,TOutputValue> *>(*itFac);
     if (som5dFactory)
       {
       itk::ObjectFactoryBase::UnRegisterFactory(som5dFactory);
       continue;
       }
-    
+    // SOM 4D
     SOM4DModelFactory<TInputValue,TOutputValue> *som4dFactory =
       dynamic_cast<SOM4DModelFactory<TInputValue,TOutputValue> *>(*itFac);
     if (som4dFactory)
@@ -169,7 +157,7 @@ DimensionalityReductionModelFactory<TInputValue,TOutputValue>
       itk::ObjectFactoryBase::UnRegisterFactory(som4dFactory);
       continue;
       }
-      
+    // SOM 3D
     SOM3DModelFactory<TInputValue,TOutputValue> *som3dFactory =
       dynamic_cast<SOM3DModelFactory<TInputValue,TOutputValue> *>(*itFac);
     if (som3dFactory)
@@ -177,7 +165,7 @@ DimensionalityReductionModelFactory<TInputValue,TOutputValue>
       itk::ObjectFactoryBase::UnRegisterFactory(som3dFactory);
       continue;
       }
-      
+    // SOM 2D
     SOM2DModelFactory<TInputValue,TOutputValue> *som2dFactory =
       dynamic_cast<SOM2DModelFactory<TInputValue,TOutputValue> *>(*itFac);
     if (som2dFactory)
@@ -185,9 +173,8 @@ DimensionalityReductionModelFactory<TInputValue,TOutputValue>
       itk::ObjectFactoryBase::UnRegisterFactory(som2dFactory);
       continue;
       }
-      
 #ifdef OTB_USE_SHARK
-	
+    // Autoencoder
     LogAutoencoderModelFactory<TInputValue,TOutputValue> *aeFactory =
       dynamic_cast<LogAutoencoderModelFactory<TInputValue,TOutputValue> *>(*itFac);
     if (aeFactory)
@@ -195,17 +182,7 @@ DimensionalityReductionModelFactory<TInputValue,TOutputValue>
       itk::ObjectFactoryBase::UnRegisterFactory(aeFactory);
       continue;
       }
-    
-    /*
-    TiedAutoencoderModelFactory<TInputValue,TOutputValue> *taeFactory =
-      dynamic_cast<TiedAutoencoderModelFactory<TInputValue,TOutputValue> *>(*itFac);
-    if (taeFactory)
-      {
-      itk::ObjectFactoryBase::UnRegisterFactory(taeFactory);
-      continue;
-      }
-    */
-    // PCA  
+    // PCA
     PCAModelFactory<TInputValue,TOutputValue> *pcaFactory =
       dynamic_cast<PCAModelFactory<TInputValue,TOutputValue> *>(*itFac);
     if (pcaFactory)
@@ -214,9 +191,7 @@ DimensionalityReductionModelFactory<TInputValue,TOutputValue>
       continue;
       }
 #endif
-
     }
-
 }
 
 } // end namespace otb
diff --git a/Modules/Learning/DimensionalityReductionLearning/include/otbImageDimensionalityReductionFilter.h b/Modules/Learning/DimensionalityReductionLearning/include/otbImageDimensionalityReductionFilter.h
index 67bf3d2e4e..93c60cf022 100644
--- a/Modules/Learning/DimensionalityReductionLearning/include/otbImageDimensionalityReductionFilter.h
+++ b/Modules/Learning/DimensionalityReductionLearning/include/otbImageDimensionalityReductionFilter.h
@@ -21,7 +21,6 @@
 #define otbImageDimensionalityReduction_h
 
 #include "itkImageToImageFilter.h"
-//#include "DimensionalityReductionModel.h"
 #include "otbMachineLearningModel.h"
 #include "otbImage.h"
 
diff --git a/Modules/Learning/DimensionalityReductionLearning/include/otbImageDimensionalityReductionFilter.txx b/Modules/Learning/DimensionalityReductionLearning/include/otbImageDimensionalityReductionFilter.txx
index 8f7a715621..2656e21e1f 100644
--- a/Modules/Learning/DimensionalityReductionLearning/include/otbImageDimensionalityReductionFilter.txx
+++ b/Modules/Learning/DimensionalityReductionLearning/include/otbImageDimensionalityReductionFilter.txx
@@ -36,8 +36,6 @@ ImageDimensionalityReductionFilter<TInputImage, TOutputImage, TMaskImage>
   this->SetNumberOfIndexedInputs(2);
   this->SetNumberOfRequiredInputs(1);
 
-  //m_DefaultLabel = itk::NumericTraits<LabelType>::ZeroValue();
-
   this->SetNumberOfRequiredOutputs(2);
   this->SetNthOutput(0,TOutputImage::New());
   this->SetNthOutput(1,ConfidenceImageType::New());
@@ -113,9 +111,7 @@ ImageDimensionalityReductionFilter<TInputImage, TOutputImage, TMaskImage>
 
   // Define iterators
   typedef itk::ImageRegionConstIterator<InputImageType> InputIteratorType;
-  //typedef itk::ImageRegionConstIterator<MaskImageType>  MaskIteratorType;
   typedef itk::ImageRegionIterator<OutputImageType>     OutputIteratorType;
-  //typedef itk::ImageRegionIterator<ConfidenceImageType> ConfidenceMapIteratorType;
 
   InputIteratorType inIt(inputPtr, outputRegionForThread);
   OutputIteratorType outIt(outputPtr, outputRegionForThread);
@@ -123,43 +119,36 @@ ImageDimensionalityReductionFilter<TInputImage, TOutputImage, TMaskImage>
   // Walk the part of the image
   for (inIt.GoToBegin(), outIt.GoToBegin(); !inIt.IsAtEnd() && !outIt.IsAtEnd(); ++inIt, ++outIt)
     {
-	// Classifify
-
-	outIt.Set(m_Model->Predict(inIt.Get()));
+    // Classifify
+    outIt.Set(m_Model->Predict(inIt.Get()));
     progress.CompletedPixel();
     }
-
 }
 
 template <class TInputImage, class TOutputImage, class TMaskImage>
 void ImageDimensionalityReductionFilter<TInputImage, TOutputImage, TMaskImage>::GenerateOutputInformation()
 {
-	Superclass::GenerateOutputInformation();
+  Superclass::GenerateOutputInformation();
     this->GetOutput()->SetNumberOfComponentsPerPixel( m_Model->GetDimension() );
 }
 
-
-
 template <class TInputImage, class TOutputImage, class TMaskImage>
 void
 ImageDimensionalityReductionFilter<TInputImage, TOutputImage, TMaskImage>
 ::BatchThreadedGenerateData(const OutputImageRegionType& outputRegionForThread, itk::ThreadIdType threadId)
 {
-
   // Get the input pointers
   InputImageConstPointerType inputPtr     = this->GetInput();
   MaskImageConstPointerType  inputMaskPtr  = this->GetInputMask();
   OutputImagePointerType     outputPtr    = this->GetOutput();
   ConfidenceImagePointerType confidencePtr = this->GetOutputConfidence();
-  
+
   // Progress reporting
   itk::ProgressReporter progress(this, threadId, outputRegionForThread.GetNumberOfPixels());
 
   // Define iterators
   typedef itk::ImageRegionConstIterator<InputImageType> InputIteratorType;
-  //typedef itk::ImageRegionConstIterator<MaskImageType>  MaskIteratorType;
   typedef itk::ImageRegionIterator<OutputImageType>     OutputIteratorType;
-  //typedef itk::ImageRegionIterator<ConfidenceImageType> ConfidenceMapIteratorType;
 
   InputIteratorType inIt(inputPtr, outputRegionForThread);
   OutputIteratorType outIt(outputPtr, outputRegionForThread);
@@ -168,45 +157,40 @@ ImageDimensionalityReductionFilter<TInputImage, TOutputImage, TMaskImage>
   typedef typename ModelType::InputListSampleType  InputListSampleType;
   typedef typename ModelType::TargetValueType      TargetValueType;
   typedef typename ModelType::TargetListSampleType TargetListSampleType;
-  
+
   typename InputListSampleType::Pointer samples = InputListSampleType::New();
   unsigned int num_features = inputPtr->GetNumberOfComponentsPerPixel();
   samples->SetMeasurementVectorSize(num_features);
   InputSampleType sample(num_features);
+
   // Fill the samples
-  
   for (inIt.GoToBegin(); !inIt.IsAtEnd(); ++inIt)
     {
-    
-     typename InputImageType::PixelType pix = inIt.Get();
-     for(size_t feat=0; feat<num_features; ++feat)
-        {
-        sample[feat]=pix[feat];
-        }
-      samples->PushBack(sample);
-      
+    typename InputImageType::PixelType pix = inIt.Get();
+    for(size_t feat=0; feat<num_features; ++feat)
+      {
+      sample[feat]=pix[feat];
+      }
+    samples->PushBack(sample);
     }
   //Make the batch prediction
   typename TargetListSampleType::Pointer labels;
- 
+
   // This call is threadsafe
   labels = m_Model->PredictBatch(samples);
 
   // Set the output values
- 
   typename TargetListSampleType::ConstIterator labIt = labels->Begin();
- 
   for (outIt.GoToBegin(); !outIt.IsAtEnd(); ++outIt)
     {
-
-	itk::VariableLengthVector<TargetValueType> labelValue;
-  
+    itk::VariableLengthVector<TargetValueType> labelValue;
     labelValue = labIt.GetMeasurementVector();
     ++labIt;    
     outIt.Set(labelValue);
     progress.CompletedPixel();
     }
 }
+
 template <class TInputImage, class TOutputImage, class TMaskImage>
 void
 ImageDimensionalityReductionFilter<TInputImage, TOutputImage, TMaskImage>
@@ -220,8 +204,8 @@ ImageDimensionalityReductionFilter<TInputImage, TOutputImage, TMaskImage>
     {
     this->ClassicThreadedGenerateData(outputRegionForThread, threadId);
     }
-
 }
+
 /**
  * PrintSelf Method
  */
@@ -232,5 +216,6 @@ ImageDimensionalityReductionFilter<TInputImage, TOutputImage, TMaskImage>
 {
   Superclass::PrintSelf(os, indent);
 }
+
 } // End namespace otb
 #endif
-- 
GitLab