cbDimensionalityReductionVector.cxx

/*
* Copyright (C) 2005-2017 Centre National d'Etudes Spatiales (CNES)
*
* This file is part of Orfeo Toolbox
*
* https://www.orfeo-toolbox.org/
*
* 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
*
* 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 "otbWrapperApplication.h"
#include "otbWrapperApplicationFactory.h"
#include "otbOGRDataSourceWrapper.h"
#include "otbOGRFeatureWrapper.h"
#include "itkVariableLengthVector.h"
#include "otbStatisticsXMLFileReader.h"
#include "itkListSample.h"
#include "otbShiftScaleSampleListFilter.h"
#include "DimensionalityReductionModelFactory.h"
#include "DimensionalityReductionModel.h"
#include <time.h>
namespace otb
{
namespace Wrapper
{
	
/** Utility function to negate std::isalnum */
/*bool IsNotAlphaNum(char c)
{
return !std::isalnum(c);
}*/
class CbDimensionalityReductionVector : public Application
{
	public:
	
		/** Standard class typedefs. */
		typedef CbDimensionalityReductionVector Self;
		typedef Application Superclass;
		typedef itk::SmartPointer<Self> Pointer;
		typedef itk::SmartPointer<const Self> ConstPointer;
		
		/** Standard macro */
		itkNewMacro(Self);
		itkTypeMacro(Self, Application)
		
		/** Filters typedef */
		
		typedef double ValueType;
		typedef DimensionalityReductionModel<ValueType,ValueType> DimensionalityReductionModelType;
		typedef DimensionalityReductionModelFactory<ValueType, ValueType> DimensionalityReductionModelFactoryType;
		typedef DimensionalityReductionModelType::Pointer ModelPointerType;
		
		/** Statistics Filters typedef */
		typedef itk::VariableLengthVector<ValueType> MeasurementType;
		typedef otb::StatisticsXMLFileReader<MeasurementType> StatisticsReader;
		typedef itk::VariableLengthVector<ValueType> InputSampleType;
		typedef itk::Statistics::ListSample<InputSampleType> ListSampleType;
		typedef otb::Statistics::ShiftScaleSampleListFilter<ListSampleType, ListSampleType> ShiftScaleFilterType;
		~CbDimensionalityReductionVector() ITK_OVERRIDE
		{
		DimensionalityReductionModelFactoryType::CleanFactories();
		}
		
	private:
	
		void DoInit() ITK_OVERRIDE
		{
		SetName("VectorDimensionalityReduction");
		SetDescription("Performs dimensionality reduction of the input vector data according to a model file.");
		SetDocName("Vector Dimensionality Reduction");
		SetDocAuthors("OTB-Team");
		SetDocLongDescription("This application performs a vector data dimensionality reduction based on a model file produced by the cbDimensionalityReductionTrainer application.");
		SetDocSeeAlso("cbDimensionalityReductionTrainer");
		AddDocTag(Tags::Learning);
		
		AddParameter(ParameterType_InputVectorData, "in", "Name of the input vector data");
		SetParameterDescription("in","The input vector data to reduce.");
		
		AddParameter(ParameterType_InputFilename, "instat", "Statistics file");
		SetParameterDescription("instat", "A XML file containing mean and standard deviation to center"
		"and reduce samples before dimensionality reduction (produced by ComputeImagesStatistics application).");
		MandatoryOff("instat");
		
		AddParameter(ParameterType_InputFilename, "model", "Model file");
		SetParameterDescription("model", "A model file (produced by cbDimensionalityReduction application,");
		
		AddParameter(ParameterType_ListView, "feat", "Field names to be calculated."); //
		SetParameterDescription("feat","List of field names in the input vector data used as features for training."); //
		
		AddParameter(ParameterType_ListView, "feat_out", "Field names to be calculated."); //
		SetParameterDescription("feat_out","List of field names in the input vector data used as features for training."); //
		
		AddParameter(ParameterType_OutputFilename, "out", "Output vector data file containing the reduced vector");
		SetParameterDescription("out","Output vector data file storing sample values (OGR format)."
		"If not given, the input vector data file is updated.");
		MandatoryOff("out");
		
		// Doc example parameter settings
		SetDocExampleParameterValue("in", "vectorData.shp");
		SetDocExampleParameterValue("instat", "meanVar.xml");
		SetDocExampleParameterValue("model", "model.txt");
		SetDocExampleParameterValue("out", "vectorDataOut.shp");
		SetDocExampleParameterValue("feat", "perimeter area width");
		SetDocExampleParameterValue("feat_out", "perimeter area width");
		//SetOfficialDocLink(); 
		}
		
		void DoUpdateParameters() ITK_OVERRIDE
		{
		/** I don't know what this does */
		/*
		if ( HasValue("in") )
		{
		std::string shapefile = GetParameterString("in");
		otb::ogr::DataSource::Pointer ogrDS;
		OGRSpatialReference oSRS("");
		std::vector<std::string> options;
		ogrDS = otb::ogr::DataSource::New(shapefile, otb::ogr::DataSource::Modes::Read);
		otb::ogr::Layer layer = ogrDS->GetLayer(0);
		OGRFeatureDefn &layerDefn = layer.GetLayerDefn();
		ClearChoices("feat");
		
		for(int iField=0; iField< layerDefn.GetFieldCount(); iField++)
		{
		std::string item = layerDefn.GetFieldDefn(iField)->GetNameRef();
		std::string key(item);
		key.erase( std::remove_if(key.begin(),key.end(),IsNotAlphaNum), key.end());
		std::transform(key.begin(), key.end(), key.begin(), tolower);
		OGRFieldType fieldType = layerDefn.GetFieldDefn(iField)->GetType();
		
		if(fieldType == OFTInteger || ogr::version_proxy::IsOFTInteger64(fieldType) || fieldType == OFTReal)
		{
		std::string tmpKey="feat."+key;
		AddChoice(tmpKey,item);
		}
		}
		}*/
		}
		
		void DoExecute() ITK_OVERRIDE
		{
			clock_t tic = clock();
			
			std::string shapefile = GetParameterString("in");
			otb::ogr::DataSource::Pointer source = otb::ogr::DataSource::New(shapefile, otb::ogr::DataSource::Modes::Read);
			otb::ogr::Layer layer = source->GetLayer(0);
			ListSampleType::Pointer input = ListSampleType::New();
			const int nbFeatures = GetSelectedItems("feat").size();
			input->SetMeasurementVectorSize(nbFeatures);
			otb::ogr::Layer::const_iterator it = layer.cbegin();
			otb::ogr::Layer::const_iterator itEnd = layer.cend();
			
			for( ; it!=itEnd ; ++it)
			{
				MeasurementType mv;
				mv.SetSize(nbFeatures);
				for(int idx=0; idx < nbFeatures; ++idx)
				{
					mv[idx] = (*it)[GetSelectedItems("feat")[idx]].GetValue<double>();
				}
				input->PushBack(mv);
			}
			
			/** Statistics for shift/scale */
			
			MeasurementType meanMeasurementVector;
			MeasurementType stddevMeasurementVector;
			
			if (HasValue("instat") && IsParameterEnabled("instat"))
			{
				StatisticsReader::Pointer statisticsReader = StatisticsReader::New();
				std::string XMLfile = GetParameterString("instat");
				statisticsReader->SetFileName(XMLfile);
				meanMeasurementVector = statisticsReader->GetStatisticVectorByName("mean");
				stddevMeasurementVector = statisticsReader->GetStatisticVectorByName("stddev");
			}
			else
			{
				meanMeasurementVector.SetSize(nbFeatures);
				meanMeasurementVector.Fill(0.);
				stddevMeasurementVector.SetSize(nbFeatures);
				stddevMeasurementVector.Fill(1.);
			}
			
			ShiftScaleFilterType::Pointer trainingShiftScaleFilter = ShiftScaleFilterType::New();
			trainingShiftScaleFilter->SetInput(input);
			trainingShiftScaleFilter->SetShifts(meanMeasurementVector);
			trainingShiftScaleFilter->SetScales(stddevMeasurementVector);
			trainingShiftScaleFilter->Update();
			otbAppLogINFO("mean used: " << meanMeasurementVector);
			otbAppLogINFO("standard deviation used: " << stddevMeasurementVector);
			otbAppLogINFO("Loading model");
			
			
			/** Read the model */
			
			m_Model = DimensionalityReductionModelFactoryType::CreateDimensionalityReductionModel(GetParameterString("model"),
			DimensionalityReductionModelFactoryType::ReadMode);
			if (m_Model.IsNull())
			{
				otbAppLogFATAL(<< "Error when loading model " << GetParameterString("model") << " : unsupported model type");
			}
			m_Model->Load(GetParameterString("model"));
			otbAppLogINFO("Model loaded");
			
			/** Perform Dimensionality Reduction */
			
			ListSampleType::Pointer listSample = trainingShiftScaleFilter->GetOutput();
			ListSampleType::Pointer target;
			target = m_Model->PredictBatch(listSample);
			
			
			/** Create/Update Output Shape file */
			
			ogr::DataSource::Pointer output;
			ogr::DataSource::Pointer buffer = ogr::DataSource::New();
			bool updateMode = false;
			if (IsParameterEnabled("out") && HasValue("out"))
			{
				// Create new OGRDataSource
				output = ogr::DataSource::New(GetParameterString("out"), ogr::DataSource::Modes::Overwrite);
				otb::ogr::Layer newLayer = output->CreateLayer(
				GetParameterString("out"),
				const_cast<OGRSpatialReference*>(layer.GetSpatialRef()),
				layer.GetGeomType());
				// Copy existing fields
				OGRFeatureDefn &inLayerDefn = layer.GetLayerDefn();
				for (int k=0 ; k<inLayerDefn.GetFieldCount() ; k++)
				{
				OGRFieldDefn fieldDefn(inLayerDefn.GetFieldDefn(k));
				newLayer.CreateField(fieldDefn);
				}
			}
			else
			{
				// Update mode
				updateMode = true;
				otbAppLogINFO("Update input vector data.");
				// fill temporary buffer for the transfer
				otb::ogr::Layer inputLayer = layer;
				layer = buffer->CopyLayer(inputLayer, std::string("Buffer"));
				// close input data source
				source->Clear();
				// Re-open input data source in update mode
				output = otb::ogr::DataSource::New(shapefile, otb::ogr::DataSource::Modes::Update_LayerUpdate);
			}
			
			otb::ogr::Layer outLayer = output->GetLayer(0);
			OGRErr errStart = outLayer.ogr().StartTransaction();
			
			if (errStart != OGRERR_NONE)
			{
				itkExceptionMacro(<< "Unable to start transaction for OGR layer " << outLayer.ogr().GetName() << ".");
			}
			
			// Add the field of prediction in the output layer if field not exist
			
			OGRFeatureDefn &layerDefn = layer.GetLayerDefn();
			int idx = layerDefn.GetFieldIndex(GetParameterString("feat_out").c_str());
			
			if (idx >= 0)
			{
				if (layerDefn.GetFieldDefn(idx)->GetType() != OFTInteger)
				itkExceptionMacro("Field name "<< GetParameterString("feat_out") << " already exists with a different type!");
			}
			else
			{
				OGRFieldDefn predictedField(GetParameterString("feat_out").c_str(), OFTInteger);
				ogr::FieldDefn predictedFieldDef(predictedField);
				outLayer.CreateField(predictedFieldDef);
			}
			
			// Fill output layer
			
			unsigned int count=0;
			std::string classfieldname = GetParameterString("feat_out");
			it = layer.cbegin();
			itEnd = layer.cend();
			for( ; it!=itEnd ; ++it, ++count)
			{
				ogr::Feature dstFeature(outLayer.GetLayerDefn());
				dstFeature.SetFrom( *it , TRUE);
				dstFeature.SetFID(it->GetFID());
				dstFeature[classfieldname].SetValue<int>(target->GetMeasurementVector(count)[0]);
				
				if (updateMode)
				{
					outLayer.SetFeature(dstFeature);
				}
				else
				{
					outLayer.CreateFeature(dstFeature);
				}
			}
			if(outLayer.ogr().TestCapability("Transactions"))
			{
				const OGRErr errCommitX = outLayer.ogr().CommitTransaction();
				if (errCommitX != OGRERR_NONE)
				{
					itkExceptionMacro(<< "Unable to commit transaction for OGR layer " << outLayer.ogr().GetName() << ".");
				}
			}
			output->SyncToDisk();
			clock_t toc = clock();
			otbAppLogINFO( "Elapsed: "<< ((double)(toc - tic) / CLOCKS_PER_SEC)<<" seconds.");
		}
		
		ModelPointerType m_Model;
};
}
}
OTB_APPLICATION_EXPORT(otb::Wrapper::CbDimensionalityReductionVector)