/*
 #
 #  File        : STMS_GrayLevelFiltering.cxx
 #                ( C++ example file - STMS )
 #
 #  Description : STMS lib that implements the STMS filter and clustering.
 #                This file is a part of the STMS Library project.
 #                ( https://www.creatis.insa-lyon.fr/site7/fr/realisations )
 #
 #  [1] S. Mure, Grenier, T., Meier, S., Guttmann, R. G., et Benoit-Cattin, H.,
 #       « Unsupervised spatio-temporal filtering of image sequences. A mean-shift specification »,
 #       Pattern Recognition Letters, vol. 68, Part 1, p. 48 - 55, 2015.
 #
 #  Copyright   : Thomas GRENIER - Simon MURE
 #                ( https://www.creatis.insa-lyon.fr/~grenier/ )
 #
 #  License     : CeCILL V2.1
 #                ( http://www.cecill.info/licences/Licence_CeCILL_V2.1-en.txt)
 #
 #  This software is governed by the CeCILL  license under French law and
 #  abiding by the rules of distribution of free software.  You can  use,
 #  modify and/ or redistribute the software under the terms of the CeCILL
 #  license as circulated by CEA, CNRS and INRIA at the following URL
 #  "http://www.cecill.info".
 #
 #  As a counterpart to the access to the source code and  rights to copy,
 #  modify and redistribute granted by the license, users are provided only
 #  with a limited warranty  and the software's author,  the holder of the
 #  economic rights,  and the successive licensors  have only  limited
 #  liability.
 #
 #  In this respect, the user's attention is drawn to the risks associated
 #  with loading,  using,  modifying and/or developing or reproducing the
 #  software by the user in light of its specific status of free software,
 #  that may mean  that it is complicated to manipulate,  and  that  also
 #  therefore means  that it is reserved for developers  and  experienced
 #  professionals having in-depth computer knowledge. Users are therefore
 #  encouraged to load and test the software's suitability as regards their
 #  requirements in conditions enabling the security of their systems and/or
 #  data to be ensured and,  more generally, to use and operate it in the
 #  same conditions as regards security.
 #
 #  The fact that you are presently reading this means that you have had
 #  knowledge of the CeCILL license and that you accept its terms.
 #
*/
/* Please don't forget to cite our work :
  @article {MURE-15a,
    title = {Unsupervised spatio-temporal filtering of image sequences. A mean-shift specification},
    journal = {Pattern Recognition Letters},
    volume = {68, Part 1},
    year = {2015},
    pages = {48 - 55},
    issn = {0167-8655},
    doi = {http://dx.doi.org/10.1016/j.patrec.2015.07.021},
    url = {http://www.sciencedirect.com/science/article/pii/S0167865515002305},
    author = {S. Mure and T Grenier and Meier, S. and Guttmann, R.G. and H. Benoit-Cattin}
}
*/
#include <iomanip>
#include <ctime>

#define STMS_NUMBERING_FORM_ONE "0001"

#include "itkImage.h"
#include "itkSTMS_ArgumentsAnalysis.h"
#include "itkSTMS_ImageSequenceToTemporalSet.h"
#include "itkSTMS_TemporalSetToImageSequence.h"
#include "itkSTMS_BlurringSTMS.h"

#include <array>



typedef float PixelType;
typedef unsigned char OutputPixelType2D;
typedef float OutputPixelType3D;


double gettime_hp()
{
    struct timespec timestamp;

    clock_gettime(CLOCK_REALTIME, &timestamp);
    return timestamp.tv_sec * 1000.0 + timestamp.tv_nsec * 1.0e-6;
}

// Only --expDescription and numTimePoints parameter are compulsory.

//--expDescription /run/media/mure/HDD/Recherche/These/CVS/Mure/Dev/Cpp/itkSTMS/Data/P43_Parser.xml --imageDimension 2 --xScale 20 --yScale 20 --rScale 1 --epsilon 0.1 --maxIt 20 --numTimePoints 25 --merge

//--expDescription /run/media/mure/HDD/Recherche/These/CVS/Mure/Dev/Cpp/itkSTMS/Data/L43_3_Parser.xml --imageDimension 3 --xScale 1000 --yScale 1000 --zScale 1000 --rScale 0.75 --epsilon 0.1 --maxIt 50 --numTimePoints 25 --merge
//--expDescription /run/media/mure/HDD/Recherche/These/CVS/Mure/Dev/Cpp/itkSTMS/Data/Simu_Parser.xml --imageDimension 2 --xScale 255 --yScale 255 --rScale 0.4 --epsilon 0.01 --maxIt 50 --numTimePoints 8
//--expDescription /run/media/mure/HDD/Recherche/These/CVS/Mure/Dev/Cpp/itkSTMS/Data/G1_Parser.xml --imageDimension 3 --xScale 1000 --yScale 1000 --zScale 1000 --rScale 0.15 --epsilon 0.01 --maxIt 50 --numTimePoints 8

// --expDescription E:/Documents/Creatis/Projets/15_MUST/Data_Cardiac/Parser_AIF_Cardiac.xml --imageDimension 2 --xScale 10 --yScale 10 --rScale 10 --numTimePoints 80

int main(int argc, char **argv){
    double dtime;

    std::cout << "The Numbering form is set to numbers like = " << STMS_NUMBERING_FORM_ONE << std::endl;
    std::cout << "size : " << sizeof(STMS_NUMBERING_FORM_ONE) << std::endl;


    itkSTMS::itkSTMS_ArgumentsAnalysis* argsAnalysis
            = new itkSTMS::itkSTMS_ArgumentsAnalysis(argc, argv);
    argsAnalysis->Update();

    itkSTMS::ParamsAnalysisOutputType* params
            = argsAnalysis->GetSTMSParams();


    switch(params->dim){
        case 2:
        {
            typedef itk::Image< PixelType, 2 >          ImageType2D;
            typedef itk::Image< OutputPixelType2D, 2 >  OutputImageType2D;
            typedef itk::Image< unsigned char, 2 >      MaskImageType2D;


            typedef itkSTMS::itkSTMS_ImageSequenceToTemporalSet< ImageType2D, MaskImageType2D >::IndexType            IndexType;
            typedef itkSTMS::itkSTMS_ImageSequenceToTemporalSet< ImageType2D, MaskImageType2D >::SpatialType          SpatialType;
            typedef itkSTMS::itkSTMS_ImageSequenceToTemporalSet< ImageType2D, MaskImageType2D >::IndexSampleSetType   IndexSampleSetType;
            typedef itkSTMS::itkSTMS_ImageSequenceToTemporalSet< ImageType2D, MaskImageType2D >::SpatialSampleSetType SpatialSampleSetType;
            typedef itkSTMS::itkSTMS_ImageSequenceToTemporalSet< ImageType2D, MaskImageType2D >::RangeSampleSetType   RangeSampleSetType;

            typedef itk::Image< IndexType, 2 >  ClassImageType2D;


            dtime=gettime_hp();

            itkSTMS::itkSTMS_ImageSequenceToTemporalSet< ImageType2D, MaskImageType2D >* preProcess
                    = new itkSTMS::itkSTMS_ImageSequenceToTemporalSet< ImageType2D, MaskImageType2D > ( params );
            preProcess->GenerateDataSets();

            dtime = gettime_hp()-dtime;
            std::cout<<std::endl<< std::setw(30) << std::left << "Characteristics extraction: " << dtime/1000 << " s" <<std::endl;

            IndexSampleSetType*   indexSet   = preProcess->GetIndexSet();
            IndexSampleSetType*   classSet   = preProcess->GetClassSet();
            IndexSampleSetType*   weightsSet = preProcess->GetWeightsSet();
            SpatialSampleSetType* spatialSet = preProcess->GetSpatialSet();
            RangeSampleSetType*   rangeSet   = preProcess->GetRangeSet();


            dtime=gettime_hp();

            itkSTMS::itkSTMS_BlurringSTMS< IndexType, SpatialType, PixelType, ImageType2D >* stmsFilter
                    = new itkSTMS::itkSTMS_BlurringSTMS< IndexType, SpatialType, PixelType, ImageType2D >
                    (indexSet, classSet, weightsSet, spatialSet, rangeSet,  params, preProcess->GetExperimentDescription());

            stmsFilter->GenerateData();

            dtime = gettime_hp()-dtime;
            std::cout<<std::endl<< std::setw(30) << std::left << "STMS filtering: " << dtime/1000 << " s" <<std::endl;


            dtime=gettime_hp();

            itkSTMS::itkSTMS_TemporalSetToImageSequence< ImageType2D, ClassImageType2D, OutputImageType2D >* postProcess
                    = new itkSTMS::itkSTMS_TemporalSetToImageSequence< ImageType2D, ClassImageType2D, OutputImageType2D>(stmsFilter->GetClassMemory(),
                                                                                                       stmsFilter->GetSpatialMemory(),
                                                                                                       stmsFilter->GetRangeSet(),
                                                                                                       params,
                                                                                                       preProcess->GetExperimentDescription());

            postProcess->GenerateImageSequence();
            if(preProcess->GetExperimentDescription()->outputCSV == "true"  )
                postProcess->GenerateCSVFile();

            dtime = gettime_hp()-dtime;
            std::cout<<std::endl<< std::setw(30) << std::left << "Image sequence saving: " << dtime/1000 << " s" <<std::endl;

            delete argsAnalysis;
            delete preProcess;
            delete stmsFilter;
            delete postProcess;
            break;
        }

        case 3:
        {
            typedef itk::Image< PixelType, 3 >     ImageType3D;
            typedef itk::Image< OutputPixelType3D, 3 >     OutputImageType3D;
            typedef itk::Image< unsigned char, 3 > MaskImageType3D;

            typedef itkSTMS::itkSTMS_ImageSequenceToTemporalSet< ImageType3D, MaskImageType3D >::IndexType            IndexType;
            typedef itkSTMS::itkSTMS_ImageSequenceToTemporalSet< ImageType3D, MaskImageType3D >::SpatialType          SpatialType;
            typedef itkSTMS::itkSTMS_ImageSequenceToTemporalSet< ImageType3D, MaskImageType3D >::IndexSampleSetType   IndexSampleSetType;
            typedef itkSTMS::itkSTMS_ImageSequenceToTemporalSet< ImageType3D, MaskImageType3D >::SpatialSampleSetType SpatialSampleSetType;
            typedef itkSTMS::itkSTMS_ImageSequenceToTemporalSet< ImageType3D, MaskImageType3D >::RangeSampleSetType   RangeSampleSetType;


            dtime=gettime_hp();

            itkSTMS::itkSTMS_ImageSequenceToTemporalSet< ImageType3D, MaskImageType3D >* preProcess
                    = new itkSTMS::itkSTMS_ImageSequenceToTemporalSet< ImageType3D, MaskImageType3D > ( params );
            preProcess->GenerateDataSets();

            dtime = gettime_hp()-dtime;
            std::cout<<std::endl<< std::setw(30) << std::left << "Characteristics extraction: " << dtime/1000 << " s" <<std::endl;

            IndexSampleSetType*   indexSet   = preProcess->GetIndexSet();
            IndexSampleSetType*   classSet   = preProcess->GetClassSet();
            IndexSampleSetType*   weightsSet = preProcess->GetWeightsSet();
            SpatialSampleSetType* spatialSet = preProcess->GetSpatialSet();
            RangeSampleSetType*   rangeSet   = preProcess->GetRangeSet();




            dtime=gettime_hp();

            itkSTMS::itkSTMS_BlurringSTMS< IndexType, SpatialType, PixelType, ImageType3D >* stmsFilter
                    = new itkSTMS::itkSTMS_BlurringSTMS< IndexType, SpatialType, PixelType, ImageType3D >
                    (indexSet, classSet, weightsSet, spatialSet, rangeSet,  params, preProcess->GetExperimentDescription());

            stmsFilter->GenerateData();

            dtime = gettime_hp()-dtime;
            std::cout<<std::endl<< std::setw(30) << std::left << "STMS filtering: " << dtime/1000 << " s" <<std::endl;


            dtime=gettime_hp();

            itkSTMS::itkSTMS_TemporalSetToImageSequence< ImageType3D, MaskImageType3D, OutputImageType3D>* postProcess
                    = new itkSTMS::itkSTMS_TemporalSetToImageSequence< ImageType3D, MaskImageType3D, OutputImageType3D >(stmsFilter->GetClassMemory(),
                                                                                                      stmsFilter->GetSpatialMemory(),
                                                                                                      stmsFilter->GetRangeSet(),
                                                                                                      params,
                                                                                                      preProcess->GetExperimentDescription());

            postProcess->GenerateImageSequence();
            if(preProcess->GetExperimentDescription()->outputCSV == "true"  )
                postProcess->GenerateCSVFile();

            dtime = gettime_hp()-dtime;
            std::cout<<std::endl<< std::setw(30) << std::left << "Image sequence saving: " << dtime/1000 << " s" <<std::endl;


            delete argsAnalysis;
            delete preProcess;
            delete stmsFilter;
            delete postProcess;
            break;
        }

        default:
        {
            delete argsAnalysis;

            std::cout << std::endl << "Image dimensionality should be equal to 2 or 3.";
            std::exit( EXIT_FAILURE );
            break;
        }
    }

    return EXIT_SUCCESS;
}