// Utilisation de SOPHYA pour faciliter les tests ...
#include "sopnamsp.h"
#include "machdefs.h"

/* ---------------------------------------------------------- 
   Projet BAORadio/PAON4 - (C) LAL/IRFU  2017

   visiavg: programme de lecture des fichiers matrices de 
   visibilites de PAON4, calcul de visibilities moyennes 
    en bin de temps et de frequence
   O. Perdereau, R.Ansari   -  LAL
   ---------------------------------------------------------- */

// include standard c/c++
#include <math.h>
#include <stdio.h>
#include <stdlib.h>
#include <string.h>

#include <iostream>
#include <string>

#include "pexceptions.h"
#include "tvector.h"
#include "fioarr.h"
// #include "tarrinit.h"
#include "ntuple.h" 
#include "datatable.h" 
#include "histinit.h" 
#include "matharr.h" 
#include "timestamp.h"
#include <utilarr.h>

// include sophya mesure ressource CPU/memoire ...
#include "resusage.h"
#include "ctimer.h"
#include "timing.h"

// include lecteur de fichiers visibilites 
#include "visp4winreader.h"

#include "fitsioserver.h"
#include "fiosinit.h"

int Usage(void);
int Usage(void)
{
  cout << " --- visiavg.cc : Read PPF files produced by mfacq time-frequency\n" << endl;
  cout << " Usage: visiavg [-arguments] \n" << endl;
  P4AnaParams::UsageOptions();
  cout<< endl;
  return 1;
}

//----------------------------------------------------
int main(int narg, const char* arg[])
{
  // --- Decoding parameters 
  if( (narg<2) || ((narg>1)&&(strcmp(arg[1],"-h")==0) ) )  return Usage();
  FitsIOServerInit();
  P4AnaParams params;
  params.DecodeArgs(narg, arg);

  string outfile = params.outfile_;
  if (outfile.length()<1)  outfile = "visavg.ppf";

  string fitsoutfile = params.fitsoutfile_;
  if (fitsoutfile.length()>=1) {
    fitsoutfile = "!"+fitsoutfile ; // adds '!' ?
  }

  int deltaIavg = params.TFMtimebin_;
  sa_size_t TFMfbin = params.TFMfreqbin_;
  int prtlev = params.prtlev_;
  bool FgTFMAC = true;
  bool FgTFMCX = true;
  string desctfmap;
  bool FgTFM = params.fgTFM_;   // true -> create time-frequency maps

  params.Print(cout);
  cout <<"visiavg/Info: Path BAO5:"<<params.inpath5_<<" BAO6:"<<params.inpath6_<<"\n"
       <<"fgreorderfreq="<<params.fgreorderfreq_<<"\n"
       <<" DeltaIAvg="<<deltaIavg<<"\n"
       <<"outfile="<<outfile<<" PrtLev="<<prtlev<<endl;

  if (!FgTFM) {
    cout<<" visiavg/parameter error : specify Time-Frequency map parameter with -tfm "<<endl;
    return 5;
  }

  P4AVisiNumEncoder  visiencod;
  vector<sa_size_t> KVAC = visiencod.getAllAutoCor();
  vector<sa_size_t> KVCXHH = visiencod.getAllHCrossCor();
  vector<sa_size_t> KVCXVV = visiencod.getAllVCrossCor();
  vector<sa_size_t> KVCXHV = visiencod.getAllHVCrossCor();

  
  cout << " List of AutoCorrelation rows:"<<endl;
  for(size_t k=0; k<KVAC.size(); k++) {
    cout << "KVAC["<<k<<"]="<<KVAC[k]<<"  ->"<<visiencod.Convert2VisiName(KVAC[k])<<endl;
  }

  cout << " List of HH X-cor rows:"<<endl;
  for(size_t k=0; k<KVCXHH.size(); k++) {
    cout << "KVCXHH["<<k<<"]="<<KVCXHH[k]<<"  ->"<<visiencod.Convert2VisiName(KVCXHH[k])<<endl;
  }


  // ---
  HiStatsInitiator _inia;
  int rc = 0;

  try {
    ResourceUsage resu;


    VisiP4WindowReader wreader(params);

    long Imin = wreader.getReader().getSerialFirst();
    long Imax =  wreader.getReader().getSerialLast();
    long Istep =  wreader.getReader().getSerialStep();
    cout << "visiavg/Info: processing visibility matrix serial/sequence number range "
	 <<Imin<<" <= seq <= " << Imax << " with step="<<Istep<<endl;
    cout << " WindowSize="<<wreader.getWindowSize()<<"  -> TotalNbWindows="<<wreader.getTotalNbWindows()<<endl;

    bool fgok=true;
    // vecteur de noms 
    vector <string> ext_names;
    // un vecteur avec les temps 
    TVector< double > timevec(wreader.getTotalNbWindows()/deltaIavg); 
    TVector< double > ravec(wreader.getTotalNbWindows()/deltaIavg); 
    TMatrix< complex<r_4> > vismtx;
    TMatrix< complex<r_4> > acsum;
    TMatrix< r_4 > acsum_sq; // wil sum only the real part ^2

    TMatrix< complex<r_4> > cxsum;
    // for sums of real and imag parts 
    TMatrix< r_4 > cxsum_sq_rp;
    TMatrix< r_4 > cxsum_sq_ip;

    // for VV if needed
    TMatrix< complex<r_4> > cxsum_vv;
    // for sums of real and imag parts 
    TMatrix< r_4 > cxsum_vv_sq_rp;
    TMatrix< r_4 > cxsum_vv_sq_ip;

    // for HV if needed
    TMatrix< complex<r_4> > cxsum_hv;
    // for sums of real and imag parts 
    TMatrix< r_4 > cxsum_hv_sq_rp;
    TMatrix< r_4 > cxsum_hv_sq_ip;

    TimeStamp dateobs, cfdate,datestart;
    TimeStamp dateorg(2015,1,1,12,0,0.);  // Date origine 1 jan 2015
    double mttag;
    int cnt=0, cntnt=0, pcntnt=0;
    int I=0; 
    // for

    //----- 6 H-H cross-cor TimeFrequency maps 
    vector< TArray< complex<r_4> > > vtfm;
    //----- 6 H-H cross-cor TimeFrequency maps for the variances of real and imag parts 
    vector< TArray< r_4 > > vtfm_rp_sq;
    vector< TArray< r_4 > > vtfm_ip_sq;

    //----- 6 V-V cross-cor TimeFrequency maps 
    vector< TArray< complex<r_4> > > vtfm_vv;
    //----- 6 V-V cross-cor TimeFrequency maps for the variances of real and imag parts 
    vector< TArray< r_4 > > vtfm_vv_rp_sq;
    vector< TArray< r_4 > > vtfm_vv_ip_sq;

    //----- 16 H-V cross-cor TimeFrequency maps 
    vector< TArray< complex<r_4> > > vtfm_hv;
    //----- 16 H-V cross-cor TimeFrequency maps for the variances of real and imag parts 
    vector< TArray< r_4 > > vtfm_hv_rp_sq;
    vector< TArray< r_4 > > vtfm_hv_ip_sq;

    //----- 8 auto-corr TimeFrequency maps 
    vector< TArray< r_4 > > vtfmac;
    //----- 8 auto-corr TimeFrequency variance maps 
    vector< TArray< r_4 > > vtfmac_sq;
    
    //---- for the time-freqency map filling    
    sa_size_t TFMtmidx=0;
    sa_size_t tfmSX, tfmSY;

    while (fgok) {
      //reads next visibility matrix window 
      fgok = wreader.Shift();
      
      if (!fgok)  break;
     
      vismtx = wreader.getAverageVisMtx(cfdate);
      
      if (cnt==0)  {    //resizing matrices for sum of auto-correlations and sum of 6 cross-correlations 

	acsum.SetSize(8, vismtx.NCols());
	if (params.doSigma_)   // for computing Sigma, if required 
	  acsum_sq.SetSize(8, vismtx.NCols());

	cxsum.SetSize(6, vismtx.NCols());
	if (params.doSigma_) {   // for computing Sigma, if required 
	  cxsum_sq_rp.SetSize(6, vismtx.NCols());
	  cxsum_sq_ip.SetSize(6, vismtx.NCols());
	}
	// VV if needed 
	if (params.doVV_){
	  cxsum_vv.SetSize(6, vismtx.NCols());
	  if (params.doSigma_) {   // for computing Sigma, if required 
	    cxsum_vv_sq_rp.SetSize(6, vismtx.NCols());
	    cxsum_vv_sq_ip.SetSize(6, vismtx.NCols());
	  }
	}

	// HV if needed 
	if (params.doHV_){
	  cxsum_hv.SetSize(16, vismtx.NCols());
	  if (params.doSigma_) {   // for computing Sigma, if required 
	    cxsum_hv_sq_rp.SetSize(16, vismtx.NCols());
	    cxsum_hv_sq_ip.SetSize(16, vismtx.NCols());
	  }
	}


	tfmSX=wreader.getTotalNbWindows()/deltaIavg;
	tfmSY=vismtx.NCols()/TFMfbin;
	//allocating 8 Auto-Corr time-frequency maps 
	cout<<"visiavg/Info: allocating 8 AutoCor Time-Frequency maps : Time->NX="<<tfmSX<<" x Freq->NY="<<tfmSY<<endl;
	for(int k=0; k<8; k++) vtfmac.push_back( TArray< r_4 >(tfmSX, tfmSY) );
	if (params.doSigma_) {   // for computing Sigma, if required 
	  cout <<" and 8 for the the variance maps "<<endl;
	  for(int k=0; k<8; k++) vtfmac_sq.push_back( TArray< r_4 >(tfmSX, tfmSY) ); 
	}
	//allocating 6 Cross-Corr H-H time-frequency maps 
	cout<<"visiavg/Info: allocating H-H cross-cor Time-Frequency maps : Time->NX="<<tfmSX<<" x Freq->NY="<<tfmSY<<endl;
	for(int k=0; k<6; k++) vtfm.push_back( TArray< complex<r_4> >(tfmSX, tfmSY) );
	if (params.doSigma_) {   // for computing Sigma, if required 
	  cout << "and the 2x6 for squares of real & imaginary parts " << endl;
	  for(int k=0; k<6; k++) vtfm_rp_sq.push_back( TArray< r_4 >(tfmSX, tfmSY) );
	  for(int k=0; k<6; k++) vtfm_ip_sq.push_back( TArray< r_4 >(tfmSX, tfmSY) );
	}
	// VV if needed 
	if (params.doVV_){
	  //allocating 6 Cross-Corr V-V time-frequency maps 
	  cout<<"visiavg/Info: allocating V-V cross-cor Time-Frequency maps : Time->NX="<<tfmSX<<" x Freq->NY="<<tfmSY<<endl;
	  for(int k=0; k<6; k++) vtfm_vv.push_back( TArray< complex<r_4> >(tfmSX, tfmSY) );
	  if (params.doSigma_) {   // for computing Sigma, if required 
	    cout << "and the 2x6 for squares of real & imaginary parts " << endl;
	    for(int k=0; k<6; k++) vtfm_vv_rp_sq.push_back( TArray< r_4 >(tfmSX, tfmSY) );
	    for(int k=0; k<6; k++) vtfm_vv_ip_sq.push_back( TArray< r_4 >(tfmSX, tfmSY) );
	  }
	}

	// HV if needed 
	if (params.doHV_){
	  //allocating 16 Cross-Corr H-V time-frequency maps 
	  cout<<"visiavg/Info: allocating 16 H-V cross-cor Time-Frequency maps : Time->NX="<<tfmSX<<" x Freq->NY="<<tfmSY<<endl;
	  for(int k=0; k<16; k++) vtfm_hv.push_back( TArray< complex<r_4> >(tfmSX, tfmSY) );
	  if (params.doSigma_) {   // for computing Sigma, if required 
	    cout << "and the 2x16 for squares of real & imaginary parts " << endl;
	    for(int k=0; k<16; k++) vtfm_hv_rp_sq.push_back( TArray< r_4 >(tfmSX, tfmSY) );
	    for(int k=0; k<16; k++) vtfm_hv_ip_sq.push_back( TArray< r_4 >(tfmSX, tfmSY) );
	  }
	}


	// recupere le jour de depart @ 0h
	datestart = TimeStamp(cfdate.DaysPart(),0.);
 
      } // end if cnt==0

      if (I==0) {   // start filling a new time bin 
	dateobs=cfdate;
	if (prtlev>0) 
	  cout<<"visiavg/Info:  dateobs="<<dateobs<<" SecondsPart()="<<dateobs.SecondsPart()<<endl;
	acsum = complex<r_4>(0.,0.);
	cxsum = complex<r_4>(0.,0.);
	if (params.doSigma_) {   // for computing Sigma, if required 
	  acsum_sq = 0.;
	  cxsum_sq_rp = 0.;
	  cxsum_sq_ip = 0.;
	}
	// VV if needed 
	if (params.doVV_){
	  cxsum_vv = complex<r_4>(0.,0.);
	  if (params.doSigma_) {   // for computing Sigma, if required 
	    cxsum_vv_sq_rp = 0.;
	    cxsum_vv_sq_ip = 0.;
	  }
	}

	// HV if needed 
	if (params.doHV_){
	  cxsum_hv = complex<r_4>(0.,0.);
	  if (params.doSigma_) {   // for computing Sigma, if required 
	    cxsum_hv_sq_rp = 0.;
	    cxsum_hv_sq_ip = 0.;
	  }
	}
      }
      
      //   sum (integration) along the time axis 
      for(size_t k=0; k<KVAC.size(); k++)      acsum.Row(k) += vismtx.Row(KVAC[k]);     // Les auto-correlations 
      if (params.doSigma_) {   // for computing Sigma, if required 
	for(size_t k=0; k<KVAC.size(); k++)      {
	  TVector<r_4> tmp = real(vismtx.Row(KVAC[k]));
	  acsum_sq.Row(k) += tmp.MulElt(tmp,tmp) ;
	}
      }

      for(size_t k=0; k<KVCXHH.size(); k++){
	cxsum.Row(k) += vismtx.Row(KVCXHH[k]);   // les cross-correlations 
	if (params.doSigma_) {   // for computing Sigma, if required 
	  TVector<r_4> tmp = real(vismtx.Row(KVCXHH[k]));
	  cxsum_sq_rp.Row(k) +=  tmp.MulElt(tmp,tmp) ;
	  tmp = imag(vismtx.Row(KVCXHH[k]));
	  cxsum_sq_ip.Row(k) +=  tmp.MulElt(tmp,tmp) ;
	}
      }
      
      if (params.doVV_){
	for(size_t k=0; k<KVCXVV.size(); k++){
	  cxsum_vv.Row(k) += vismtx.Row(KVCXVV[k]);   // les cross-correlations 
	  if (params.doSigma_) {   // for computing Sigma, if required 
	    TVector<r_4> tmp = real(vismtx.Row(KVCXVV[k]));
	    cxsum_vv_sq_rp.Row(k) +=  tmp.MulElt(tmp,tmp) ;
	    tmp = imag(vismtx.Row(KVCXVV[k]));
	    cxsum_vv_sq_ip.Row(k) +=  tmp.MulElt(tmp,tmp) ;
	  }
	}
      }

      if (params.doHV_){
	for(size_t k=0; k<KVCXHV.size(); k++){
	  cxsum_hv.Row(k) += vismtx.Row(KVCXHV[k]);   // les cross-correlations HV
	  if (params.doSigma_) {   // for computing Sigma, if required 
	    TVector<r_4> tmp = real(vismtx.Row(KVCXHV[k]));
	    cxsum_hv_sq_rp.Row(k) +=  tmp.MulElt(tmp,tmp) ; 
	    tmp = imag(vismtx.Row(KVCXHV[k]));
	    cxsum_hv_sq_ip.Row(k) +=  tmp.MulElt(tmp,tmp) ;
	  }
	}
      }



      I++;    // incrementing DeltaTime counter 
      // we check that our time index did not go beyond the allocated array size (might not be necessary)
      if ((I==deltaIavg)&&(TFMtmidx>=tfmSX)) {  // Cela ne devrait pas arriver en principe 
	TFMtmidx++;	I=0;  
	cout << "visiavg/Warning: something wrong in the logic , (TFMtmidx="<<TFMtmidx<<") >= (tfmSX="<<tfmSX<<")"
	     << " for read count="<<cnt<<endl; 
      }
      else if (I==deltaIavg) {   // Filling TFM maps 
	//---- On s'occupe d'abord des autocorrelations P1 ... P8 
	for(size_t k=0; k<KVAC.size(); k++) {  // Loop over the 8 auto-correlations 
	  TVector<r_4> vac = real(acsum.Row(k));
	  TArray< r_4 > & tfmap = vtfmac[k];
	  for(sa_size_t jy=0; jy<tfmSY; jy++) {  // frequency binning 
	    tfmap(TFMtmidx, jy) = vac( Range(jy*TFMfbin, (jy+1)*TFMfbin-1) ).Sum();
	  }
	  if (params.doSigma_) {   // for computing Sigma, if required 
	    TVector<r_4> vacsq = acsum_sq.Row(k);
	    TArray< r_4 > & tfmap_sq = vtfmac_sq[k];
	    for(sa_size_t jy=0; jy<tfmSY; jy++) {  // frequency binning 
	      tfmap_sq(TFMtmidx, jy) = vacsq( Range(jy*TFMfbin, (jy+1)*TFMfbin-1) ).Sum();
	    }
	  }  //-- end of computing sigmas   
	}  //----- end of loop over the 8 AutoCor

	//---- On s'occupe des 6 cross-correlations  1H-2H ... 3H-4H 
 	for(size_t k=0; k<KVCXHH.size(); k++)   {   // loop over the 6 Xcor 	  
	  TVector< complex<r_4> > vcx = cxsum.Row(k);
	  TArray< complex<r_4> > & tfmap = vtfm[k];
	  for(sa_size_t jy=0; jy<tfmSY; jy++) {
	    tfmap(TFMtmidx, jy) = vcx( Range(jy*TFMfbin, (jy+1)*TFMfbin-1) ).Sum();
	  } 
	  if (params.doSigma_) {   // for computing Sigma, if required 
	    TVector<r_4>  vcxprsq = cxsum_sq_rp.Row(k);
	    TVector<r_4>  vcxpisq = cxsum_sq_ip.Row(k);
	    TArray< r_4 > & tfmapsqpr = vtfm_rp_sq[k];
	    TArray< r_4 > & tfmapsqpi = vtfm_ip_sq[k];
	    for(sa_size_t jy=0; jy<tfmSY; jy++) {
	      tfmapsqpr(TFMtmidx, jy) = vcxprsq( Range(jy*TFMfbin, (jy+1)*TFMfbin-1) ).Sum();
	      tfmapsqpi(TFMtmidx, jy) = vcxpisq( Range(jy*TFMfbin, (jy+1)*TFMfbin-1) ).Sum();
	    } 
	  }    //-- end of computing sigmas  
	}  //----- end of loop over the 6 Xcor 

	if (params.doVV_){ // Option VV 
	  //---- On s'occupe des 6 cross-correlations  1V-2V ... 3V-4V 
	  for(size_t k=0; k<KVCXVV.size(); k++)   {   // loop over the 6 Xcor 	  
	    TVector< complex<r_4> > vcx = cxsum_vv.Row(k);
	    TArray< complex<r_4> > & tfmap = vtfm_vv[k];
	    for(sa_size_t jy=0; jy<tfmSY; jy++) {
	      tfmap(TFMtmidx, jy) = vcx( Range(jy*TFMfbin, (jy+1)*TFMfbin-1) ).Sum();
	    }
	    if (params.doSigma_) {   // for computing Sigma, if required 
	      TVector<r_4>  vcxprsq = cxsum_vv_sq_rp.Row(k);
	      TVector<r_4>  vcxpisq = cxsum_vv_sq_ip.Row(k);
	      TArray< r_4 > & tfmapsqpr = vtfm_vv_rp_sq[k];
	      TArray< r_4 > & tfmapsqpi = vtfm_vv_ip_sq[k];
	      for(sa_size_t jy=0; jy<tfmSY; jy++) {
		tfmapsqpr(TFMtmidx, jy) = vcxprsq( Range(jy*TFMfbin, (jy+1)*TFMfbin-1) ).Sum();
		tfmapsqpi(TFMtmidx, jy) = vcxpisq( Range(jy*TFMfbin, (jy+1)*TFMfbin-1) ).Sum();
	      }
	    } //-- end of computing sigmas  
	  }  //----- end of loop over the 6 Xcor VV
	} // end VV option 

	if (params.doHV_){ // Option HV 
	  //---- On s'occupe des 16 cross-correlations  1H-1V ... 4H-4V 
	  for(size_t k=0; k<KVCXHV.size(); k++)   {   // loop over the 16 Xcor 	  
	    TVector< complex<r_4> > vcx = cxsum_hv.Row(k);
	    TArray< complex<r_4> > & tfmap = vtfm_hv[k];
	    for(sa_size_t jy=0; jy<tfmSY; jy++) {
	      tfmap(TFMtmidx, jy) = vcx( Range(jy*TFMfbin, (jy+1)*TFMfbin-1) ).Sum();
	    } 
	    if (params.doSigma_) {   // for computing Sigma, if required 
	      TVector<r_4>  vcxprsq = cxsum_hv_sq_rp.Row(k);
	      TVector<r_4>  vcxpisq = cxsum_hv_sq_ip.Row(k);
	      TArray< r_4 > & tfmapsqpr = vtfm_hv_rp_sq[k];
	      TArray< r_4 > & tfmapsqpi = vtfm_hv_ip_sq[k];
	      for(sa_size_t jy=0; jy<tfmSY; jy++) {
		tfmapsqpr(TFMtmidx, jy) = vcxprsq( Range(jy*TFMfbin, (jy+1)*TFMfbin-1) ).Sum();
		tfmapsqpi(TFMtmidx, jy) = vcxpisq( Range(jy*TFMfbin, (jy+1)*TFMfbin-1) ).Sum();
	      } 
	    } //-- end of computing sigmas  
	  }  //----- end of loop over the 16 Xcor HV
	} // end HV option 

	double tdif =  cfdate.TimeDifferenceSeconds(cfdate,dateobs)/2.;
	timevec(TFMtmidx) = dateobs.TimeDifferenceSeconds(dateobs.ShiftSeconds (tdif ),datestart);	// centre du bin 
	ravec(TFMtmidx) = P4Coords::RAFromTimeTU(dateobs.ShiftSeconds (tdif ));
	TFMtmidx++;
	//  ... done 
	I=0;  cntnt++;
      }
      cnt++;
      if ((cnt>0)&&(cntnt%10==0)&&(cntnt>pcntnt)) {
	cout<<"visiavg/Info: TFM-Map fill cnt="<<cntnt<<" VisMtxCount="<<cnt
	    <<" /Max="<<wreader.getTotalNbWindows()<<" DateObs="<<dateobs<<endl;
	pcntnt=cntnt;
      }
    }
    cout<<"visiavg/Info: count="<<cnt*wreader.getWindowSize()<<" Visibility Matrices read "<<endl;

    // --- Sauvegarde cartes temps-frequence en fits 

    FitsInOutFile  * fos = NULL ;

    if (fitsoutfile.length()>=1){
      cout << " fitsoutfile :" <<fitsoutfile<<":"<< endl;
      fos = new FitsInOutFile(fitsoutfile, FitsInOutFile::Fits_Create);
    }
    

    POutPersist potfm(outfile);
    char bufnam[10];
    int numkey =0;
    // --- renormalizing and saving AutoCorr time-frequency maps 
    cout<<"  visiavg/Info: Saving 8 AutoCorr time-frequency maps to PPF file "<<outfile<<endl;
    const char* tfm_names[8]={"TFM_1H", "TFM_2H", "TFM_3H", "TFM_4H", "TFM_1V", "TFM_2V", "TFM_3V", "TFM_4V"};
    const char* tfmsq_names[8]={"VARTFM_1H", "VARTFM_2H", "VARTFM_3H", "VARTFM_4H", "VARTFM_1V", "VARTFM_2V", "VARTFM_3V", "VARTFM_4V"};
    for(int k=0; k<8; k++)  {   // loop over the 8 AutoCorr 
      TArray< r_4 > & tfmap = vtfmac[k];
      tfmap *= (r_4)(1./((double)deltaIavg*(double)TFMfbin));
      potfm << PPFNameTag(tfm_names[k]) << tfmap;

      if (fos != NULL) {
	ext_names.push_back(tfm_names[k]);
	(*fos)<<  tfmap;
      }
      if (params.doSigma_) {   // for saving TFM-Sigma, if required 
	TArray< r_4 > & tfmapsq = vtfmac_sq[k];
	tfmapsq *= (r_4)(1./((double)deltaIavg*(double)TFMfbin));
	tfmapsq = tfmapsq - tfmap.MulElt(tfmap,tfmap) ; // tfmap ->tfmap*tfmap !! 
	potfm << PPFNameTag(tfmsq_names[k]) << tfmapsq;
	if (fos != NULL) {
	  ext_names.push_back(tfmsq_names[k]);
	  (*fos)<<  tfmapsq;
	}
      } // end of saving TFM-of-sigma 
    }

    // --- renormalizing and saving H-H Cross-Corr time-frequency maps 
    cout<<"  visiavg/Info: Saving 6 H-H cross-corr time-frequency maps to PPF file "<<outfile<<endl;

    const char* tfmCC_names[6]={"TFM_1H2H", "TFM_1H3H", "TFM_1H4H", "TFM_2H3H", "TFM_2H4H", "TFM_3H4H"};
    const char* vrtfmCC_names[6]={"RVARTFM_1H2H", "RVARTFM_1H3H", "RVARTFM_1H4H", "RVARTFM_2H3H", "RVARTFM_2H4H", "RVARTFM_3H4H"};
    const char* vitfmCC_names[6]={"IVARTFM_1H2H", "IVARTFM_1H3H", "IVARTFM_1H4H", "IVARTFM_2H3H", "IVARTFM_2H4H", "IVARTFM_3H4H"};

    for(int k=0; k<6; k++)  {   // loop over the 6 Xcor 
      TArray< complex<r_4> > & tfmap = vtfm[k];

      TArray< r_4 > & tfmap_sqpr = vtfm_rp_sq[k];
      TArray< r_4 > & tfmap_sqpi = vtfm_ip_sq[k];
      tfmap *= complex<r_4>((r_4)(1./((double)deltaIavg*(double)TFMfbin)), 0.);
      potfm << PPFNameTag(tfmCC_names[k]) << tfmap;
      if (fos != NULL) {
	ext_names.push_back(string(tfmCC_names[k])+"_real");
	(*fos)<<  real(tfmap);
	ext_names.push_back(string(tfmCC_names[k])+"_imag");
	(*fos)<<  imag(tfmap);
      }
      if (params.doSigma_) {   // for saving TFM-Sigma, if required 
	TArray< r_4 >  tfmapr = real(tfmap);
	TArray< r_4 >  tfmapi = imag(tfmap);
	
	tfmap_sqpr *= ((r_4)(1./((double)deltaIavg*(double)TFMfbin)));
	tfmap_sqpi *= ((r_4)(1./((double)deltaIavg*(double)TFMfbin)));
	tfmapr = tfmapr.MulElt(tfmapr,tfmapr) ;
	tfmap_sqpr -= tfmapr ;
	tfmapi = tfmapi.MulElt(tfmapi,tfmapi) ;
	tfmap_sqpi -= tfmapi;
	potfm << PPFNameTag(vrtfmCC_names[k]) << tfmap_sqpr;
	potfm << PPFNameTag(vitfmCC_names[k]) << tfmap_sqpi;
	if (fos != NULL) {
	  ext_names.push_back(vrtfmCC_names[k]);
	  (*fos)<<  tfmap_sqpr;
	  ext_names.push_back(vitfmCC_names[k]);
	  (*fos)<<  tfmap_sqpi;
	}
      }  // end of saving TFM-of-sigma  
    }
    // ========================== end saving HH XCorr

    //===========================
    if (params.doVV_){ // Option VV 
      // --- renormalizing and saving V-V Cross-Corr time-frequency maps 
      cout<<"  visiavg/Info: Saving 6 V-V cross-corr time-frequency maps to PPF file "<<outfile<<endl;

      const char* tfmVV_names[6]={"TFM_1V2V", "TFM_1V3V", "TFM_1V4V", "TFM_2V3V", "TFM_2V4V", "TFM_3V4V"};
      const char* vrtfmVV_names[6]={"RVARTFM_1V2V", "RVARTFM_1V3V", "RVARTFM_1V4V", "RVARTFM_2V3V", "RVARTFM_2V4V", "RVARTFM_3V4V"};
      const char* vitfmVV_names[6]={"IVARTFM_1V2V", "IVARTFM_1V3V", "IVARTFM_1V4V", "IVARTFM_2V3V", "IVARTFM_2V4V", "IVARTFM_3V4V"};
      
      for(int k=0; k<6; k++)  {   // loop over the 6 Xcor 
	TArray< complex<r_4> > & tfmap = vtfm_vv[k];
	
	TArray< r_4 > & tfmap_sqpr = vtfm_vv_rp_sq[k];
	TArray< r_4 > & tfmap_sqpi = vtfm_vv_ip_sq[k];
	tfmap *= complex<r_4>((r_4)(1./((double)deltaIavg*(double)TFMfbin)), 0.);
	potfm << PPFNameTag(tfmVV_names[k]) << tfmap;

	if (fos != NULL) {
	  ext_names.push_back(string(tfmVV_names[k])+"_real");
	  (*fos)<<  real(tfmap);
	  ext_names.push_back(string(tfmVV_names[k])+"_imag");
	  (*fos)<<  imag(tfmap);
	}
	if (params.doSigma_) {   // for saving TFM-Sigma, if required 
	  TArray< r_4 >  tfmapr = real(tfmap);
	  TArray< r_4 >  tfmapi = imag(tfmap);
	  
	  tfmap_sqpr *= ((r_4)(1./((double)deltaIavg*(double)TFMfbin)));
	  tfmap_sqpi *= ((r_4)(1./((double)deltaIavg*(double)TFMfbin)));
	  tfmapr = tfmapr.MulElt(tfmapr,tfmapr) ;
	  tfmap_sqpr -= tfmapr ;
	  tfmapi = tfmapi.MulElt(tfmapi,tfmapi) ;
	  tfmap_sqpi -= tfmapi;
	  potfm << PPFNameTag(vrtfmVV_names[k]) << tfmap_sqpr;
	  potfm << PPFNameTag(vitfmVV_names[k]) << tfmap_sqpi;
	  if (fos != NULL) {
	    ext_names.push_back(vrtfmVV_names[k]);
	    (*fos)<<  tfmap_sqpr;
	    ext_names.push_back(vitfmVV_names[k]);
	    (*fos)<<  tfmap_sqpi;
	  }
	}   // end of saving TFM-of-sigma  
      }
    } // end option VV 


    //===========================
    if (params.doHV_){ // Option HV 
      // --- renormalizing and saving H-V Cross-Corr time-frequency maps 
      cout<<"  visiavg/Info: Saving 16 H-V cross-corr time-frequency maps to PPF file "<<outfile<<endl;

      const char* tfmHV_names[16]={"TFM_1H1V", "TFM_1H2V", "TFM_1H3V", "TFM_1H4V", 
				   "TFM_2H1V", "TFM_2H2V", "TFM_2H3V", "TFM_2H4V", 
				   "TFM_3H1V", "TFM_3H2V", "TFM_3H3V", "TFM_3H4V",  
				   "TFM_4H1V", "TFM_4H2V", "TFM_4H3V", "TFM_4H4V"
      };
      const char* vrtfmHV_names[16]={"RVARTFM_1H1V", "RVARTFM_1H2V", "RVARTFM_1H3V", "RVARTFM_1H4V",
				     "RVARTFM_2H1V", "RVARTFM_2H2V", "RVARTFM_2H3V", "RVARTFM_2H4V",
				     "RVARTFM_3H1V", "RVARTFM_3H2V", "RVARTFM_3H3V", "RVARTFM_3H4V",
				     "RVARTFM_4H1V", "RVARTFM_4H2V", "RVARTFM_4H3V", "RVARTFM_4H4V"
      };
      const char* vitfmHV_names[16]={"IVARTFM_1H1V", "IVARTFM_1H2V", "IVARTFM_1H3V", "IVARTFM_1H4V", 
				     "IVARTFM_2H1V", "IVARTFM_2H2V", "IVARTFM_2H3V", "IVARTFM_2H4V", 
				     "IVARTFM_3H1V", "IVARTFM_3H2V", "IVARTFM_3H3V", "IVARTFM_3H4V", 
				     "IVARTFM_4H1V", "IVARTFM_4H2V", "IVARTFM_4H3V", "IVARTFM_4H4V" 
      };
      
      for(int k=0; k<16; k++)  {   // loop over the 6 Xcor 
	TArray< complex<r_4> > & tfmap = vtfm_hv[k];
	
	TArray< r_4 > & tfmap_sqpr = vtfm_hv_rp_sq[k];
	TArray< r_4 > & tfmap_sqpi = vtfm_hv_ip_sq[k];
	tfmap *= complex<r_4>((r_4)(1./((double)deltaIavg*(double)TFMfbin)), 0.);
	potfm << PPFNameTag(tfmHV_names[k]) << tfmap;

	if (fos != NULL) {
	  ext_names.push_back(string(tfmHV_names[k])+"_real");
	  (*fos)<<  real(tfmap);
	  ext_names.push_back(string(tfmHV_names[k])+"_imag");
	  (*fos)<<  imag(tfmap);
	}

	if (params.doSigma_) {   // for saving TFM-Sigma, if required 
	  TArray< r_4 >  tfmapr = real(tfmap);
	  TArray< r_4 >  tfmapi = imag(tfmap);
	  
	  tfmap_sqpr *= ((r_4)(1./((double)deltaIavg*(double)TFMfbin)));
	  tfmap_sqpi *= ((r_4)(1./((double)deltaIavg*(double)TFMfbin)));
	  tfmapr = tfmapr.MulElt(tfmapr,tfmapr) ;
	  tfmap_sqpr -= tfmapr ;
	  tfmapi = tfmapi.MulElt(tfmapi,tfmapi) ;
	  tfmap_sqpi -= tfmapi;
	  potfm << PPFNameTag(vrtfmHV_names[k]) << tfmap_sqpr;
	  potfm << PPFNameTag(vitfmHV_names[k]) << tfmap_sqpi;
	  if (fos != NULL) {
	    ext_names.push_back(vrtfmHV_names[k]);
	    (*fos)<<  tfmap_sqpr;
	    ext_names.push_back(vitfmHV_names[k]);
	    (*fos)<<  tfmap_sqpi;
	  }
	}  // end of saving TFM-of-sigma 
      }

    } // end option HV 
    P4FreqBand myp4fre;
    TVector <double> lim_freq(2);
    if (params.gain_gnu_file_.length()>0) {
      P4gnuGain p4gnu( params.gain_gnu_file_ );
      lim_freq(0) =  p4gnu. minGoodF();
      lim_freq(1) =  p4gnu. maxGoodF();
    }else{
      lim_freq(0) = myp4fre.freqstart_;
      lim_freq(1) = myp4fre.freqend_;
    }

    cout  << " frequences limites "<< lim_freq(0) <<" ; "<< lim_freq(1)<<endl;
    potfm << PPFNameTag("FreqLims") << lim_freq ;
    potfm << PPFNameTag("TimeVec") << timevec ;
    potfm << PPFNameTag("RAVec") << ravec ;
    // --- FIN sauvegarde cartes temps-frequence 
    //    resu.Update();

    

    TVector <double> avg_freqs( myp4fre.getP4NbFreqChannels()/TFMfbin);
    
    double frbase =  myp4fre.freqstart_ + myp4fre.getP4FreqResolution()/2. ;
    for (int kf=0 ; kf< myp4fre.getP4NbFreqChannels()/TFMfbin ; kf++,frbase += myp4fre.getP4FreqResolution()*TFMfbin )
      avg_freqs(kf) = frbase ;
    
    potfm << PPFNameTag("FreqVec") << avg_freqs;

    if (fos != NULL) {
      ext_names.push_back("FreqsLims");
      (*fos)<< lim_freq ;
      ext_names.push_back("Frequences");
      (*fos)<< avg_freqs ;
      ext_names.push_back("RAs");
      (*fos)<<  ravec;
      ext_names.push_back("Times");
      (*fos)<<  timevec;
      cout << " number of objs in fits "<< ext_names.size() << endl;
      cout << ext_names << endl;
      delete(fos);
    }
    cout << " return code "<<rc<<endl;
    cout << resu;   // Update est fait lors du print

  }
  catch (PException& exc) {
    cerr << " visiavg.cc catched PException " << exc.Msg() << endl;
    rc = 77;
  }  
  catch (std::exception& sex) {
    cerr << "\n visiavg.cc std::exception :" 
         << (string)typeid(sex).name() << "\n msg= " 
         << sex.what() << endl;
    rc = 78;
  }
  catch (...) {
    cerr << " visiavg.cc catched unknown (...) exception  " << endl; 
    rc = 79; 
  }

  cout << ">>>> visiavg.cc ------- END ----------- RC=" << rc << endl;
  return rc;

}