TFParams Class Reference

#include <TFParams.h>

Inheritance diagram for TFParams:

Public Member Functions
double	computePulseWidth (int, double, double)
void	copie_colonne_mat (matrice, matrice, int)
void	diff_mat (matrice, matrice, matrice)
double	f3deg (int, double parom[10], double mask[30], double adcpj[30], double errpj[30][30])
double	fitpj (double **, double *, double **, double noise_val, int debug)
double	inv3x3 (double a[3][3], double b[3][3])
double	inverpj (int, double g[30][30], double ginv[30][30])
void	inverse_mat (matrice, matrice)
double	lastShape (Double_t *, Double_t *)
double	lastShape2 (Double_t *, Double_t *)
double	mixShape (Double_t *, Double_t *)
double	parab (double *, Int_t, Int_t, double *)
Double_t	polfit (Int_t ns, Int_t imax, Double_t par3d[10], Double_t errpj[30][30], double *)
void	print_mat (matrice)
void	print_mat_nk (matrice, int)
void	produit_mat (matrice, matrice, matrice)
void	produit_mat_int (matrice, matrice, matrice)
double	pulseShapepj (Double_t *, Double_t *)
double	pulseShapepj2 (Double_t *, Double_t *)
void	set_const (int, int, int, double, double, int)
void	somme_mat_int (matrice, matrice)
void	somme_mat_int_scale (matrice, matrice, double)
	TFParams (int size=10, int size_sh=650)
void	transpose_mat (matrice, matrice)
void	zero_mat (matrice)
void	zero_mat_nk (matrice, int)
	~TFParams ()

Public Attributes
char	name_mat [10]

Private Attributes
double	a1ini
double	a2ini
double	a3ini
double	adclu [26]
int	METHODE
int	nevtmax
int	ns
int	nsmax
int	nsmin
double	step_shape
double	weight_matrix [10][10]

Detailed Description

Definition at line 47 of file TFParams.h.

Constructor & Destructor Documentation

TFParams::TFParams	(	int	size = 10,
		int	size_sh = 650
	)

Definition at line 25 of file TFParams.cc.

References i, and j.

                                          {

  //int  sdim = size;
  //int plshdim = size_sh;

for (int i=0 ; i<10 ; i++) {
  for (int j=0 ; j<10 ; j++) {
      weight_matrix[i][j] = 8.; 
    }
  } 

}

TFParams::~TFParams ( )

inline

Definition at line 66 of file TFParams.h.

{};

Member Function Documentation

double TFParams::computePulseWidth	(	int	methode,
		double	alpha_here,
		double	beta_here
	)

Definition at line 1226 of file TFParams.cc.

References dt, testEve_cfg::level, hltrates_dqm_sourceclient-live_cfg::offset, and create_public_lumi_plots::width.

                                                                                     { 

// level of amplitude where we calculate the width ( level = 0.5 if at 50 % )
//   (level = 0.3 if at 30 % )
  double level = 0.30 ;
// fixed parameters
  double amplitude   = 1.00 ;
  double offset      = 7.00;  
  double amp_max     = amplitude;

// steps in time
  double t_min       =  offset-4.50;
  double t_max       =  offset+12.50;

  int    t_step_max  = 3000;
  double delta_t     =  (double)((t_max-t_min)/t_step_max);
      
// Loop over time ( Loop 2  --> get width )
  int    t_amp_half_flag =    0;
  double t_amp_half_min  =  999.; 
  double t_amp_half_max  = -999.; 

  for (int t_step=0; t_step<t_step_max; t_step++){

       double t_val = t_min + (double)t_step*delta_t;
       double albet = alpha_here*beta_here ;
       double dt = t_val-offset ;
       double amp =0;

       if( methode == 2 ) { // electronic function
      if( (t_val-offset) > -albet) {

            amp =  amplitude*TMath::Power( ( 1 + ( dt / (alpha_here*beta_here) ) ) , alpha_here ) * TMath::Exp(-1.0*(dt/beta_here));
      } else {
        
        amp = 1. ;
      }
       } 

       if( amp > (amp_max*level) && t_amp_half_flag == 0) {
           t_amp_half_flag = 1;
           t_amp_half_min = t_val;
       }

       if( amp < (amp_max*level) && t_amp_half_flag == 1) {
           t_amp_half_flag = 2;
           t_amp_half_max = t_val;
       }          

   }
    
// Compute Width
  double width = (t_amp_half_max - t_amp_half_min);

  return width;
}

void TFParams::copie_colonne_mat	(	matrice	A,
		matrice	M,
		int	nk
	)

Definition at line 626 of file TFParams.cc.

References matrice::coeff, i, j, relval_2017::k, matrice::nb_colonnes, matrice::nb_lignes, and reco::return().

{
  int i,j ;
  int k ;
 /* resultat de la copie de A dans un vecteur colonne M */
  k = 0 ;
  for(i=0 ; i< A.nb_lignes; i++) {
    for(j=0 ; j < A.nb_colonnes ; j++) {
      M.coeff[nk][k] = A.coeff[i][j] ;
   printf(" copie nk %d  i %d j %d k %d A %e M %e \n ",nk,i,j,k,A.coeff[i][j],
      M.coeff[nk][k]);      
      k++ ;
    }
  }
  return  ;
}

void TFParams::diff_mat	(	matrice	A,
		matrice	B,
		matrice	M
	)

Definition at line 607 of file TFParams.cc.

References matrice::coeff, i, j, matrice::nb_colonnes, matrice::nb_lignes, NULL, and reco::return().

{
  int i,j ;
//resultat de la difference A-B = M 
  if(A.nb_lignes != B.nb_lignes) {
    printf( " Erreur : difference de matrices de tailles incompatibles \n ");
    M.coeff = NULL ;
    return ;
  }
  M.nb_lignes = A.nb_lignes ;
  M.nb_colonnes = A.nb_colonnes ;
  for(i=0 ; i< M.nb_lignes; i++) {
    for(j=0 ; j < M.nb_colonnes ; j++) {
      M.coeff[i][j] = A.coeff[i][j] - B.coeff[i][j] ;
    }
  }
  return  ;
  
}

double TFParams::f3deg	(	int	nmxu,
		double	parom[10],
		double	mask[30],
		double	adcpj[30],
		double	errpj[30][30]
	)

Definition at line 867 of file TFParams.cc.

References delta, dimmat, f, h, i, relval_2017::k, cmsLHEtoEOSManager::l, alignCSCRings::s, mathSSE::sqrt(), lumiQTWidget::t, reco::t2, and tmp.

                                                                                                                                       {
/*                                                                   */
/*  fit   3rd degree polynomial                                      */
/*  nmxu = nb of samples in sample data array adcpj[]
    parom   values of parameters
    errpj  inverse of the error matrix
    fplo3dg uses only the diagonal terms of errpj[][]
*/
  int i , k , l  /*,iworst*/ ;
  double  h , t2 , tm , delta , tmp ;
  double xki2 , dif , difmx , deglib   ;
  double t[dimmat] ,  f[dimmat][4]   ;
  double cov[dimmat][dimmat] , bv[4] , invcov[dimmat][dimmat] , s /*, deter*/  ;
  
  deglib=(double)nmxu - 4.  ;
  for ( i=0 ; i<nmxu ; i++ ) {
    t[i]=i ;
    f[i][0]=1. ;
    f[i][1]=t[i]  ;
    f[i][2]=t[i]*t[i]  ;
    f[i][3]=f[i][2]*t[i] ;
  }
/*   computation of covariance matrix     */
  for ( k=0 ; k<4 ; k++ ) {
    for ( l=0 ; l<4 ; l++ ) {
      s=0.   ;
      for (i=0 ; i<nmxu ; i++ ) {
        s=s+f[i][k]*f[i][l]*errpj[i][i]*mask[i]   ;
      }
      cov[k][l]=s  ;
    }
    s=0.    ;
    for (i=0 ; i<nmxu ; i++ ) {
        s=s+f[i][k]*adcpj[i]*errpj[i][i]*mask[i]   ;
    }
      bv[k]=s  ;
  }
/*     parameters                          */
  /*deter =*/ inverpj ( 4 , cov , invcov );
  for ( k=0 ; k<4 ; k++ ) {
    s=0.  ;
    for ( l=0 ; l<4 ; l++ ) {
      s=s+bv[l]*invcov[l][k]   ;
    }
    parom[k]=s  ;
  }

  if( parom[3] == 0. ){
    parom[4] = -1000.;
    parom[5] = -1000.;
    parom[6] = -1000.;
    return 1000000.;
  }
/*    worst hit and ki2                    */
  xki2=0.    ;
  difmx=0.   ;
    for (i=0 ; i<nmxu ; i++ ){
      t2=t[i]*t[i]  ;
      h= parom[0]+parom[1]*t[i]+parom[2]*t2+parom[3]*t2*t[i] ;
      dif=(adcpj[i]-h)*mask[i]     ;
        if(dif > difmx) {
      // iworst=i  ;
      difmx=dif ;
    }
    }
    if(deglib > 0.5) xki2=xki2/deglib ;
/*     amplitude and maximum position                    */
  delta=parom[2]*parom[2]-3.*parom[3]*parom[1]  ;
  if(delta > 0.){
    delta=sqrt(delta)  ;
    tm=-(delta+parom[2])/(3.*parom[3])  ;
    tmp=(delta-parom[2])/(3.*parom[3])  ;
  }
  else{
    parom[4] = -1000.;
    parom[5] = -1000.;
    parom[6] = -1000.;
    return xki2  ;
  }
  parom[4]= tm  ;
  parom[5]= parom[0]+parom[1]*tm+parom[2]*tm*tm+parom[3]*tm*tm*tm ;
  parom[6]= tmp ;
  // printf("par --------> %f %f %f %f \n",parom[3],parom[2],parom[1],parom[0]);
  
   return xki2  ;
}

double TFParams::fitpj	(	double **	adcval,
		double *	parout,
		double **	db_i,
		double	noise_val,
		int	debug
	)

Definition at line 38 of file TFParams.cc.

References alpha, beta, funct::C, HLT_FULL_cff::chi2, matrice::coeff, gather_cfg::cout, cree_mat(), cree_mat_prod(), dqmPostProcessing_online::DB, delta, dt, i, j, relval_2017::k, relval_steps::k2, dqm-mbProfile::log, nsamp, ntrack, lumiQTWidget::t, X, and Gflash::Z.

Referenced by TShapeAnalysis::computeShape().

{
  
#define dimn 10
#define dimin 10
#define plshdim 300
#define nsamp 10                                            
#define ntrack 500       
  //#define debug debug1

  // ******************************************************************
  // *  Definitions of variables used in the routine                    
  // ******************************************************************
  
  
  double a1,a2,a3,b1,b2;
  int iter,nevt;
  //double errpj[dimmat][dimmat]  ;
  double bi[ntrack][2],dbi[ntrack][2];
  double zi[ntrack][2] ;
  double par3degre[3] ;
  int    ioktk[ntrack],nk,nborn_min=0,nborn_max=0;
  double cti[ntrack][6],dm1i[ntrack][4]; 
  double par[4],tsig[1];
  double amp,delta[nsamp],delta2,fun;
  double num_fit_min[ntrack],num_fit_max[ntrack] ;
  int i,j,k,imax[ntrack];

  double ampmax[ntrack],dt,t;
  double chi2, chi2s, da1[nsamp], da2[nsamp], db1[nsamp], db2[nsamp] ;
  double chi2tot;
  double fact2;
  double albet,dtsbeta,variab,alpha,beta;
  double  unsurs1 /*,unsurs2*/ ;
//  double fit3 ;
  int numb_a,numb_b,numb_x;

  fun=0; chi2s=0; chi2tot=0;
  matrice DA,DAT,BK,DB,DBT,C,CT,D,DM1,CDM1,CDM1CT,Z,CDM1Z,YK,Y,B,X,XINV,RES2 ;
  matrice A_CROISS,ZMCT ;

  double *amplu ;
  amplu = new double[nsamp] ;
  
  parout[0] = 0. ;
  parout[1] = 0. ;
  parout[2] = 0. ;

  //  
  //  Initialisation of fit parameters 
  //  

  a1 = a1ini ;
  a2 = a2ini ;
  a3 = a3ini ;
  if( METHODE==2) {
    a2 = a3ini ;   // for lastshape BETA is the third parameter ( ... ! )
  }
  if (debug==1){
    printf(" ------> __> valeurs de a1 %f a2 %f a3 %f\n",a1,a2,a3) ;
  }
  for (i=0 ; i<ntrack ; i++) {
    for (j=0 ; j<2 ; j++ ) {
      bi[i][j] = (double)0. ;
      dbi[i][j] = (double)0. ;
      zi[i][j]=(double)0. ;
      cti[i][j]=(double)0. ;
      dm1i[i][j]=(double)0. ;
    }
  }

  numb_a = 2 ;


  //
  //  Matrices initialisation
  //

  numb_x = 1 ;
  numb_b = 2 ;
  DA = cree_mat(numb_a,numb_x) ;
  DAT = cree_mat(numb_x,numb_a) ;
  BK = cree_mat_prod(DA,DAT) ;
  DB = cree_mat(numb_b,numb_x) ;
  DBT = cree_mat(numb_x,numb_b) ;
  C = cree_mat(numb_a,numb_b) ;
  CT = cree_mat(numb_b,numb_a) ;
  D = cree_mat_prod(DB,DBT) ;
  DM1 = cree_mat_prod(DB,DBT) ;
  CDM1 = cree_mat_prod(C,DM1) ;
  CDM1CT = cree_mat_prod(CDM1,CT) ;
  Z = cree_mat(numb_b,numb_x) ;
  CDM1Z =cree_mat_prod(CDM1,Z) ;
  YK =cree_mat(numb_a,numb_x) ;
  Y =cree_mat(numb_a,numb_x) ;
  B = cree_mat_prod(DA,DAT) ;
  X = cree_mat_prod(DA,DAT) ;
  XINV = cree_mat_prod(DA,DAT) ;
  RES2=cree_mat(numb_a,numb_x) ;
  A_CROISS = cree_mat(numb_a,numb_x) ;
  ZMCT = cree_mat(numb_b,numb_x) ;


  // First Loop on iterations //                        
 
  for (iter=0 ; iter < 6 ; iter++) {

    chi2tot=0;

    //    
    //    Set zeros for general matrices
    //                                                                      
    
    if (debug==1){
      printf(" Debut de l'iteration numero %d \n",iter) ;
    }
    zero_mat(CDM1Z) ;
    zero_mat(Y) ;
    zero_mat(CDM1CT) ;
    zero_mat(B) ;
    zero_mat(X) ;
    zero_mat(CDM1) ;


    nk = -1 ;   
    if (debug==1){
      printf( " resultats injectes a iterations %d \n",iter) ;
      printf( " parametre a1 = %f \n",a1) ;
      printf( " parametre a2 = %f \n",a2) ;
      printf( " chi2 du fit chi2s = %f \n",chi2s) ;
      
      printf(" value de nevtmax _______________ %d \n",nevtmax) ;
    }
    
    
    //  Loop on events //
    
    for (nevt=0 ; nevt < nevtmax ; nevt++) {
                 
      //       B1 = BI[nk,1] est la normalisation du signal                    
      //       B2 = BI[nk,2] ewst le dephasage par rapport a une            
      //                 fonction centree en zero                                 
      //        Nous choisissons ici de demarrer avec les resultats           
      //            de l'ajustement parabolique mais il faudra bien             
      //            entendu verifier que cela ne biaise pas le resultat !      
      //            mise a zero des matrices utilisees dans la boucle             
      
      
      zero_mat(Z) ;
      zero_mat(YK) ;
      zero_mat(BK) ;
      zero_mat(C) ;
      zero_mat(D) ;
      
      nk=nevt ;  
      ampmax[nk] = 0. ;
      imax[nk] = 0 ;
      for ( k = 0 ; k < 10 ; k++) {     
    amplu[k]=adcval[nevt][k] ; 
    if (amplu[k] > ampmax[nk] ) {
      ampmax[nk] = amplu[k] ;
      imax[nk] = k ; 
    }
      }
      
      
      if( iter == 0 ) {

        // start with degree 3 polynomial .... 
    //fit3 =polfit(ns ,imax[nk] ,par3degre ,errpj ,amplu ) ;
    //  std::cout << "Poly Fit Param  :"<< par3degre[0] <<" "<< par3degre[1]<< std::endl; 
        
    // start with parabol
    //fit3 = parab(amplu,4,12,par3degre) ;
    /*fit3 =*/ parab(amplu,2,9,par3degre) ;
    //std::cout << "Parab Fit Param :"<< par3degre[0] <<" "<< par3degre[1]<< std::endl; 


    // start with basic initial values
    //par3degre[0]= ampmax+ampmax/10. ;
    //par3degre[1]= (double)imax[nk]+0.1 ;
    //bi[nk][0] = ampmax[nk] ;
    //bi[nk][1] = (double)imax[nk] ;

    num_fit_min[nevt] = (double)imax[nk] - (double)nsmin ;
        num_fit_max[nevt] = (double)imax[nk] + (double)nsmax ;
    
    
    bi[nk][0] = par3degre[0] ;
    bi[nk][1] = par3degre[1] ;
    
    
    if (debug==1){
      printf("---------> depart ampmax[%d]=%f   maximum %f tim %f \n",
         nk,ampmax[nk],bi[nk][0],bi[nk][1]);
    }
    
      } else {
    
    
    //  in other iterations  :                                              
    //   increment bi[][] parameters with bdi[][]                         
    //   calculated in previous                                           
    //   iteration                                                      
    

    bi[nk][0] +=  dbi[nk][0] ;
    bi[nk][1] +=  dbi[nk][1] ;
    
    if (debug==1){
      printf("iter %d valeur de max %f et norma %f poly 3 \n",iter,bi[nk][1],bi[nk][0]) ;
    }   
      }
    
      b1 = bi[nk][0] ;
      b2 = bi[nk][1] ;


      // Loop on samples //                     
      
      chi2 = 0. ;
      ioktk[nk] = 0 ;
      ns =nborn_max-nborn_min+1 ;
       
      for (k=0 ; k < 10 ; k++){
    
    //
    //  calculation of fonction used to fit
    //   
    
    dt =(double)k - b2 ;
    t = (double)k ;
    amp = amplu[k] ;
    if (debug==1){
      printf(" CHECK sample %f ampli %f \n",t,amp) ;
    }
        //unsurs1 = 1./sig_err ;
    //unsurs2 = 1./(sig_err*sig_err) ;
    //unsurs1 = 0.1 ;
    //unsurs2 = 0.01 ;
    
    
    unsurs1=1./noise_val;
    //unsurs2=(1./noise_val)*(1./noise_val);

    //                           
    // Pulse shape function used: pulseShapepj
    //
    
    nborn_min = (int)num_fit_min[nevt] ;
    nborn_max = (int)num_fit_max[nevt] ;
        if(k < nborn_min || k > nborn_max ) continue ;
        tsig[0] =(double)k  ;

    
        if(METHODE==2) {
    par[0]=  b1 ;
    par[1] = b2 ;
    par[2] = a1 ;
    par[3] = a2 ;
    fun = pulseShapepj( tsig , par) ;
        }
    if (debug==1){
      printf(" valeur ampli %f et function %f min %d max %d \n",amp,fun,nsmin,nsmax) ;
      printf("min %f max %f \n",num_fit_min[nevt],num_fit_max[nevt]) ;
    }
    
    //   we need to determine a1,a2 which are global parameters         
    //    and  b1, b2 which are parameters for each individual signal: 
    //        b1, b2 = amplitude and time event by event
    //        a1, a2 = alpha and beta global      
    //    we first begin to calculate the derivatives used in the following calculation                          
    
    if(METHODE==2){
      alpha = a1 ;
      beta  = a2 ;
      albet=alpha*beta;
      if(dt > -albet)  { 
        variab = (double)1. + dt/albet ;
        dtsbeta = dt/beta ;
        db1[k] = unsurs1*fun/b1 ;
        fact2 =  fun ;
        db2[k] = unsurs1*fact2*dtsbeta/(albet*variab) ;
        da1[k] = unsurs1*fact2*(log(variab)-dtsbeta/(alpha*variab)) ;
        da2[k] = unsurs1*fact2*dtsbeta*dtsbeta/(albet*variab) ;
      }
    }
        delta[k] = (amp - fun)*unsurs1 ;
    if (debug==1){
      printf(" ------->iter %d valeur de k %d amp %f fun %f delta %f \n",
         iter,k,amp,fun,delta[k]) ;
      printf(" -----> valeur de k %d delta %f da1 %f da2 %f  \n",
         k,delta[k],da1[k],da2[k]) ;
    }

    chi2 = chi2 + delta[k]*delta[k]     ;
    
    if (debug==1){
      printf(" CHECK chi2 %f deltachi2 %f sample %d iter %d \n",chi2,delta[k]*delta[k],k, iter) ;
    }

      }
    
      
      // End Loop on samples //                     
      
      
      double wk1wk2 ;

      // Start Loop on samples //                       

      for(int k1=nborn_min ; k1<nborn_max+1 ; k1++) {
    wk1wk2 = 1. ;
    int k2 = k1 ;
    
    DA.coeff[0][0] = da1[k1]*wk1wk2 ;
    DA.coeff[1][0] = da2[k1]*wk1wk2 ;
    DAT.coeff[0][0]= da1[k2] ;
    DAT.coeff[0][1]= da2[k2] ;
    DB.coeff[0][0] = db1[k1]*wk1wk2 ;
    DB.coeff[1][0] = db2[k1]*wk1wk2 ;
    DBT.coeff[0][0]= db1[k2] ;
    DBT.coeff[0][1]= db2[k2] ;
    
    //  Compute derivative matrix : matrix b[2][2]  
    
        produit_mat_int(DA,DAT,BK) ;
    
    //  Compute matrix c[2][2]                          
    
        produit_mat_int(DA,DBT,C) ;
    
    //  Compute matrix d[2][2]                               
    
    produit_mat_int(DB,DBT,D) ;
    
    //  Compute matrix y[3] and z[2] depending of delta (amp-fun)        
    
    delta2 = delta[k2] ;
    
    somme_mat_int_scale(DA,YK,delta2) ;         
        somme_mat_int_scale(DB,Z,delta2) ;
    
    ioktk[nk]++ ;
    
      }
      
      // End Loop on samples //                     
      
      
      //  Remove events with a bad shape 
      
      if(ioktk[nk] < 4 ) {
    printf(" event rejected because npamp_used = %d \n",ioktk[nk]);
    continue ;
      }
      chi2s = chi2/(2. + (double)ns + 2.)  ;      
      chi2tot+=chi2s;

      if (debug==1){
    if (nevt==198 || nevt==199){
      std::cout << "adc123 pour l'evt " << nevt <<" = "<<adcval[nevt][nborn_min]<<" = "<<adcval[nevt][imax[nevt]]<<" = "<<adcval[nevt][nborn_max]<<std::endl;
      std::cout << "chi2s  pour l'evt " << nevt <<" = "<< chi2s<<" "<< chi2<<" "<< ns<<"  "<<iter<<std::endl;
      std::cout << "chi2tot           " << nevt <<" = "<< chi2tot<<"  "<<iter<<std::endl;
    }
      }
      
      //  Transpose matrix C ---> CT                        
     
      transpose_mat(C,CT) ;
      
      //  Calculate DM1 (inverse of D matrix 2x2)             
      
      inverse_mat(D,DM1) ;

      
      //  Set matrix product c*d in memory in order to compute variations    
      //   of parameters B at the end of the iteration loop                   
      //   the variations of parameters b are dependant of the variations of  
      //   parameters da[1],da[2]                                            
         
      cti[nk][0] = CT.coeff[0][0]  ;
      cti[nk][1] = CT.coeff[0][1]  ;
      cti[nk][2] = CT.coeff[1][0]  ;
      cti[nk][3] = CT.coeff[1][1]  ;
      
      
       dm1i[nk][0] = DM1.coeff[0][0] ;
       dm1i[nk][1] = DM1.coeff[0][1] ;
       dm1i[nk][2] = DM1.coeff[1][0] ;
       dm1i[nk][3] = DM1.coeff[1][1] ; 

       zi[nk][0] = Z.coeff[0][0]  ;
       zi[nk][1] = Z.coeff[1][0]  ;

       //   Sum the matrix b and y after every event            
      
       for( k=0 ; k< numb_a ; k++) {
     Y.coeff[k][0] += YK.coeff[k][0] ;
       }
       somme_mat_int(BK,B) ;
       

       //   Calculate c(d-1)                                     

      produit_mat(C,DM1,CDM1) ;

      // Compute c(d-1)ct                                         

      produit_mat_int(CDM1,CT,CDM1CT);
                                                                 
      // Compute c(d-1)z                                          
      
      produit_mat_int(CDM1,Z,CDM1Z) ;


    }
      // End Loop on events //                      
    
    
    //  Compute b-cdm1ct
       
    diff_mat(B,CDM1CT,X) ;
    inverse_mat(X,XINV) ;
    diff_mat(Y,CDM1Z,RES2) ;

                                                                  
    // Calculation is now easy for da[0] da[1]                         
                                                                  
    produit_mat(XINV,RES2,A_CROISS) ;

    
    //  A la fin, on peut iterer en mesurant l'accroissement a apporter
    //    des parametres globaux par la formule db[i] = dm1(z-ct*da[i])  
         
    for( k=0 ; k< nk+1 ; k++) {
      
      if(METHODE ==2 ) {
    ZMCT.coeff[0][0] = zi[k][0] - (cti[k][0]*A_CROISS.coeff[0][0]+
                       cti[k][1]*A_CROISS.coeff[1][0]) ;
    ZMCT.coeff[1][0] = zi[k][1] - (cti[k][2]*A_CROISS.coeff[0][0]+
                       cti[k][3]*A_CROISS.coeff[1][0]) ;
      }
      
      dbi[k][0] = dm1i[k][0]*ZMCT.coeff[0][0] + dm1i[k][1]*ZMCT.coeff[1][0] ;
      dbi[k][1] = dm1i[k][2]*ZMCT.coeff[0][0] + dm1i[k][3]*ZMCT.coeff[1][0] ;
      if (debug==1){
    if( k < 100 ){
      printf(" variations de b1= %f et b2= %f  \n",dbi[k][0],dbi[k][1]) ;
    } 
      }
      db_i[k][0] = bi[k][0]+ dbi[k][0]   ;
      db_i[k][1] = bi[k][1]+ dbi[k][1]   ;
    }
    
    
    //   dbi[0] et dbi[1] mesurent les variations a apporter aux       
    //   parametres du signal                                          
                                                                     
    a1 += A_CROISS.coeff[0][0] ;
    a2 += A_CROISS.coeff[1][0] ;
    

    if (debug==1){
      printf(" CHECK croiss coef0: %f  croiss coef1: %f iter %d \n",fabs(A_CROISS.coeff[0][0]),fabs(A_CROISS.coeff[1][0]), iter);
    }
    if(fabs(A_CROISS.coeff[0][0]) < 0.001 && fabs(A_CROISS.coeff[1][0]) < 0.001)
      break;
    
  }
  
  //  End Loop on iterations //

  parout[0] = a1 ;
  parout[1] = a2 ;
  parout[2] = a3 ;
  if (debug==1){
    printf( " resultats trouves au bout de %d iterations \n",iter) ;
    printf( " parametre a1 = %f \n",a1) ;
    printf( " parametre a2 = %f \n",a2) ;
  }

  if (debug==1){
    std::cout << " Final chi2 / NDOF  :  "<< chi2tot/nevtmax << std::endl;
    std::cout << " Final (alpha,beta) : ("<< a1<<","<<a2<<")"<< std::endl;
  }

  return chi2tot/nevtmax ;

}

double TFParams::inv3x3	(	double	a[3][3],
		double	b[3][3]
	)

Definition at line 1017 of file TFParams.cc.

References i, and j.

{
/*   a[ligne][colonne]   b[ligne][colonne]   */
int i , j   ;
double  deter=0.  ;
      b[0][0]=a[1][1]*a[2][2]-a[2][1]*a[1][2] ;
      b[1][1]=a[0][0]*a[2][2]-a[2][0]*a[0][2] ;
      b[2][2]=a[0][0]*a[1][1]-a[0][1]*a[1][0] ;
      printf("a[x][x] %e %e %e %e %e %e %e \n",a[0][0],a[1][1],a[0][1],a[1][0],
         a[0][0]*a[1][1],a[0][1]*a[1][0],b[2][2]);
      b[0][1]=a[2][1]*a[0][2]-a[0][1]*a[2][2] ;
      b[0][2]=a[0][1]*a[1][2]-a[1][1]*a[0][2] ;
      b[1][0]=a[1][2]*a[2][0]-a[1][0]*a[2][2] ;
      b[1][2]=a[1][0]*a[0][2]-a[0][0]*a[1][2] ;
      b[2][0]=a[1][0]*a[2][1]-a[1][1]*a[2][0] ;
      b[2][1]=a[0][1]*a[2][0]-a[0][0]*a[2][1] ;
      deter=a[0][0]*b[0][0] + a[1][0]*b[0][1] + a[2][0]*b[0][2] ;
      printf(" deter = %e \n",deter) ;
 for ( i=0 ; i<3 ; i++ ) {
   for ( j=0 ; j<3 ; j++ ) {
     printf(" avant division a[3][3] %d %d  %e \n",i,j,a[i][j]) ;
     printf(" avant division b[3][3] %d %d  %e %e \n",i,j,b[i][j],deter) ;
     b[i][j] = b[i][j]/deter  ;
     printf(" valeur de b[3][3] apres division %d %d  %e %e \n",i,j,b[i][j],deter) ;
   }
 }
  return deter ;
}

double TFParams::inverpj	(	int	n,
		double	g[30][30],
		double	ginv[30][30]
	)

Definition at line 955 of file TFParams.cc.

References dimmat, g, i, j, findQualityFiles::jj, relval_2017::k, gen::n, alignCSCRings::r, alignCSCRings::s, and mathSSE::sqrt().

{
/*                                                                   */
/*  inversion d une matrice symetrique definie positive de taille n  */
/*  J.P. Pansart   Novembre 99                                       */
/*                                                                   */
int i , j , k , jj  ;
double r ,  s  ;
double deter=0  ;
double al[dimmat][dimmat] , be[dimmat][dimmat]  ;
/*   initialisation                                                  */
 for( i=0 ; i<n ; i++ ) {
   for ( j=0 ; j<n ; j++ ) {
    al[i][j] = 0.  ;
    be[i][j] = 0.  ;
   }
 }
/*  decomposition en vecteurs sur une base orthonormee               */
 al[0][0] =  sqrt( g[0][0] )  ;
 for ( i=1 ; i<n ; i++ ) {
 al[i][0] = g[0][i] / al[0][0]  ;
   for ( j=1 ; j<=i ; j++ ) {
    s=0.   ;
    for ( k=0 ; k<=j-1 ; k++ ) {
     s=s+ al[i][k] * al[j][k]  ;
    }
    r= g[i][j] - s   ;
   if( j < i ) al[i][j] = r/al[j][j]  ;
   if( j == i ) al[i][j] =  sqrt ( r)  ;
   }
 }
/*  inversion de la matrice al                                       */
 be[0][0] = 1./al[0][0]  ;
 for ( i=1 ; i<n ; i++ ) {
 be[i][i] = 1. / al[i][i]  ;
   for ( j=0 ; j<i ; j++ ) {
    jj=i-j-1  ;
    s=0.   ;
    for ( k=jj+1 ; k<=i ; k++ ) {
     s=s+ be[i][k] * al[k][jj]  ;
    }
    be[i][jj]=-s/al[jj][jj]  ;
   }
 }
/*   calcul de la matrice ginv                                       */
 for ( i=0 ; i<n ; i++ ) {
   for ( j=0 ; j<n ; j++ ) {
    s=0.   ;
    for ( k=0 ; k<n ; k++ ) {
     s=s+ be[k][i] * be[k][j]  ;
    }
    ginv[i][j]=s  ;
    //    if (debug==1){
    //printf("valeur de la matrice %d %d %f \n",i,j,ginv[i][j]) ;
    //}
   }
 }
  return deter ;
}

void TFParams::inverse_mat	(	matrice	A,
		matrice	M
	)

Definition at line 777 of file TFParams.cc.

References matrice::coeff, i, j, matrice::nb_colonnes, matrice::nb_lignes, and reco::return().

{
/*   A[ligne][colonne]   B[ligne][colonne]   */
int i , j   ;
double  deter=0.  ;
/*  M est la matrice inverse de A */
 
 if(A.nb_lignes != A.nb_colonnes) {
   printf( " attention matrice non inversible !!!! %d lignes %d colonnes \n",
       A.nb_lignes,A.nb_colonnes) ;
   return ;
 }
  zero_mat(M) ;
  if(A.nb_lignes == 2) {
    deter = A.coeff[0][0]*A.coeff[1][1] - A.coeff[0][1]*A.coeff[1][0] ;
    M.coeff[0][0] = A.coeff[1][1]/deter ;
    M.coeff[0][1] = -A.coeff[0][1]/deter ;
    M.coeff[1][0] = -A.coeff[1][0]/deter ;
    M.coeff[1][1] = A.coeff[0][0]/deter ;
  }
 else if(A.nb_lignes == 3) {
      M.coeff[0][0]=A.coeff[1][1]*A.coeff[2][2]-A.coeff[2][1]*A.coeff[1][2] ;
      M.coeff[1][1]=A.coeff[0][0]*A.coeff[2][2]-A.coeff[2][0]*A.coeff[0][2] ;

      M.coeff[2][2]=A.coeff[0][0]*A.coeff[1][1]-A.coeff[0][1]*A.coeff[1][0] ;
      M.coeff[0][1]=A.coeff[2][1]*A.coeff[0][2]-A.coeff[0][1]*A.coeff[2][2] ;
      M.coeff[0][2]=A.coeff[0][1]*A.coeff[1][2]-A.coeff[1][1]*A.coeff[0][2] ;
      M.coeff[1][0]=A.coeff[1][2]*A.coeff[2][0]-A.coeff[1][0]*A.coeff[2][2] ;
      M.coeff[1][2]=A.coeff[1][0]*A.coeff[0][2]-A.coeff[0][0]*A.coeff[1][2] ;
      M.coeff[2][0]=A.coeff[1][0]*A.coeff[2][1]-A.coeff[1][1]*A.coeff[2][0] ;
      M.coeff[2][1]=A.coeff[0][1]*A.coeff[2][0]-A.coeff[0][0]*A.coeff[2][1] ;
      deter=A.coeff[0][0]*M.coeff[0][0]+A.coeff[1][0]*M.coeff[0][1]
    +A.coeff[2][0]*M.coeff[0][2] ;
      for ( i=0 ; i<3 ; i++ ) {
    for ( j=0 ; j<3 ; j++ ) M.coeff[i][j] = M.coeff[i][j]/deter  ;
      }
 }
 else {
 printf(" Attention , on ne peut inverser la MATRICE %d \n",A.nb_lignes) ;
 return ;
 }
  
 return ;
}

double TFParams::lastShape	(	Double_t *	x,
		Double_t *	par
	)

Definition at line 1083 of file TFParams.cc.

References alpha, beta, dt, create_public_lumi_plots::exp, and HLT_FULL_cff::exponent.

{

  Double_t fitfun;
  Double_t alpha, beta;
  Double_t dt,alphadt,exponent ;
  Double_t b1,b2 ;
  b1 = par[0] ;
  b2 = par[1] ;
  alpha = par[2] ;
  beta  = par[3] ;
  dt= x[0] - b2  ;
  alphadt = alpha*dt ;
  exponent = -(alphadt+(exp(-alphadt)-1.))/beta ; 
  fitfun = b1*exp(exponent) ; 
  return fitfun;
}

double TFParams::lastShape2	(	Double_t *	x,
		Double_t *	par
	)

Definition at line 1100 of file TFParams.cc.

References alpha, beta, dt, create_public_lumi_plots::exp, and HLT_FULL_cff::exponent.

{

  Double_t fitfun;
  Double_t alpha, beta;
  Double_t dt,expo1,dt2,exponent ;
  Double_t b1,b2 ;
  b1 = par[0] ;
  b2 = par[1] ;
  alpha = par[2] ;
  beta  = par[3] ;
  dt= x[0] - b2  ;
  expo1 = exp(-beta*dt) ;
  dt2 = dt*dt ;
  exponent = -(alpha*dt2+(expo1-1.)) ;
  fitfun = b1*exp(exponent) ; 
  return fitfun;
}

double TFParams::mixShape	(	Double_t *	x,
		Double_t *	par
	)

Definition at line 1193 of file TFParams.cc.

References alpha, beta, dt, create_public_lumi_plots::exp, HLT_FULL_cff::exponent, fact, funct::pow(), and lumiQTWidget::t.

{
  Double_t fitval0,fitval;
  Double_t alpha,beta,fact,puiss;
  Double_t dt,alpha2dt,exponent ;
  Double_t b1,b2,alpha2,t ;
  b1 = par[0] ;
  b2 = par[1] ;
  alpha  = par[2] ;
  alpha2 = par[3] ;
  beta   = par[4] ;
//
  t = x[0] ;
  dt= x[0]-b2  ;
//
  if(t>0.) {
  fact = t/b2 ;
  puiss = pow(fact,alpha) ;
  fitval0 = puiss*exp(-alpha*dt/b2) ;
  }
  else
  {
  fitval0=1. ;
  }
  dt = x[0] - b2 ;
  alpha2dt = dt*alpha2 ;
  exponent = -(alpha2dt+(exp(-alpha2dt)-1.))/beta ;
  fitval = b1*fitval0*exp(exponent) ;  
  return fitval;
}

double TFParams::parab	(	double *	,
		Int_t	,
		Int_t	,
		double *
	)

Definition at line 1154 of file TFParams.cc.

References dt, and relval_2017::k.

{
/* Now we calculate the parabolic adjustement in order to get        */
/*    maximum and time max                                           */
  
  double denom,dt,amp1,amp2,amp3 ; 
  double ampmax = 0. ;              
  int imax = 0 ;
  int k ;
/*
                                                                   */     
  for ( k = nmin ; k < nmax ; k++) {
    if (ampl[k] > ampmax ) {
      ampmax = ampl[k] ;
      imax = k ;
    }
  }
    amp1 = ampl[imax-1] ;
    amp2 = ampl[imax] ;
    amp3 = ampl[imax+1] ;
    denom=2.*amp2-amp1-amp3  ;
/*                                       */       
    if(denom>0.){
      dt =0.5*(amp3-amp1)/denom  ;
    }
    else {
      //printf("denom =%f\n",denom)  ;
      dt=0.5  ;
    }
/*                                           */        
/* ampmax correspond au maximum d'amplitude parabolique et dt        */
/* decalage en temps par rapport au sample maximum soit k + dt       */
        
    parout[0] =amp2+(amp3-amp1)*dt*0.25 ;
    parout[1] = (double)imax + dt ;
    parout[2] = (double)imax ;
return denom ;
}

Double_t TFParams::polfit	(	Int_t	ns,
		Int_t	imax,
		Double_t	par3d[10],
		Double_t	errpj[30][30],
		double *	adcpj
	)

Definition at line 821 of file TFParams.cc.

References dimmat, dimout, h, and i.

 {
  double val , val2 , val3 , adfmx[dimmat] , parfp3[dimout]  ;
  double ius[dimmat], maskp3[dimmat] ;
  double deglib,fit3,tm,h,xki2 ;
  int i ,nus ,ilow,isup ;
  val=adcpj[imax] ;
  val2=val/2.  ;
  val3=val/3.  ;
  ilow=0       ;
  isup=ns    ;
  deglib=-4.  ;
  for (i=0 ; i<ns ; i++ ){
    deglib=deglib+1.  ;
    ius[i] = 1. ;
    if((adcpj[i] < val3) && (i<imax) ){
      ilow=i  ;
    }
    if(adcpj[i] > val2 ){
      isup=i  ;
    }
  }
  ilow=ilow+1   ;
  if(ilow == imax )ilow=ilow-1 ;
  if(isup-ilow < 3) isup=ilow+3 ;
  nus=0  ;
  for(i=ilow ; i<=isup ; i++){
    
    adfmx[nus]=adcpj[i]  ;
    maskp3[nus] =0. ;
    if(ius[i] == 1) {
      maskp3[nus]=1. ;
      nus=nus+1    ;
    }
  }
  if(nus < 4) return 10000. ;
  xki2 =  f3deg (  nus , parfp3 ,  maskp3 , adfmx ,  errpj ) ;
  tm= parfp3[4]  ;
  h=parfp3[5] ;
  tm=tm+(double)ilow  ;
  par3d[0] = h ;
  par3d[1] = tm ;
  fit3 = xki2 ;
  return fit3 ;
}

void TFParams::print_mat

(

matrice

M

)

Definition at line 736 of file TFParams.cc.

References matrice::coeff, i, j, matrice::nb_colonnes, matrice::nb_lignes, NULL, and reco::return().

{
  int i,j ;
  if( M.coeff == NULL) 
  {
    printf(" erreur : affichage d'une matrice vide \n") ;
    return;
  }
  printf(" m_nli %d M_ncol %d \n",M.nb_lignes,M.nb_colonnes) ;
  for(i=0 ; i< M.nb_lignes; i++) {
    for(j=0 ; j< M.nb_colonnes ; j++) 
      printf(" MATRICE i= %d j= %d ---> %e \n",i,j,M.coeff[i][j]) ;
  }
  //printf(" apres passage d'impression \n") ;
  return ;
}

void TFParams::print_mat_nk	(	matrice	M,
		int	nk
	)

Definition at line 766 of file TFParams.cc.

References matrice::coeff, j, matrice::nb_colonnes, matrice::nb_lignes, NULL, and reco::return().

{
  int j ;
  if( M.coeff == NULL)
    printf(" erreur : affichage d'une matrice vide \n") ;
  printf(" nk = %d m_nli %d M_ncol %d \n",nk,M.nb_lignes,M.nb_colonnes) ;
    for(j=0 ; j< M.nb_colonnes ; j++) 
      printf(" MATRICE nk= %d j= %d  ---> %e \n",nk,j,M.coeff[nk][j]) ;    
  printf(" apres passage d'impression \n") ;
  return ;
}

void TFParams::produit_mat	(	matrice	A,
		matrice	B,
		matrice	M
	)

Definition at line 566 of file TFParams.cc.

References matrice::coeff, i, j, relval_2017::k, matrice::nb_colonnes, matrice::nb_lignes, NULL, and reco::return().

{
  int i,j,k ;
//  resultat du produit A*B = M 
  if(A.nb_colonnes != B.nb_lignes) {
    printf( " Erreur : produit de matrices de tailles incompatibles \n ");
    M.coeff = NULL ;
    return ;
  }
  M.nb_lignes = A.nb_lignes ;
  M.nb_colonnes = B.nb_colonnes ;
  zero_mat(M) ;
  for(i=0 ; i< M.nb_lignes; i++) {
    for(j=0 ; j< M.nb_colonnes ; j++) {
      for(k=0 ; k< A.nb_colonnes; k++){
    M.coeff[i][j] += A.coeff[i][k]*B.coeff[k][j] ;
      }
    }
  }
  return  ;
}

void TFParams::produit_mat_int	(	matrice	A,
		matrice	B,
		matrice	M
	)

Definition at line 588 of file TFParams.cc.

References matrice::coeff, i, j, relval_2017::k, matrice::nb_colonnes, matrice::nb_lignes, NULL, and reco::return().

{
  int i,j,k ;
  if(A.nb_colonnes != B.nb_lignes) {
    printf( " Erreur : produit de matrices de tailles incompatibles \n ");
    M.coeff = NULL ;
    return ;
  }
  M.nb_lignes = A.nb_lignes ;
  M.nb_colonnes = B.nb_colonnes ;
  for(i=0 ; i< M.nb_lignes; i++) {
    for(j=0 ; j< M.nb_colonnes ; j++) {
      for(k=0 ; k< A.nb_colonnes; k++){
    M.coeff[i][j] += A.coeff[i][k]*B.coeff[k][j] ;
      }
    }
  }
  return  ;
}

double TFParams::pulseShapepj	(	Double_t *	x,
		Double_t *	par
	)

Definition at line 1046 of file TFParams.cc.

References alpha, beta, dt, create_public_lumi_plots::exp, h, and funct::pow().

{

  Double_t fitfun;
  Double_t ped, h, tm, alpha, beta;
  Double_t  dt, dtsbeta, albet, variab, puiss;
  Double_t b1,b2,a1,a2 ;
  b1 = par[0] ;
  b2 = par[1] ;
  a1 = par[2] ;
  a2 = par[3] ;

  ped   =  0. ;
  h     =  b1 ;
  tm    =  b2 ;
  alpha =  a1 ;
  beta  =  a2 ;
  dt= x[0] - tm  ;
  //printf(" par %f %f %f %f dt = %f albet = %f",b1,b2,a1,a2,dt,albet) ;
  albet = alpha*beta ;
  if( albet <= 0 )return( (Double_t)0. );

  if(dt > -albet)  {
    dtsbeta=dt/beta ;
    variab=1.+dt/albet ;
    puiss=pow(variab,alpha);
    fitfun=h*puiss*exp(-dtsbeta) + ped;
    //printf(" dt = %f h = %f puiss = %f exp(-dtsbeta) %f \n",dt,h,puiss,
    // exp(-dtsbeta)) ;
     }
  else {
      fitfun = ped;
     }

  return fitfun;
}

Double_t TFParams::pulseShapepj2	(	Double_t *	x,
		Double_t *	par
	)

Definition at line 1119 of file TFParams.cc.

References alpha, beta, dt, create_public_lumi_plots::exp, h, and funct::pow().

{

  Double_t fitfun;
  Double_t ped, h, /*tm,*/ alpha, beta;
  Double_t  dt, dtsbeta, albet, variab, puiss;
  Double_t b1,/*b2,*/a1,a2 ;
  b1 = par[0] ;
  //b2 = par[1] ;
  a1 = par[2] ;
  a2 = par[3] ;
  ped   =  0. ;
  h     =  b1 ;
  //tm    =  b2 ;
  alpha =  a1 ;
  beta  =  a2 ;
  dt= x[0]  ;
  albet = alpha*beta ;
  if( albet <= 0 )return( (Double_t)0. );

  if(dt > -albet)  {
    dtsbeta=dt/beta ;
    variab=1.+dt/albet ;
    puiss=pow(variab,alpha);
    fitfun=h*puiss*exp(-dtsbeta) + ped;
  }
  else {
    fitfun = ped;
  }

  /*  printf( "fitfun %f %f %f %f, %f %f %f\n", ped, h, tm, alpha, beta, *x, fitfun );  */

  return fitfun;
}

void TFParams::set_const	(	int	n_samples,
		int	sample_min,
		int	sample_max,
		double	alpha,
		double	beta,
		int	nevtmaximum
	)

Definition at line 552 of file TFParams.cc.

References alpha, beta, and SDIM2.

Referenced by TShapeAnalysis::computeShape().

                                                     {
/*------------------------------------------------------------------------*/
  ns      = n_samples;
  nsmin   = sample_min ;
  nsmax   = sample_max ;
  nevtmax = nevtmaximum ;
  a1ini = alpha ;
  a2ini = 0.0 ;
  a3ini = beta ;
  step_shape = .04;
  METHODE = 2;
  if(ns > SDIM2) printf("warning: NbOfsamples exceed maximum\n");
} 

void TFParams::somme_mat_int	(	matrice	A,
		matrice	M
	)

Definition at line 643 of file TFParams.cc.

References matrice::coeff, i, j, matrice::nb_colonnes, matrice::nb_lignes, NULL, and reco::return().

{
  int i,j;
 /* resultat de la somme integree M += A */
  if(A.nb_lignes != M.nb_lignes) {
    printf( " Erreur : somme de matrices de tailles incompatibles \n ");
    M.coeff = NULL ;
    return ;
  }
  M.nb_lignes = A.nb_lignes ;
  M.nb_colonnes = A.nb_colonnes ;
  for(i=0 ; i< M.nb_lignes; i++) {
    for(j=0 ; j< M.nb_colonnes ; j++) 
      M.coeff[i][j] += A.coeff[i][j] ;
  }
  return  ;
}

void TFParams::somme_mat_int_scale	(	matrice	A,
		matrice	M,
		double	delta
	)

Definition at line 660 of file TFParams.cc.

References matrice::coeff, i, j, matrice::nb_colonnes, matrice::nb_lignes, and reco::return().

{
  int i,j ;
  M.nb_lignes = A.nb_lignes ;
  M.nb_colonnes = A.nb_colonnes ;
  for(i=0 ; i< M.nb_lignes; i++) {
    for(j=0 ; j< M.nb_colonnes ; j++) M.coeff[i][j] += A.coeff[i][j]*delta ;
    }
  return  ;
}

void TFParams::transpose_mat	(	matrice	A,
		matrice	M
	)

Definition at line 670 of file TFParams.cc.

References matrice::coeff, i, j, matrice::nb_colonnes, matrice::nb_lignes, and reco::return().

{
  int i,j;
// resultat de la transposition = matrice M 
  for(i=0 ; i< A.nb_lignes; i++) {
    for(j=0 ; j< A.nb_colonnes ; j++) {
    M.coeff[j][i] = A.coeff[i][j]  ;
    }
  }
  return  ;
}

void TFParams::zero_mat

(

matrice

M

)

Definition at line 752 of file TFParams.cc.

References matrice::coeff, i, j, matrice::nb_colonnes, matrice::nb_lignes, and reco::return().

{
  int i,j ;
  for(i=0 ; i< M.nb_lignes; i++) {
    for(j=0 ; j< M.nb_colonnes ; j++) M.coeff[i][j]=0. ; 
  }
  return ;
}

void TFParams::zero_mat_nk	(	matrice	M,
		int	nk
	)

Definition at line 760 of file TFParams.cc.

References matrice::coeff, j, and matrice::nb_colonnes.

{
  int j ;
    for(j=0 ; j< M.nb_colonnes ; j++) M.coeff[nk][j]=0. ;
  return ;
}

Member Data Documentation

double TFParams::a1ini

private

Definition at line 55 of file TFParams.h.

double TFParams::a2ini

private

Definition at line 56 of file TFParams.h.

double TFParams::a3ini

private

Definition at line 57 of file TFParams.h.

double TFParams::adclu[26]

private

Definition at line 59 of file TFParams.h.

int TFParams::METHODE

private

Definition at line 61 of file TFParams.h.

char TFParams::name_mat[10]

Definition at line 79 of file TFParams.h.

int TFParams::nevtmax

private

Definition at line 54 of file TFParams.h.

int TFParams::ns

private

Definition at line 51 of file TFParams.h.

int TFParams::nsmax

private

Definition at line 53 of file TFParams.h.

int TFParams::nsmin

private

Definition at line 52 of file TFParams.h.

double TFParams::step_shape

private

Definition at line 58 of file TFParams.h.

double TFParams::weight_matrix[10][10]

private

Definition at line 60 of file TFParams.h.