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/*****************************************************************************
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* Project: RooFit *
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* *
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* This code was autogenerated by RooClassFactory *
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*****************************************************************************/
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// Your description goes here...
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#include "Riostream.h"
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#include "RooSUSYCompleteBkgPdf.h"
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#include "RooAbsReal.h"
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#include "RooAbsCategory.h"
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#include "TMath.h"
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#include "RooRealVar.h"
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#include "RooComplex.h"
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#include "RooMath.h"
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//ClassImp(RooSUSYBkgPdf)
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//RooSUSYCompleteBkgPdf FullModel("FullModel","FullModel",mll, fttbaree, fttbarmm, par1ttbarOF, par2ttbarOF, par3ttbarOF, par4ttbarOF, meanz,widthz, sigmazee, sigmazmm, fzee, fzmm, par1signal, fsignalee, fsignalmm);
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RooSUSYCompleteBkgPdf::RooSUSYCompleteBkgPdf(const char *name, const char *title,
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RooAbsReal& _mll,
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RooAbsReal& _te,
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RooAbsReal& _tm,
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RooAbsReal& _t1,
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RooAbsReal& _t2,
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RooAbsReal& _t3,
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RooAbsReal& _t4,
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RooAbsReal& _meanz,
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RooAbsReal& _widthz,
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RooAbsReal& _sigmazee,
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RooAbsReal& _sigmazmm,
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RooAbsReal& _fzee,
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RooAbsReal& _fzmm,
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RooAbsReal& _s1,
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RooAbsReal& _s3,
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RooAbsReal& _sn) :
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RooAbsPdf(name,title),
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mll("mll","mll",this,_mll),
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te("te","te",this,_te),
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tm("tm","tm",this,_tm),
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t1("t1","t1",this,_t1),
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t2("t2","t2",this,_t2),
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t3("t3","t3",this,_t3),
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t4("t4","t4",this,_t4),
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meanz("meanz","meanz",this,_meanz),
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widthz("widthz","widthz",this,_widthz),
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sigmazee("sigmazee","sigmazee",this,_sigmazee),
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sigmazmm("sigmazmm","sigmazmm",this,_sigmazmm),
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fzee("fzee","fzee",this,_fzee),
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fzmm("fzmm","fzmm",this,_fzmm),
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s1("s1","s1",this,_s1),
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s3("s3","s3",this,_s3),
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sn("sn","sn",this,_sn)
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{
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}
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RooSUSYCompleteBkgPdf::RooSUSYCompleteBkgPdf(const RooSUSYCompleteBkgPdf& other, const char* name) :
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RooAbsPdf(other,name),
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mll("mll",this,other.mll),
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te("te",this,other.te),
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tm("tm",this,other.tm),
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t1("t1",this,other.t1),
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t2("t2",this,other.t2),
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t3("t3",this,other.t3),
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t4("t4",this,other.t4),
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meanz("meanz",this,other.meanz),
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widthz("widthz",this,other.widthz),
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sigmazee("sigmazee",this,other.sigmazee),
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sigmazmm("sigmazmm",this,other.sigmazmm),
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fzee("fzee",this,other.fzee),
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fzmm("fzmm",this,other.fzmm),
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s1("s1",this,other.s1),
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s3("s3",this,other.s3),
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sn("sn",this,other.sn)
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{
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}
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Double_t RooSUSYCompleteBkgPdf::Voigtian(float x, float sigma,float width,float mean) const
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{
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Double_t s = (sigma>0) ? sigma : -sigma ;
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Double_t w = (width>0) ? width : -width ;
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Double_t coef= -0.5/(s*s);
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Double_t arg = x - mean;
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// return constant for zero width and sigma
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if (s==0. && w==0.) return 1.;
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// Breit-Wigner for zero sigma
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if (s==0.) return (1./(arg*arg+0.25*w*w));
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// Gauss for zero width
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if (w==0.) return exp(coef*arg*arg);
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// actual Voigtian for non-trivial width and sigma
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Double_t c = 1./(sqrt(2.)*s);
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Double_t a = 0.5*c*w;
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Double_t u = c*arg;
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RooComplex z(u,a) ;
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RooComplex v(0.) ;
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v = RooMath::ComplexErrFunc(z);
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double _invRootPi=_invRootPi= 1./sqrt(atan2(0.,-1.));
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return c*_invRootPi*v.re();
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}
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Double_t RooSUSYCompleteBkgPdf::GetSignal(float c, float s, float m0) const
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{
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float value = c*(TMath::Sqrt(2)*s*(TMath::Exp(-mll*mll/(2*s*s))-TMath::Exp(-(m0-mll)*(m0-mll)/(2*s*s)))+mll*TMath::Sqrt(TMath::Pi())*(TMath::Erf(mll/(TMath::Sqrt(2)*s))+TMath::Erf((m0-mll)/(TMath::Sqrt(2)*s))));
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if(value>0) return value;
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else return 0.;
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}
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Double_t RooSUSYCompleteBkgPdf::TTNormalization() const
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{
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Double_t sum=0.0;
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for(float a=20.0;a<=300;a+=0.1) {
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sum+=TMath::Power(a,t1)*TMath::Exp(-t3*a);
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}
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return sum;
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}
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Double_t RooSUSYCompleteBkgPdf::DYNormalization(Double_t sigma) const
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{
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Double_t sum=0.0;
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for(float a=20.0;a<=300;a+=0.1) {
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sum+=RooSUSYCompleteBkgPdf::Voigtian(a,sigma,widthz,meanz);
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}
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return sum;
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}
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Double_t RooSUSYCompleteBkgPdf::evaluate() const
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{
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// ENTER EXPRESSION IN TERMS OF VARIABLE ARGUMENTS HERE
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// float TTNormalization=1.0/(-pow(300.0,t1)*expint(t1,300.0*t3)+pow(20.0,t1)*expint(t1,20.0*t3)); // 300 and 20 are the limits within which we want to have ttbar normalized!
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float TTNormalization=1.0/RooSUSYCompleteBkgPdf::TTNormalization();
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float eeVoigtianNormalization=1.0/RooSUSYCompleteBkgPdf::DYNormalization(sigmazee);
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float mmVoigtianNormalization=1.0/RooSUSYCompleteBkgPdf::DYNormalization(sigmazmm);
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float ttbaree=te*TTNormalization*TMath::Power(mll,t1)*TMath::Exp(-t3*mll);
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float ttbarmm=tm*TTNormalization*TMath::Power(mll,t1)*TMath::Exp(-t3*mll);
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float DYee = fzee*eeVoigtianNormalization*RooSUSYCompleteBkgPdf::Voigtian(mll,sigmazee,widthz,meanz);
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float DYmm = fzmm*mmVoigtianNormalization*RooSUSYCompleteBkgPdf::Voigtian(mll,sigmazmm,widthz,meanz);
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float sig_e = GetSignal(s1,sigmazee,s3);
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float sig_m = GetSignal(s1,sigmazmm,s3);
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float sig = sn * ( (te/(te+tm)) * sig_e + (tm/(te+tm)) * sig_m );
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if(mll>90&&mll<92) {
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// cout << "TTbar normalization : " << TTNormalization << endl;
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// cout << "t: " << te << " ; " << tm << " ; " << t1 << " ; " << t2 << " ; " << t3 << " ; " << t4 << endl;
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// cout << "dy: " << meanz << " ; " << widthz << " ; " << sigmazee << " ; " << sigmazmm << " ; " << fzee << " ; " << fzmm << endl;
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// cout << "s : " << s1 << " ; " << s3 << " ; " << sn << endl;
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cout << " CONTRIBUTIONS : (mll=" << mll << endl;
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cout << " ttbaree : " << ttbaree << endl;
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cout << " ttbarmm : " << ttbarmm << endl;
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cout << " dy ee : " << DYee << endl;
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cout << " dy mm : " << DYmm << endl;
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cout << " sig ee : " << sig_e << endl;
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cout << " sig mm : " << sig_m << endl;
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cout << " -> sig : " << sig << endl;
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cout << " full : " << ttbaree+ttbarmm+DYee+DYmm+sig << endl;
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}
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return ttbaree+ttbarmm+DYee+DYmm+sig;
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}
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