double HiggsPlot::ProbChi2(int iDecay, double tBmH, double RD[2], double RDs[2]){
double chi2;
double valMeas[3][2] = {{Measurement[0][0], Measurement[1][0]},
{MeasuredRD[0]->Eval(tBmH), MeasuredRD[2]->Eval(tBmH)},
{MeasuredRD[1]->Eval(tBmH), MeasuredRD[3]->Eval(tBmH)}};
int ndof=1;
if(iDecay<3) {
chi2 = Chi2(RD,valMeas[iDecay]);
} else {
TMatrixT<double> CovM(2,2), DiffRD(1,2), MDiff(1,2); //CovM is the covariance matrix
if(_varyRD){
CovM(0,0) = pow(RD[1],2) +pow(valMeas[1][1],2);
CovM(1,1) = pow(RDs[1],2)+pow(valMeas[2][1],2);
CovM(1,0) = Measurement[3][0]*valMeas[1][1]*valMeas[2][1];
DiffRD(0,0) = valMeas[1][0]-RD[0]; DiffRD(0,1) = valMeas[2][0]-RDs[0];
} else {
CovM(0,0) = pow(RD[1],2) +pow(Measurement[1][1],2);
CovM(1,1) = pow(RDs[1],2)+pow(Measurement[2][1],2);
CovM(1,0) = Measurement[3][0]*Measurement[1][1]*Measurement[2][1];
DiffRD(0,0) = Measurement[1][0]-RD[0]; DiffRD(0,1) = Measurement[2][0]-RDs[0];
}
CovM(0,1) = CovM(1,0);
CovM.Invert();
MDiff.Mult(DiffRD,CovM);
chi2 = MDiff(0,0)*DiffRD(0,0) + MDiff(0,1)*DiffRD(0,1);
ndof++;
if(tBmH==0 && _varyRD)
cout<<endl<<"SM chi2 is "<<RoundNumber(chi2,2)<<" with a p-value of "<<TMath::Prob(chi2,ndof)<<". This is "
<<RoundNumber(sqrt(2)*TMath::ErfInverse(1 - TMath::Prob(chi2,ndof)),2)<<" sigma away"<<endl<<endl;
}
return 1 - TMath::Prob(chi2,ndof);
}
double Verosimilitud::LLH(std::vector<double> param)
{
dlib::matrix<double,0,1> nuisance(4);
nuisance(0)=(param)[0];
nuisance(1)=(param)[1];
nuisance(2)=(param)[2];
nuisance(3)=(param)[3];
return Chi2(nuisance);
}
double HiggsPlot::ProbChi2(int iDecay, double tBmH, double rL){
double RD[2], RDs[2], chi2;
double valMeas[3][2] = {{Measurement[0][0], Measurement[1][0]},
{MeasuredRD[0]->Eval(tBmH), MeasuredRD[2]->Eval(tBmH)},
{MeasuredRD[1]->Eval(tBmH), MeasuredRD[3]->Eval(tBmH)}};
int ndof=1;
if(iDecay<3) {
Compute(tBmH,RD,iDecay);
chi2 = Chi2(RD,valMeas[iDecay]);
} else {
if(iDecay==3) {Compute(tBmH,RD,1); Compute(tBmH,RDs,2);}
else {
double mb = 4.2, rRrL = tBmH + rL, tBmH_Eff = sqrt(fabs(rRrL/(mTau*mb)));
if(rRrL > 0) RDCoef[0][0][1] = fabs(RDCoef[0][0][1]);
Compute(tBmH_Eff,RD,1);
valMeas[1][0] = MeasuredRD[0]->Eval(tBmH_Eff);
valMeas[1][1] = MeasuredRD[2]->Eval(tBmH_Eff);
rRrL = tBmH - rL; tBmH_Eff = sqrt(fabs(rRrL/(mTau*mb)));
if(rRrL > 0) RDCoef[1][0][1] = fabs(RDCoef[1][0][1]);
Compute(tBmH_Eff,RDs,2);
RDCoef[0][0][1] = -fabs(RDCoef[0][0][1]); RDCoef[1][0][1] = -fabs(RDCoef[1][0][1]);
valMeas[2][0] = MeasuredRD[1]->Eval(tBmH_Eff);
valMeas[2][1] = MeasuredRD[3]->Eval(tBmH_Eff);
// cout<<RoundNumber(RD[0],3)<<" +- "<<RoundNumber(RD[1],3)<<", "
// <<RoundNumber(RDs[0],3)<<" +- "<<RoundNumber(RDs[1],3)<<" at tBmH = "<<tBmH_Eff<<endl;
}
//if(tBmH==0) {RD[0] = 0.316; RD[1] = 0.014;} // MILC 2012
//if(tBmH==0) {RD[0] = 0.302; RD[1] = 0.016;} // Tanaka 2010
//if(tBmH==0) {RD[0] = 0.310; RD[1] = 0.020;} // Nierste 2008
TMatrixT<double> CovM(2,2), DiffRD(1,2), MDiff(1,2); //CovM is the covariance matrix
if(_varyRD){
CovM(0,0) = pow(RD[1],2) +pow(valMeas[1][1],2);
CovM(1,1) = pow(RDs[1],2)+pow(valMeas[2][1],2);
CovM(1,0) = Measurement[3][0]*valMeas[1][1]*valMeas[2][1];
DiffRD(0,0) = valMeas[1][0]-RD[0]; DiffRD(0,1) = valMeas[2][0]-RDs[0];
} else {
CovM(0,0) = pow(RD[1],2) +pow(Measurement[1][1],2);
CovM(1,1) = pow(RDs[1],2)+pow(Measurement[2][1],2);
CovM(1,0) = Measurement[3][0]*Measurement[1][1]*Measurement[2][1];
DiffRD(0,0) = Measurement[1][0]-RD[0]; DiffRD(0,1) = Measurement[2][0]-RDs[0];
}
CovM(0,1) = CovM(1,0);
CovM.Invert();
MDiff.Mult(DiffRD,CovM);
chi2 = MDiff(0,0)*DiffRD(0,0) + MDiff(0,1)*DiffRD(0,1);
ndof++;
// if(tBmH==0 && _varyRD)
// cout<<endl<<"SM chi2 is "<<RoundNumber(chi2,2)<<" with a p-value of "<<TMath::Prob(chi2,ndof)<<". This is "
// <<RoundNumber(sqrt(2)*TMath::ErfInverse(1 - TMath::Prob(chi2,ndof)),2)<<" sigma away"<<endl<<endl;
}
return 1 - TMath::Prob(chi2,ndof);
}
std::vector<double> Verosimilitud::MinLLH(std::vector<double> param, std::vector<double> low_bound, std::vector<double> high_bound, std::vector<bool> param_to_minimize)
{
if(param.size() != param_to_minimize.size()){
std::cout << "sizes param do not match. break" <<std::endl;
exit(1);
}
if(low_bound.size() != param_to_minimize.size()){
std::cout << "sizes low do not match. break" <<std::endl;
exit(1);
}
if(high_bound.size() != param_to_minimize.size()){
std::cout << "sizes high do not match. break" <<std::endl;
exit(1);
}
unsigned int number_of_parameters_to_minimize = std::count(param_to_minimize.begin(),param_to_minimize.end(),true);
//set initial values and boundaries
dlib::matrix<double,0,1> nuisance(number_of_parameters_to_minimize);
dlib::matrix<double,0,1> lo_bounds(number_of_parameters_to_minimize);
dlib::matrix<double,0,1> hi_bounds(number_of_parameters_to_minimize);
unsigned int j=0;
for(unsigned int i=0; i<param.size(); i++){
if(param_to_minimize[i]){
nuisance(j)=param[i];
lo_bounds(j)=low_bound[i];
hi_bounds(j)=high_bound[i];
j++;
}
}
/* all ok
std::cout << "Input" << std::endl;
std::cout << nuisance << std::endl;
std::cout << lo_bounds << std::endl;
std::cout << hi_bounds << std::endl;
*/
// dlib::find_min_box_constrained(dlib::bfgs_search_strategy(),
// dlib::objective_delta_stop_strategy(1e-7),
// Chi2_caller(this,param,param_to_minimize),
// Chi2grad_caller(this,param,param_to_minimize),
// nuisance,
// lo_bounds,
// hi_bounds);
dlib::find_min_box_constrained(dlib::lbfgs_search_strategy(10),
dlib::gradient_norm_stop_strategy(1e-1),
Chi2_caller(this,param,param_to_minimize),
Chi2grad_caller(this,param,param_to_minimize),
nuisance,
lo_bounds,
hi_bounds);
std::vector<double> ret(param.size()+1,0);
dlib::matrix<double,0,1> param_eval(param.size());
unsigned int jj=0;
for (unsigned int i=0; i<param.size(); i++){
if(param_to_minimize[i]){
ret[i] = nuisance(jj);
param_eval(i) = nuisance(jj);
jj++;
} else {
ret[i] = param[i];
param_eval(i) = param[i];
}
}
ret[param.size()] = Chi2(param_eval);
return ret;
}
/////////////////////////////////
// y := observables
// x := gen level quantities
// type := decides the TF
/////////////////////////////////
double MEM::transfer_function(double* y, double* x, const TFType::TFType& type, int& out_of_range, const double& cutoff, const int& debug){
// return value
double w{1.};
// temporary values;
double E, H;
double m1,s1, m2, s2, f, rho, c1, c2;
// parameters
const double* par;
switch( type ){
case TFType::bReco:
// x[0] = parton energy ;
// x[1] = parton eta;
// y[0] = jet energy;
E = x[0];
H = x[1];
par = TF_B_param[ eta_to_bin(H) ];
f = par[10];
m1 = par[0] + par[1]*E;
m2 = par[5] + par[6]*E;
s1 = E*TMath::Sqrt(par[2]*par[2] + par[3]*par[3]/E + par[4]*par[4]/E/E);
s2 = E*TMath::Sqrt(par[7]*par[7] + par[8]*par[8]/E + par[9]*par[9]/E/E);
c1 = Chi2(y[0], m1, s1);
c2 = Chi2(y[0], m2, s2);
if( c1>cutoff && c2>cutoff ) ++out_of_range;
w *= (1./sqrt(2*PI) * (f/s1*TMath::Exp(-0.5*c1) + (1-f)/s2*TMath::Exp(-0.5*c2) ));
#ifdef DEBUG_MODE
if( debug&DebugVerbosity::integration)
cout << "\t\ttransfer_function: Evaluate W(" << y[0] << " | E=" << E << ", y=" << H << ", TFType::bReco) = " << w << endl;
#endif
break;
case TFType::qReco:
// x[0] = parton energy ;
// x[1] = parton eta;
// y[0] = jet energy;
E = x[0];
H = x[1];
par = TF_Q_param[ eta_to_bin(H) ];
m1 = par[0] + par[1]*E;
s1 = E*TMath::Sqrt(par[2]*par[2] + par[3]*par[3]/E + par[4]*par[4]/E/E);
c1 = Chi2(y[0], m1, s1);
if( c1>cutoff ) ++out_of_range;
w *= (1./sqrt(2*PI)/s1*TMath::Exp(-0.5*c1));
#ifdef DEBUG_MODE
if( debug&DebugVerbosity::integration)
cout << "\t\ttransfer_function: Evaluate W(" << y[0] << " | E=" << E << ", y=" << H << ", TFType::qReco) = " << w << endl;
#endif
break;
case TFType::MET:
// x[0] = sum nu_x ; x[1] = sum nu_y
// y[0] = MET_x ; y[1] = MET_y
par = TF_MET_param;
s1 = par[0];
s2 = par[1];
rho = par[2];
c1 = Chi2Corr(y[0]-x[0], y[1]-x[1], s1, s2, rho);
if( c1/2>cutoff ) ++out_of_range;
w *= 1./(2*PI)/s1/s2/sqrt(1.-rho*rho)*TMath::Exp( -0.5*c1 );
#ifdef DEBUG_MODE
if( debug&DebugVerbosity::integration)
cout << "\t\ttransfer_function: Evaluate W(" << y[0] << "-" << x[0] << " , " << y[1] << "-" << x[1] << ", TFType::MET) = " << w << endl;
#endif
break;
case TFType::Recoil:
// Sudakov factor
// x[0] = pT
// y[0] = rhoT if extra_jets==0, else par[2]+1GeV
par = TF_RECOIL_param;
m1 = par[0];
s1 = par[1];
if( y[0] < par[2] )
w *= TMath::Gaus( log(x[0]), m1, s1, 1 );
else
w *= 1.;
#ifdef DEBUG_MODE
if( debug&DebugVerbosity::integration)
cout << "\t\ttransfer_function: Evaluate W( log(" << x[0] << "); TFType::Recoil) = " << w << endl;
#endif
break;
case TFType::bLost:
case TFType::qLost:
// x[0] = parton energy ;
// x[1] = parton eta;
// y[0] = jet energy
// par: [0]-> eta acceptance, [1]-> pT cut, [2]-> E max, [3]->acceptance (cos*phi)
if( TMath::Abs(x[1])>TF_ACC_param[0] ){
w *= 1.;
#ifdef DEBUG_MODE
if( debug&DebugVerbosity::integration)
cout << "\t\ttransfer_function: Evaluate W(" << x[0] << ", " << x[1] << ", TFType::qLost) = " << w << endl;
#endif
}
else{
// x[0] = parton energy ;
// x[1] = parton eta
// y[0] = 0.
E = x[0];
H = x[1];
par = TF_Q_param[ eta_to_bin(H) ];
double mean_e = (par[0] + par[1]*E);
double sigma_e = E*TMath::Sqrt(par[2]*par[2] + par[3]*par[3]/E + par[4]*par[4]/E/E);
double sign = (TF_ACC_param[1]*TMath::CosH(H) >= mean_e) ? +1. : -1.;
c1 = Chi2( TF_ACC_param[1]*TMath::CosH(H), mean_e, sigma_e);
if( c1>cutoff ) ++out_of_range;
w *= 0.5*(TMath::Erf( sqrt(c1/2.)*sign ) + 1 ) ;
#ifdef DEBUG_MODE
if( debug&DebugVerbosity::integration)
cout << "\t\ttransfer_function: Evaluate W(" << TF_ACC_param[1] << " | " << E << ", " << H << ", TFType::qLost) = " << w << endl;
#endif
}
break;
case TFType::Unknown:
w *= 1.;
#ifdef DEBUG_MODE
if( debug&DebugVerbosity::integration)
cout << "\t\ttransfer_function: Evaluate W = 1 " << endl;
#endif
break;
default:
break;
}
return w;
}
double MEM::Chi2Corr(const double& x, const double& y, const double& sx, const double& sy, const double& rho){
return 1./(1-rho*rho)*( Chi2(x,0.,sx) + Chi2(y,0.,sy) - 2*rho*x*y/sx/sy ) ;
}
