void rf605_profilell()
{
   
   
 
   
 
   
   RooRealVar mean(
"mean", 
"mean of g1 and g2", 0, -10, 10);
 
 
 
 
   
   std::unique_ptr<RooDataSet> 
data{model.generate(
x, 1000)};
 
 
   
   
 
   
   std::unique_ptr<RooAbsReal> nll{model.createNLL(*
data, NumCPU(2))};
 
 
   
 
   
 
   
 
   
   
 
   
   
 
   std::unique_ptr<RooAbsReal> 
pll_frac{
nll->createProfile(frac)};
 
 
   
 
   
 
   
   
 
   
   
 
   
 
   
 
   
   gPad->SetLeftMargin(0.15);
 
   frame1->GetYaxis()->SetTitleOffset(1.4);
 
   gPad->SetLeftMargin(0.15);
 
   frame2->GetYaxis()->SetTitleOffset(1.4);
 
}
ROOT::Detail::TRangeCast< T, true > TRangeDynCast
TRangeDynCast is an adapter class that allows the typed iteration through a TCollection.
 
Option_t Option_t TPoint TPoint const char GetTextMagnitude GetFillStyle GetLineColor GetLineWidth GetMarkerStyle GetTextAlign GetTextColor GetTextSize void data
 
Efficient implementation of a sum of PDFs of the form.
 
RooArgList is a container object that can hold multiple RooAbsArg objects.
 
Wrapper class around ROOT::Math::Minimizer that provides a seamless interface between the minimizer f...
 
int migrad()
Execute MIGRAD.
 
Plot frame and a container for graphics objects within that frame.
 
Variable that can be changed from the outside.
 
RooCmdArg Bins(Int_t nbin)
 
RooCmdArg LineColor(TColorNumber color)
 
double nll(double pdf, double weight, int binnedL, int doBinOffset)
 
The namespace RooFit contains mostly switches that change the behaviour of functions of PDFs (or othe...
 
   
[#0] WARNING:InputArguments -- The parameter 'sigma_g1' with range [-inf, inf] of the RooGaussian 'g1' exceeds the safe range of (0, inf). Advise to limit its range.
[#1] INFO:Fitting -- RooAbsPdf::fitTo(model) fixing normalization set for coefficient determination to observables in data
[#1] INFO:Fitting -- using generic CPU library compiled with no vectorizations
[#1] INFO:Fitting -- Creation of NLL object took 7.63764 ms
[#1] INFO:Fitting -- RooAddition::defaultErrorLevel(nll_model_modelData) Summation contains a RooNLLVar, using its error level
Minuit2Minimizer: Minimize with max-calls 1500 convergence for edm < 1 strategy 1
Minuit2Minimizer : Valid minimum - status = 0
FVAL  = 2659.73712858695399
Edm   = 0.000190395763129910388
Nfcn  = 60
frac    = 0.62118  +/-  0.165788 (limited)
mean    = 0.00442366  +/-  0.109372 (limited)
sigma_g2   = 4.10789  +/-  0.405468 (limited)
[#1] INFO:Minimization -- RooProfileLL::evaluate(RooEvaluatorWrapper_Profile[frac]) Creating instance of MINUIT
[#1] INFO:Fitting -- RooAddition::defaultErrorLevel(nll_model_modelData) Summation contains a RooNLLVar, using its error level
[#1] INFO:Minimization -- RooProfileLL::evaluate(RooEvaluatorWrapper_Profile[frac]) determining minimum likelihood for current configurations w.r.t all observable
[#1] INFO:Minimization -- RooProfileLL::evaluate(RooEvaluatorWrapper_Profile[frac]) minimum found at (frac=0.62104)
..................................................................................
[#1] INFO:Minimization -- RooProfileLL::evaluate(RooEvaluatorWrapper_Profile[sigma_g2]) Creating instance of MINUIT
[#1] INFO:Fitting -- RooAddition::defaultErrorLevel(nll_model_modelData) Summation contains a RooNLLVar, using its error level
[#1] INFO:Minimization -- RooProfileLL::evaluate(RooEvaluatorWrapper_Profile[sigma_g2]) determining minimum likelihood for current configurations w.r.t all observable
[#1] INFO:Minimization -- RooProfileLL::evaluate(RooEvaluatorWrapper_Profile[sigma_g2]) minimum found at (sigma_g2=4.11258)
....................................................................................