void rf105_funcbinding()
{
RooPlot *
frame1 =
x.frame(Title(
"TMath::Erf bound as RooFit function"));
beta->Print();
std::unique_ptr<RooDataSet>
data{beta->generate(
x2, 10000)};
beta->fitTo(*
data, PrintLevel(-1));
TF1 *
fa1 =
new TF1(
"fa1",
"sin(x)/x", 0, 10);
TCanvas *
c =
new TCanvas(
"rf105_funcbinding",
"rf105_funcbinding", 1200, 400);
gPad->SetLeftMargin(0.15);
frame1->GetYaxis()->SetTitleOffset(1.6);
gPad->SetLeftMargin(0.15);
frame2->GetYaxis()->SetTitleOffset(1.6);
gPad->SetLeftMargin(0.15);
frame3->GetYaxis()->SetTitleOffset(1.6);
}
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
Option_t Option_t TPoint TPoint const char x2
Abstract interface for all probability density functions.
Abstract base class for objects that represent a real value and implements functionality common to al...
Plot frame and a container for graphics objects within that frame.
Variable that can be changed from the outside.
double beta_pdf(double x, double a, double b)
Probability density function of the beta distribution.
The namespace RooFit contains mostly switches that change the behaviour of functions of PDFs (or othe...
Double_t Erf(Double_t x)
Computation of the error function erf(x).
RooCFunction1Binding<double,double>::erf[ function=TMath::Erf x=x ] = 0
RooCFunction3PdfBinding<double,double,double,double>::beta[ function=(0x7f0960d1fd20) x=x2 y=a z=b ] = 0.934689
[#1] INFO:NumericIntegration -- RooRealIntegral::init(beta_Int[x2]) using numeric integrator RooIntegrator1D to calculate Int(x2)
[#1] INFO:NumericIntegration -- RooRealIntegral::init(beta_Int[x2]) using numeric integrator RooIntegrator1D to calculate Int(x2)
[#1] INFO:Fitting -- RooAbsPdf::fitTo(beta_over_beta_Int[x2]) fixing normalization set for coefficient determination to observables in data
[#1] INFO:Fitting -- using CPU computation library compiled with -mavx2
[#1] INFO:Fitting -- RooAddition::defaultErrorLevel(nll_beta_over_beta_Int[x2]_betaData) Summation contains a RooNLLVar, using its error level
[#1] INFO:Minimization -- RooAbsMinimizerFcn::setOptimizeConst: activating const optimization
[#1] INFO:NumericIntegration -- RooRealIntegral::init(beta_Int[x2]) using numeric integrator RooIntegrator1D to calculate Int(x2)
[#1] INFO:Minimization -- RooAbsMinimizerFcn::setOptimizeConst: deactivating const optimization
[#1] INFO:NumericIntegration -- RooRealIntegral::init(beta_Int[x2]) using numeric integrator RooIntegrator1D to calculate Int(x2)
RooTFnBinding::fa1[ TFn={fa1=sin(x)/x} obs=(x3) ] = -0.0547936