void rf315_projectpdf()
{
std::unique_ptr<RooAbsData>
data{
modelx->generateBinned(
x, 1000)};
TH1 *
hh = model.createHistogram(
"x,y");
TCanvas *
c =
new TCanvas(
"rf315_projectpdf",
"rf315_projectpdf", 800, 400);
gPad->SetLeftMargin(0.15);
gPad->SetLeftMargin(0.20);
hh->GetZaxis()->SetTitleOffset(2.5);
}
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
Abstract interface for all probability density functions.
static RooNumIntConfig * defaultIntegratorConfig()
Returns the default numeric integration configuration for all RooAbsReals.
RooArgSet is a container object that can hold multiple RooAbsArg objects.
Plot frame and a container for graphics objects within that frame.
static RooPlot * frame(const RooAbsRealLValue &var, double xmin, double xmax, Int_t nBins)
Create a new frame for a given variable in x.
void Draw(Option_t *options=nullptr) override
Draw this plot and all of the elements it contains.
A RooAbsReal implementing a polynomial in terms of a list of RooAbsReal coefficients.
Efficient implementation of a product of PDFs of the form.
Variable that can be changed from the outside.
virtual void SetTitleOffset(Float_t offset=1)
Set distance between the axis and the axis title.
TH1 is the base class of all histogram classes in ROOT.
The namespace RooFit contains mostly switches that change the behaviour of functions of PDFs (or othe...
[#0] WARNING:InputArguments -- The parameter 'sigmax' with range [-inf, inf] of the RooGaussian 'gaussx' exceeds the safe range of (0, inf). Advise to limit its range.
[#1] INFO:NumericIntegration -- RooRealIntegral::init(SPECINT[gaussy_NORM[y]_X_gaussx_NORM[x]]_Int[y]) using numeric integrator RooIntegrator1D to calculate Int(y)
[#1] INFO:Fitting -- RooAbsPdf::fitTo(model_Int[y]_Norm[x,y]_wrapped_pdf) 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 892.343 μs
[#1] INFO:Fitting -- RooAddition::defaultErrorLevel(nll_model_Int[y]_Norm[x,y]_wrapped_pdf_genData) Summation contains a RooNLLVar, using its error level
[#0] WARNING:Minimization -- RooAbsMinimizerFcn::synchronize: WARNING: no initial error estimate available for a1: using 0.4
[#1] INFO:Minimization -- [fitFCN] No discrete parameters, performing continuous minimization only
[#1] INFO:NumericIntegration -- RooRealIntegral::init(SPECINT[gaussy_NORM[y]_X_gaussx_NORM[x]]_Int[y]) using numeric integrator RooIntegrator1D to calculate Int(y)
prevFCN = 1900.156536 a1=-1.488,
prevFCN = 1899.96972 a1=-1.512,
prevFCN = 1900.566064 a1=-1.499,
prevFCN = 1900.127678 a1=-1.501,
prevFCN = 1900.187622 a1=-1.484,
prevFCN = 1899.958651 a1=-1.483,
prevFCN = 1899.959674 a1=-1.484,
prevFCN = 1899.958586 a1=-1.484,
prevFCN = 1899.958651 a1=-1.483,
prevFCN = 1899.959674 a1=-1.484,
prevFCN = 1899.958586 a1=-1.483,
prevFCN = 1899.958779 a1=-1.484,
prevFCN = 1899.958562 a1=-1.484,
prevFCN = 1899.958651 a1=-1.483,
prevFCN = 1899.958779 a1=-1.484,
prevFCN = 1899.958562 a1=-1.484,
prevFCN = 1899.958674 a1=-1.484,
prevFCN = 1899.95863 a1=-1.484, [#1] INFO:NumericIntegration -- RooRealIntegral::init(SPECINT[gaussy_NORM[y]_X_gaussx_NORM[x]]_Int[y]) using numeric integrator RooIntegrator1D to calculate Int(y)