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rf103_interprfuncs.C File Reference

Detailed Description

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Basic functionality: interpreted functions and PDFs.

#include "RooRealVar.h"
#include "RooDataSet.h"
#include "RooGaussian.h"
#include "TCanvas.h"
#include "TAxis.h"
#include "RooPlot.h"
#include "RooFitResult.h"
#include "RooGenericPdf.h"
using namespace RooFit;
{
// ----------------------------------------------------
// G e n e r i c i n t e r p r e t e d p . d . f .
// ====================================================
// Declare observable x
RooRealVar x("x", "x", -20, 20);
// C o n s t r u c t g e n e r i c p d f f r o m i n t e r p r e t e d e x p r e s s i o n
// -------------------------------------------------------------------------------------------------
// To construct a proper pdf, the formula expression is explicitly normalized internally by dividing
// it by a numeric integral of the expression over x in the range [-20,20]
//
RooRealVar alpha("alpha", "alpha", 5, 0.1, 10);
RooGenericPdf genpdf("genpdf", "genpdf", "(1+0.1*abs(x)+sin(sqrt(abs(x*alpha+0.1))))", RooArgSet(x, alpha));
// S a m p l e , f i t a n d p l o t g e n e r i c p d f
// ---------------------------------------------------------------
// Generate a toy dataset from the interpreted pdf
std::unique_ptr<RooDataSet> data{genpdf.generate(x, 10000)};
// Fit the interpreted pdf to the generated data
genpdf.fitTo(*data, PrintLevel(-1));
// Make a plot of the data and the pdf overlaid
RooPlot *xframe = x.frame(Title("Interpreted expression pdf"));
data->plotOn(xframe);
genpdf.plotOn(xframe);
// -----------------------------------------------------------------------------------------------------------
// S t a n d a r d p . d . f a d j u s t w i t h i n t e r p r e t e d h e l p e r f u n c t i o n
// ==========================================================================================================
// Make a gauss(x,sqrt(mean2),sigma) from a standard RooGaussian
// C o n s t r u c t s t a n d a r d p d f w i t h f o r m u l a r e p l a c i n g p a r a m e t e r
// ------------------------------------------------------------------------------------------------------------
// Construct parameter mean2 and sigma
RooRealVar mean2("mean2", "mean^2", 10, 0, 200);
RooRealVar sigma("sigma", "sigma", 3, 0.1, 10);
// Construct interpreted function mean = sqrt(mean^2)
RooFormulaVar mean("mean", "mean", "sqrt(mean2)", mean2);
// Construct a gaussian g2(x,sqrt(mean2),sigma) ;
RooGaussian g2("g2", "h2", x, mean, sigma);
// G e n e r a t e t o y d a t a
// ---------------------------------
// Construct a separate gaussian g1(x,10,3) to generate a toy Gaussian dataset with mean 10 and width 3
RooGaussian g1("g1", "g1", x, 10.0, 3.0);
std::unique_ptr<RooDataSet> data2{g1.generate(x, 1000)};
// F i t a n d p l o t t a i l o r e d s t a n d a r d p d f
// -------------------------------------------------------------------
// Fit g2 to data from g1
std::unique_ptr<RooFitResult> fitResult{g2.fitTo(*data2, Save(), PrintLevel(-1))};
fitResult->Print();
// Plot data on frame and overlay projection of g2
RooPlot *xframe2 = x.frame(Title("Tailored Gaussian pdf"));
data2->plotOn(xframe2);
g2.plotOn(xframe2);
// Draw all frames on a canvas
TCanvas *c = new TCanvas("rf103_interprfuncs", "rf103_interprfuncs", 800, 400);
c->Divide(2);
c->cd(1);
gPad->SetLeftMargin(0.15);
xframe->GetYaxis()->SetTitleOffset(1.4);
xframe->Draw();
c->cd(2);
gPad->SetLeftMargin(0.15);
xframe2->GetYaxis()->SetTitleOffset(1.4);
xframe2->Draw();
}
#define c(i)
Definition RSha256.hxx:101
Option_t Option_t TPoint TPoint const char GetTextMagnitude GetFillStyle GetLineColor GetLineWidth GetMarkerStyle GetTextAlign GetTextColor GetTextSize void data
#define gPad
RooArgSet is a container object that can hold multiple RooAbsArg objects.
Definition RooArgSet.h:55
A RooFormulaVar is a generic implementation of a real-valued object, which takes a RooArgList of serv...
Plain Gaussian p.d.f.
Definition RooGaussian.h:24
Implementation of a probability density function that takes a RooArgList of servers and a C++ express...
Plot frame and a container for graphics objects within that frame.
Definition RooPlot.h:43
static RooPlot * frame(const RooAbsRealLValue &var, double xmin, double xmax, Int_t nBins)
Create a new frame for a given variable in x.
Definition RooPlot.cxx:237
TAxis * GetYaxis() const
Definition RooPlot.cxx:1276
void Draw(Option_t *options=nullptr) override
Draw this plot and all of the elements it contains.
Definition RooPlot.cxx:649
Variable that can be changed from the outside.
Definition RooRealVar.h:37
virtual void SetTitleOffset(Float_t offset=1)
Set distance between the axis and the axis title.
Definition TAttAxis.cxx:298
The Canvas class.
Definition TCanvas.h:23
RooCmdArg Save(bool flag=true)
RooCmdArg PrintLevel(Int_t code)
const Double_t sigma
Double_t x[n]
Definition legend1.C:17
The namespace RooFit contains mostly switches that change the behaviour of functions of PDFs (or othe...
Definition JSONIO.h:26
const char * Title
Definition TXMLSetup.cxx:68
[#1] INFO:NumericIntegration -- RooRealIntegral::init(genpdf_Int[x]) using numeric integrator RooIntegrator1D to calculate Int(x)
[#1] INFO:NumericIntegration -- RooRealIntegral::init(genpdf_Int[x]) using numeric integrator RooIntegrator1D to calculate Int(x)
[#1] INFO:Fitting -- RooAbsPdf::fitTo(genpdf_over_genpdf_Int[x]) 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_genpdf_over_genpdf_Int[x]_genpdfData) Summation contains a RooNLLVar, using its error level
[#1] INFO:Minimization -- RooAbsMinimizerFcn::setOptimizeConst: activating const optimization
[#1] INFO:NumericIntegration -- RooRealIntegral::init(genpdf_Int[x]) using numeric integrator RooIntegrator1D to calculate Int(x)
[#1] INFO:Minimization -- RooAbsMinimizerFcn::setOptimizeConst: deactivating const optimization
[#1] INFO:NumericIntegration -- RooRealIntegral::init(genpdf_Int[x]) using numeric integrator RooIntegrator1D to calculate Int(x)
[#1] INFO:Fitting -- RooAbsPdf::fitTo(g2_over_g2_Int[x]) fixing normalization set for coefficient determination to observables in data
[#1] INFO:Fitting -- RooAddition::defaultErrorLevel(nll_g2_over_g2_Int[x]_g1Data) Summation contains a RooNLLVar, using its error level
[#1] INFO:Minimization -- RooAbsMinimizerFcn::setOptimizeConst: activating const optimization
[#1] INFO:Minimization -- RooAbsMinimizerFcn::setOptimizeConst: deactivating const optimization
RooFitResult: minimized FCN value: 2551.39, estimated distance to minimum: 4.39288e-06
covariance matrix quality: Full, accurate covariance matrix
Status : MINIMIZE=0 HESSE=0
Floating Parameter FinalValue +/- Error
-------------------- --------------------------
mean2 1.0010e+02 +/- 1.98e+00
sigma 3.1172e+00 +/- 7.12e-02
Date
July 2008
Author
Wouter Verkerke

Definition in file rf103_interprfuncs.C.