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rf804_mcstudy_constr.C File Reference
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View in nbviewer Open in SWAN 'VALIDATION AND MC STUDIES' RooFit tutorial macro #804

Using RooMCStudy on models with constrains

pict1_rf804_mcstudy_constr.C.png
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RooFit v3.60 -- Developed by Wouter Verkerke and David Kirkby
Copyright (C) 2000-2013 NIKHEF, University of California & Stanford University
All rights reserved, please read http://roofit.sourceforge.net/license.txt
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[#1] INFO:NumericIntegration -- RooRealIntegral::init(pullGauss_Int[fpull]) using numeric integrator RooIntegrator1D to calculate Int(fpull)
[#1] INFO:Minization -- RooMinimizer::optimizeConst: activating const optimization
[#1] INFO:Minization -- RooMinimizer::optimizeConst: deactivating const optimization
[#1] INFO:NumericIntegration -- RooRealIntegral::init(pullGauss_Int[fpull]) using numeric integrator RooIntegrator1D to calculate Int(fpull)
#include "RooRealVar.h"
#include "RooDataSet.h"
#include "RooGaussian.h"
#include "RooConstVar.h"
#include "RooPolynomial.h"
#include "RooAddPdf.h"
#include "RooProdPdf.h"
#include "RooMCStudy.h"
#include "RooPlot.h"
#include "TCanvas.h"
#include "TAxis.h"
#include "TH1.h"
using namespace RooFit ;
void rf804_mcstudy_constr()
{
// C r e a t e m o d e l w i t h p a r a m e t e r c o n s t r a i n t
// ---------------------------------------------------------------------------
// Observable
RooRealVar x("x","x",-10,10) ;
// Signal component
RooRealVar m("m","m",0,-10,10) ;
RooRealVar s("s","s",2,0.1,10) ;
RooGaussian g("g","g",x,m,s) ;
// Background component
RooPolynomial p("p","p",x) ;
// Composite model
RooRealVar f("f","f",0.4,0.,1.) ;
RooAddPdf sum("sum","sum",RooArgSet(g,p),f) ;
// Construct constraint on parameter f
RooGaussian fconstraint("fconstraint","fconstraint",f,RooConst(0.7),RooConst(0.1)) ;
// Multiply constraint with p.d.f
RooProdPdf sumc("sumc","sum with constraint",RooArgSet(sum,fconstraint)) ;
// S e t u p t o y s t u d y w i t h m o d e l
// ---------------------------------------------------
// Perform toy study with internal constraint on f
RooMCStudy mcs(sumc,x,Constrain(f),Silence(),Binned(),FitOptions(PrintLevel(-1))) ;
// Run 500 toys of 2000 events.
// Before each toy is generated, a value for the f is sampled from the constraint pdf and
// that value is used for the generation of that toy.
mcs.generateAndFit(500,2000) ;
// Make plot of distribution of generated value of f parameter
TH1* h_f_gen = mcs.fitParDataSet().createHistogram("f_gen",-40) ;
// Make plot of distribution of fitted value of f parameter
RooPlot* frame1 = mcs.plotParam(f,Bins(40)) ;
frame1->SetTitle("Distribution of fitted f values") ;
// Make plot of pull distribution on f
RooPlot* frame2 = mcs.plotPull(f,Bins(40),FitGauss()) ;
frame1->SetTitle("Distribution of f pull values") ;
TCanvas* c = new TCanvas("rf804_mcstudy_constr","rf804_mcstudy_constr",1200,400) ;
c->Divide(3) ;
c->cd(1) ; gPad->SetLeftMargin(0.15) ; h_f_gen->GetYaxis()->SetTitleOffset(1.4) ; h_f_gen->Draw() ;
c->cd(2) ; gPad->SetLeftMargin(0.15) ; frame1->GetYaxis()->SetTitleOffset(1.4) ; frame1->Draw() ;
c->cd(3) ; gPad->SetLeftMargin(0.15) ; frame2->GetYaxis()->SetTitleOffset(1.4) ; frame2->Draw() ;
}
Author
07/2008 - Wouter Verkerke

Definition in file rf804_mcstudy_constr.C.