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Reference Guide
rs801_HypoTestInverterOriginal.C
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1 /// \file
2 /// \ingroup tutorial_roostats
3 /// \notebook -js
4 /// 'Hypothesis Test Inversion' RooStats tutorial macro #801
5 ///
6 /// This tutorial shows an example of using the HypoTestInverterOriginal class
7 ///
8 /// \macro_image
9 /// \macro_output
10 /// \macro_code
11 ///
12 /// \author Gregory Schott
13 
14 #include "RooRealVar.h"
15 #include "RooConstVar.h"
16 #include "RooProdPdf.h"
17 #include "RooWorkspace.h"
18 #include "RooDataSet.h"
19 #include "RooPolynomial.h"
20 #include "RooAddPdf.h"
21 #include "RooExtendPdf.h"
22 
27 
28 #include "TGraphErrors.h"
29 
30 using namespace RooFit;
31 using namespace RooStats;
32 
33 
34 void rs801_HypoTestInverterOriginal()
35 {
36  // prepare the model
37  RooRealVar lumi("lumi","luminosity",1);
38  RooRealVar r("r","cross-section ratio",3.74,0,50);
39  RooFormulaVar ns("ns","1*r*lumi",RooArgList(lumi,r));
40  RooRealVar nb("nb","background yield",1);
41  RooRealVar x("x","dummy observable",0,1);
43  RooPolynomial flatPdf("flatPdf","flat PDF",x,p0);
44  RooAddPdf totPdf("totPdf","S+B model",RooArgList(flatPdf,flatPdf),RooArgList(ns,nb));
45  RooExtendPdf bkgPdf("bkgPdf","B-only model",flatPdf,nb);
46  RooDataSet* data = totPdf.generate(x,1);
47 
48  // prepare the calculator
49  HybridCalculatorOriginal myhc(*data, totPdf, bkgPdf,0,0);
50  myhc.SetTestStatistic(2);
51  myhc.SetNumberOfToys(1000);
52  myhc.UseNuisance(false);
53 
54  // run the hypothesis-test inversion
55  HypoTestInverterOriginal myInverter(myhc,r);
56  myInverter.SetTestSize(0.10);
57  myInverter.UseCLs(true);
58  // myInverter.RunFixedScan(5,1,6);
59  // scan for a 95% UL
60  myInverter.RunAutoScan(3.,5,myInverter.Size()/2,0.005);
61  // run an alternative autoscan algorithm
62  // myInverter.RunAutoScan(1,6,myInverter.Size()/2,0.005,1);
63  //myInverter.RunOnePoint(3.9);
64 
65 
66  HypoTestInverterResult* results = myInverter.GetInterval();
67 
68  HypoTestInverterPlot myInverterPlot("myInverterPlot","",results);
69  TGraphErrors* gr1 = myInverterPlot.MakePlot();
70  gr1->Draw("ALP");
71 
72  double ulError = results->UpperLimitEstimatedError();
73 
74  double upperLimit = results->UpperLimit();
75  std::cout << "The computed upper limit is: " << upperLimit << std::endl;
76  std::cout << "an estimated error on this upper limit is: " << ulError << std::endl;
77  // expected result: 4.10
78 }
79 int main() {
80  rs801_HypoTestInverterOriginal();
81 }
RooAddPdf is an efficient implementation of a sum of PDFs of the form.
Definition: RooAddPdf.h:29
HybridCalculatorOriginal class.
virtual void Draw(Option_t *chopt="")
Draw this graph with its current attributes.
Definition: TGraph.cxx:745
Double_t x[n]
Definition: legend1.C:17
int main(int argc, char **argv)
RooConstVar represent a constant real-valued object.
Definition: RooConstVar.h:25
RooRealVar represents a fundamental (non-derived) real valued object.
Definition: RooRealVar.h:36
ROOT::R::TRInterface & r
Definition: Object.C:4
RooDataSet is a container class to hold unbinned data.
Definition: RooDataSet.h:29
Namespace for the RooStats classes.
Definition: Asimov.h:20
This class is now deprecated and to be replaced by the HypoTestInverter.
HypoTestInverterResult class holds the array of hypothesis test results and compute a confidence inte...
Class to plot an HypoTestInverterResult, result of the HypoTestInverter calculator.
Double_t UpperLimitEstimatedError()
Estimate of lower limit error function evaluates only a rough error on the lower limit.
RooConstVar & RooConst(Double_t val)
A TGraphErrors is a TGraph with error bars.
Definition: TGraphErrors.h:26
RooPolynomial implements a polynomial p.d.f of the form By default coefficient a_0 is chosen to be 1...
Definition: RooPolynomial.h:28
static constexpr double ns