CLs limit with MC toys¶
Open the ROOT file
In [1]:
TFile* f = TFile::Open("model.root") ;
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
Retrieve the workspace
In [2]:
RooWorkspace* w = (RooWorkspace*) f->Get("w") ;
w->Print() ;
RooWorkspace(w) w contents
variables
---------
(B,Nobs_CR,Nobs_SR,S,mu,tau)
p.d.f.s
-------
RooProdPdf::model[ model_SR * model_CR ] = 0.00144134
RooPoisson::model_CR[ x=Nobs_CR mean=Nexp_CR ] = 0.0281977
RooPoisson::model_SR[ x=Nobs_SR mean=Nexp_SR ] = 0.0511153
functions
--------
RooFormulaVar::Nexp_CR[ actualVars=(tau,B) formula="tau*B" ] = 200
RooFormulaVar::Nexp_SR[ actualVars=(mu,S,B) formula="mu*S+B" ] = 30
datasets
--------
RooDataSet::observed_data(Nobs_SR,Nobs_CR)
parameter snapshots
-------------------
ModelConfig__snapshot = (mu=1)
named sets
----------
ModelConfig_NuisParams:(B)
ModelConfig_Observables:(Nobs_SR,Nobs_CR)
ModelConfig_POI:(mu)
ModelConfig__snapshot:(mu)
obs:(Nobs_SR,Nobs_CR)
generic objects
---------------
RooStats::ModelConfig::ModelConfig
Retrieve the ModelConfig for the S+B hypothesis¶
Retrieve the ModelConfig and the observed data. Together these uniquely define the statistical problem
In [3]:
RooAbsData* data = w->data("observed_data") ;
RooStats::ModelConfig* sbModel = (RooStats::ModelConfig*) w->obj("ModelConfig") ;
Construct a ModelConfig for the B-only hypothesis¶
For a CLS-style limit calculation (hypothesis test inversion) we need an explicit specification of the background-only hypothesis == another RooStats::ModelConfig that describe the B-only scenario
In [4]:
RooStats::ModelConfig* bModel = (RooStats::ModelConfig*) sbModel->Clone("BonlyModel") ;
Here we take a little shortcut from universality by assuming that the POI=0 scenario corresponds to the background-only scenario
Set value POI parameter to zero
In [5]:
RooRealVar* poi = (RooRealVar*) bModel->GetParametersOfInterest()->first();
poi->setVal(0) ;
Configure bModel to encode current poi=0 scenario as its hypothesis
In [6]:
bModel->SetSnapshot( *poi );
NB: To make CLS-style hypothesis calculation macros truly universal workspace files should contain both ModelConfigs upfront
Construct an hypothesis p-value calculator¶
i.e the calculation of p(sbModel) and p(bModel) for the observed data
Instantiate hypothesis testing calculator assuming asymptotic
distributions of the profile likelihood ratio (PLR) test statistic.
This calculator is much more time consuming than the asymptotic
calculator but is also valid in the low statistics regime.
In [7]:
RooStats::FrequentistCalculator freqCalc(*data, *bModel, *sbModel);
The frequentist calculator is more general than the asymptotic calculator: it can calculate distributions for any test statistic. So here we have to tell it that we want the profile likelihood ratio test statistic
In [8]:
RooStats::ProfileLikelihoodTestStat* plr = new RooStats::ProfileLikelihoodTestStat(*sbModel->GetPdf());
Configure calculator for a limit (=one-sided interval)
In [9]:
plr->SetOneSided(true);
Specifically we have to tell the Toy MC sampler part of the calculator what the relevant test statistic is
In [10]:
RooStats::ToyMCSampler* toymcs = (RooStats::ToyMCSampler*) freqCalc.GetTestStatSampler();
toymcs->SetTestStatistic(plr);
If we use the frequentist calculator for counting experiments (instead of models of distributions) we should instruct the sampler to generate one event for each toy. ( This is the case because we model counting experiments in RooFit as a single observation in distribution of event counts. )
In [11]:
if (!sbModel->GetPdf()->canBeExtended()) {
toymcs->SetNEventsPerToy(1);
}
Sample 1000 toys for SB and B hypothesis respectively to model their distributions (Here you can trade speed vs accuracy)
In [12]:
freqCalc.SetToys(1000,1000) ;
Construct an hypothesis test inverter¶
i.e. a tool that can calculate the POI value for which (in this case) CLS==\(p(\mathrm{sbModel})/(1-p(\mathrm{Model}))\) takes a certain value. This inversion requires a scan over possible values of \(\mu\).
In [13]:
RooStats::HypoTestInverter inverter(freqCalc);
[#1] INFO:InputArguments -- HypoTestInverter ---- Input models:
using as S+B (null) model : ModelConfig
using as B (alternate) model : BonlyModel
Statistical configuration of hypothesis test inverter
In [14]:
inverter.SetConfidenceLevel(0.90);
inverter.UseCLs(true);
Technical configuration of hypothesis test inverter
In [15]:
inverter.SetVerbose(false);
inverter.SetFixedScan(30,0.0,6.0); // set number of points , xmin and xmax
Perform calculation of limit
In [16]:
RooStats::HypoTestInverterResult* result = inverter.GetInterval();
[#1] INFO:Eval -- HypoTestInverter::GetInterval - run a fixed scan
[#1] INFO:ObjectHandling -- RooWorkspace::saveSnaphot(w) replacing previous snapshot with name ModelConfig__snapshot
=== Using the following for ModelConfig ===
Observables: RooArgSet:: = (Nobs_SR,Nobs_CR)
Parameters of Interest: RooArgSet:: = (mu)
Nuisance Parameters: RooArgSet:: = (B)
PDF: RooProdPdf::model[ model_SR * model_CR ] = 0.00125727
Snapshot:
1) 0x7f8391561690 RooRealVar:: mu = 0 L(-1 - 10) "mu"
=== Using the following for BonlyModel ===
Observables: RooArgSet:: = (Nobs_SR,Nobs_CR)
Parameters of Interest: RooArgSet:: = (mu)
Nuisance Parameters: RooArgSet:: = (B)
PDF: RooProdPdf::model[ model_SR * model_CR ] = 0.00125727
Snapshot:
1) 0x7f8391561690 RooRealVar:: mu = 0 L(-1 - 10) "mu"
[#0] PROGRESS:Generation -- Test Statistic on data: 0
[#1] INFO:InputArguments -- Profiling conditional MLEs for Null.
[#1] INFO:InputArguments -- Using a ToyMCSampler. Now configuring for Null.
[#0] PROGRESS:Generation -- generated toys: 500 / 1000
[#1] INFO:InputArguments -- Profiling conditional MLEs for Alt.
[#1] INFO:InputArguments -- Using a ToyMCSampler. Now configuring for Alt.
[#0] PROGRESS:Generation -- generated toys: 500 / 1000
[#1] INFO:ObjectHandling -- RooWorkspace::saveSnaphot(w) replacing previous snapshot with name ModelConfig__snapshot
=== Using the following for ModelConfig ===
Observables: RooArgSet:: = (Nobs_SR,Nobs_CR)
Parameters of Interest: RooArgSet:: = (mu)
Nuisance Parameters: RooArgSet:: = (B)
PDF: RooProdPdf::model[ model_SR * model_CR ] = 0.00186075
Snapshot:
1) 0x7f8391442ea0 RooRealVar:: mu = 0.206897 L(-1 - 10) "mu"
=== Using the following for BonlyModel ===
Observables: RooArgSet:: = (Nobs_SR,Nobs_CR)
Parameters of Interest: RooArgSet:: = (mu)
Nuisance Parameters: RooArgSet:: = (B)
PDF: RooProdPdf::model[ model_SR * model_CR ] = 0.00186075
Snapshot:
1) 0x7f8391442ea0 RooRealVar:: mu = 0 L(-1 - 10) "mu"
[#0] PROGRESS:Generation -- Test Statistic on data: 0
[#1] INFO:InputArguments -- Profiling conditional MLEs for Null.
[#1] INFO:InputArguments -- Using a ToyMCSampler. Now configuring for Null.
[#0] PROGRESS:Generation -- generated toys: 500 / 1000
[#1] INFO:InputArguments -- Profiling conditional MLEs for Alt.
[#1] INFO:InputArguments -- Using a ToyMCSampler. Now configuring for Alt.
[#0] PROGRESS:Generation -- generated toys: 500 / 1000
[#1] INFO:ObjectHandling -- RooWorkspace::saveSnaphot(w) replacing previous snapshot with name ModelConfig__snapshot
=== Using the following for ModelConfig ===
Observables: RooArgSet:: = (Nobs_SR,Nobs_CR)
Parameters of Interest: RooArgSet:: = (mu)
Nuisance Parameters: RooArgSet:: = (B)
PDF: RooProdPdf::model[ model_SR * model_CR ] = 0.00220851
Snapshot:
1) 0x7f839172c370 RooRealVar:: mu = 0.413793 L(-1 - 10) "mu"
=== Using the following for BonlyModel ===
Observables: RooArgSet:: = (Nobs_SR,Nobs_CR)
Parameters of Interest: RooArgSet:: = (mu)
Nuisance Parameters: RooArgSet:: = (B)
PDF: RooProdPdf::model[ model_SR * model_CR ] = 0.00220851
Snapshot:
1) 0x7f839172c370 RooRealVar:: mu = 0 L(-1 - 10) "mu"
[#0] PROGRESS:Generation -- Test Statistic on data: 0
[#1] INFO:InputArguments -- Profiling conditional MLEs for Null.
[#1] INFO:InputArguments -- Using a ToyMCSampler. Now configuring for Null.
[#0] PROGRESS:Generation -- generated toys: 500 / 1000
[#1] INFO:InputArguments -- Profiling conditional MLEs for Alt.
[#1] INFO:InputArguments -- Using a ToyMCSampler. Now configuring for Alt.
[#0] PROGRESS:Generation -- generated toys: 500 / 1000
[#1] INFO:ObjectHandling -- RooWorkspace::saveSnaphot(w) replacing previous snapshot with name ModelConfig__snapshot
=== Using the following for ModelConfig ===
Observables: RooArgSet:: = (Nobs_SR,Nobs_CR)
Parameters of Interest: RooArgSet:: = (mu)
Nuisance Parameters: RooArgSet:: = (B)
PDF: RooProdPdf::model[ model_SR * model_CR ] = 0.00217996
Snapshot:
1) 0x7f839172bdf0 RooRealVar:: mu = 0.62069 L(-1 - 10) "mu"
=== Using the following for BonlyModel ===
Observables: RooArgSet:: = (Nobs_SR,Nobs_CR)
Parameters of Interest: RooArgSet:: = (mu)
Nuisance Parameters: RooArgSet:: = (B)
PDF: RooProdPdf::model[ model_SR * model_CR ] = 0.00217996
Snapshot:
1) 0x7f839172bdf0 RooRealVar:: mu = 0 L(-1 - 10) "mu"
[#0] PROGRESS:Generation -- Test Statistic on data: 0.0262556
[#1] INFO:InputArguments -- Profiling conditional MLEs for Null.
[#1] INFO:InputArguments -- Using a ToyMCSampler. Now configuring for Null.
[#0] PROGRESS:Generation -- generated toys: 500 / 1000
[#1] INFO:InputArguments -- Profiling conditional MLEs for Alt.
[#1] INFO:InputArguments -- Using a ToyMCSampler. Now configuring for Alt.
[#0] PROGRESS:Generation -- generated toys: 500 / 1000
[#1] INFO:ObjectHandling -- RooWorkspace::saveSnaphot(w) replacing previous snapshot with name ModelConfig__snapshot
=== Using the following for ModelConfig ===
Observables: RooArgSet:: = (Nobs_SR,Nobs_CR)
Parameters of Interest: RooArgSet:: = (mu)
Nuisance Parameters: RooArgSet:: = (B)
PDF: RooProdPdf::model[ model_SR * model_CR ] = 0.00184041
Snapshot:
1) 0x7f8391624430 RooRealVar:: mu = 0.827586 L(-1 - 10) "mu"
=== Using the following for BonlyModel ===
Observables: RooArgSet:: = (Nobs_SR,Nobs_CR)
Parameters of Interest: RooArgSet:: = (mu)
Nuisance Parameters: RooArgSet:: = (B)
PDF: RooProdPdf::model[ model_SR * model_CR ] = 0.00184041
Snapshot:
1) 0x7f8391624430 RooRealVar:: mu = 0 L(-1 - 10) "mu"
[#0] PROGRESS:Generation -- Test Statistic on data: 0.184997
[#1] INFO:InputArguments -- Profiling conditional MLEs for Null.
[#1] INFO:InputArguments -- Using a ToyMCSampler. Now configuring for Null.
[#0] PROGRESS:Generation -- generated toys: 500 / 1000
[#1] INFO:InputArguments -- Profiling conditional MLEs for Alt.
[#1] INFO:InputArguments -- Using a ToyMCSampler. Now configuring for Alt.
[#0] PROGRESS:Generation -- generated toys: 500 / 1000
[#1] INFO:ObjectHandling -- RooWorkspace::saveSnaphot(w) replacing previous snapshot with name ModelConfig__snapshot
=== Using the following for ModelConfig ===
Observables: RooArgSet:: = (Nobs_SR,Nobs_CR)
Parameters of Interest: RooArgSet:: = (mu)
Nuisance Parameters: RooArgSet:: = (B)
PDF: RooProdPdf::model[ model_SR * model_CR ] = 0.00135861
Snapshot:
1) 0x7f839172c370 RooRealVar:: mu = 1.03448 L(-1 - 10) "mu"
=== Using the following for BonlyModel ===
Observables: RooArgSet:: = (Nobs_SR,Nobs_CR)
Parameters of Interest: RooArgSet:: = (mu)
Nuisance Parameters: RooArgSet:: = (B)
PDF: RooProdPdf::model[ model_SR * model_CR ] = 0.00135861
Snapshot:
1) 0x7f839172c370 RooRealVar:: mu = 0 L(-1 - 10) "mu"
[#0] PROGRESS:Generation -- Test Statistic on data: 0.471936
[#1] INFO:InputArguments -- Profiling conditional MLEs for Null.
[#1] INFO:InputArguments -- Using a ToyMCSampler. Now configuring for Null.
[#0] PROGRESS:Generation -- generated toys: 500 / 1000
[#1] INFO:InputArguments -- Profiling conditional MLEs for Alt.
[#1] INFO:InputArguments -- Using a ToyMCSampler. Now configuring for Alt.
[#0] PROGRESS:Generation -- generated toys: 500 / 1000
[#1] INFO:ObjectHandling -- RooWorkspace::saveSnaphot(w) replacing previous snapshot with name ModelConfig__snapshot
=== Using the following for ModelConfig ===
Observables: RooArgSet:: = (Nobs_SR,Nobs_CR)
Parameters of Interest: RooArgSet:: = (mu)
Nuisance Parameters: RooArgSet:: = (B)
PDF: RooProdPdf::model[ model_SR * model_CR ] = 0.000892654
Snapshot:
1) 0x7f839172bdf0 RooRealVar:: mu = 1.24138 L(-1 - 10) "mu"
=== Using the following for BonlyModel ===
Observables: RooArgSet:: = (Nobs_SR,Nobs_CR)
Parameters of Interest: RooArgSet:: = (mu)
Nuisance Parameters: RooArgSet:: = (B)
PDF: RooProdPdf::model[ model_SR * model_CR ] = 0.000892654
Snapshot:
1) 0x7f839172bdf0 RooRealVar:: mu = 0 L(-1 - 10) "mu"
[#0] PROGRESS:Generation -- Test Statistic on data: 0.871855
[#1] INFO:InputArguments -- Profiling conditional MLEs for Null.
[#1] INFO:InputArguments -- Using a ToyMCSampler. Now configuring for Null.
[#0] PROGRESS:Generation -- generated toys: 500 / 1000
[#1] INFO:InputArguments -- Profiling conditional MLEs for Alt.
[#1] INFO:InputArguments -- Using a ToyMCSampler. Now configuring for Alt.
[#0] PROGRESS:Generation -- generated toys: 500 / 1000
[#1] INFO:ObjectHandling -- RooWorkspace::saveSnaphot(w) replacing previous snapshot with name ModelConfig__snapshot
=== Using the following for ModelConfig ===
Observables: RooArgSet:: = (Nobs_SR,Nobs_CR)
Parameters of Interest: RooArgSet:: = (mu)
Nuisance Parameters: RooArgSet:: = (B)
PDF: RooProdPdf::model[ model_SR * model_CR ] = 0.000529598
Snapshot:
1) 0x7f8391624430 RooRealVar:: mu = 1.44828 L(-1 - 10) "mu"
=== Using the following for BonlyModel ===
Observables: RooArgSet:: = (Nobs_SR,Nobs_CR)
Parameters of Interest: RooArgSet:: = (mu)
Nuisance Parameters: RooArgSet:: = (B)
PDF: RooProdPdf::model[ model_SR * model_CR ] = 0.000529598
Snapshot:
1) 0x7f8391624430 RooRealVar:: mu = 0 L(-1 - 10) "mu"
[#0] PROGRESS:Generation -- Test Statistic on data: 1.37183
[#1] INFO:InputArguments -- Profiling conditional MLEs for Null.
[#1] INFO:InputArguments -- Using a ToyMCSampler. Now configuring for Null.
[#0] PROGRESS:Generation -- generated toys: 500 / 1000
[#1] INFO:InputArguments -- Profiling conditional MLEs for Alt.
[#1] INFO:InputArguments -- Using a ToyMCSampler. Now configuring for Alt.
[#0] PROGRESS:Generation -- generated toys: 500 / 1000
[#1] INFO:ObjectHandling -- RooWorkspace::saveSnaphot(w) replacing previous snapshot with name ModelConfig__snapshot
=== Using the following for ModelConfig ===
Observables: RooArgSet:: = (Nobs_SR,Nobs_CR)
Parameters of Interest: RooArgSet:: = (mu)
Nuisance Parameters: RooArgSet:: = (B)
PDF: RooProdPdf::model[ model_SR * model_CR ] = 0.000287113
Snapshot:
1) 0x7f839172c370 RooRealVar:: mu = 1.65517 L(-1 - 10) "mu"
=== Using the following for BonlyModel ===
Observables: RooArgSet:: = (Nobs_SR,Nobs_CR)
Parameters of Interest: RooArgSet:: = (mu)
Nuisance Parameters: RooArgSet:: = (B)
PDF: RooProdPdf::model[ model_SR * model_CR ] = 0.000287113
Snapshot:
1) 0x7f839172c370 RooRealVar:: mu = 0 L(-1 - 10) "mu"
[#0] PROGRESS:Generation -- Test Statistic on data: 1.96102
[#1] INFO:InputArguments -- Profiling conditional MLEs for Null.
[#1] INFO:InputArguments -- Using a ToyMCSampler. Now configuring for Null.
[#0] PROGRESS:Generation -- generated toys: 500 / 1000
[#1] INFO:InputArguments -- Profiling conditional MLEs for Alt.
[#1] INFO:InputArguments -- Using a ToyMCSampler. Now configuring for Alt.
[#0] PROGRESS:Generation -- generated toys: 500 / 1000
[#1] INFO:ObjectHandling -- RooWorkspace::saveSnaphot(w) replacing previous snapshot with name ModelConfig__snapshot
=== Using the following for ModelConfig ===
Observables: RooArgSet:: = (Nobs_SR,Nobs_CR)
Parameters of Interest: RooArgSet:: = (mu)
Nuisance Parameters: RooArgSet:: = (B)
PDF: RooProdPdf::model[ model_SR * model_CR ] = 0.000143654
Snapshot:
1) 0x7f839172bdf0 RooRealVar:: mu = 1.86207 L(-1 - 10) "mu"
=== Using the following for BonlyModel ===
Observables: RooArgSet:: = (Nobs_SR,Nobs_CR)
Parameters of Interest: RooArgSet:: = (mu)
Nuisance Parameters: RooArgSet:: = (B)
PDF: RooProdPdf::model[ model_SR * model_CR ] = 0.000143654
Snapshot:
1) 0x7f839172bdf0 RooRealVar:: mu = 0 L(-1 - 10) "mu"
[#0] PROGRESS:Generation -- Test Statistic on data: 2.63018
[#1] INFO:InputArguments -- Profiling conditional MLEs for Null.
[#1] INFO:InputArguments -- Using a ToyMCSampler. Now configuring for Null.
[#0] PROGRESS:Generation -- generated toys: 500 / 1000
[#1] INFO:InputArguments -- Profiling conditional MLEs for Alt.
[#1] INFO:InputArguments -- Using a ToyMCSampler. Now configuring for Alt.
[#0] PROGRESS:Generation -- generated toys: 500 / 1000
[#1] INFO:ObjectHandling -- RooWorkspace::saveSnaphot(w) replacing previous snapshot with name ModelConfig__snapshot
=== Using the following for ModelConfig ===
Observables: RooArgSet:: = (Nobs_SR,Nobs_CR)
Parameters of Interest: RooArgSet:: = (mu)
Nuisance Parameters: RooArgSet:: = (B)
PDF: RooProdPdf::model[ model_SR * model_CR ] = 6.68923e-05
Snapshot:
1) 0x7f8391624430 RooRealVar:: mu = 2.06897 L(-1 - 10) "mu"
=== Using the following for BonlyModel ===
Observables: RooArgSet:: = (Nobs_SR,Nobs_CR)
Parameters of Interest: RooArgSet:: = (mu)
Nuisance Parameters: RooArgSet:: = (B)
PDF: RooProdPdf::model[ model_SR * model_CR ] = 6.68923e-05
Snapshot:
1) 0x7f8391624430 RooRealVar:: mu = 0 L(-1 - 10) "mu"
[#0] PROGRESS:Generation -- Test Statistic on data: 3.37135
[#1] INFO:InputArguments -- Profiling conditional MLEs for Null.
[#1] INFO:InputArguments -- Using a ToyMCSampler. Now configuring for Null.
[#0] PROGRESS:Generation -- generated toys: 500 / 1000
[#1] INFO:InputArguments -- Profiling conditional MLEs for Alt.
[#1] INFO:InputArguments -- Using a ToyMCSampler. Now configuring for Alt.
[#0] PROGRESS:Generation -- generated toys: 500 / 1000
[#1] INFO:ObjectHandling -- RooWorkspace::saveSnaphot(w) replacing previous snapshot with name ModelConfig__snapshot
=== Using the following for ModelConfig ===
Observables: RooArgSet:: = (Nobs_SR,Nobs_CR)
Parameters of Interest: RooArgSet:: = (mu)
Nuisance Parameters: RooArgSet:: = (B)
PDF: RooProdPdf::model[ model_SR * model_CR ] = 2.91963e-05
Snapshot:
1) 0x7f839172c370 RooRealVar:: mu = 2.27586 L(-1 - 10) "mu"
=== Using the following for BonlyModel ===
Observables: RooArgSet:: = (Nobs_SR,Nobs_CR)
Parameters of Interest: RooArgSet:: = (mu)
Nuisance Parameters: RooArgSet:: = (B)
PDF: RooProdPdf::model[ model_SR * model_CR ] = 2.91963e-05
Snapshot:
1) 0x7f839172c370 RooRealVar:: mu = 0 L(-1 - 10) "mu"
[#0] PROGRESS:Generation -- Test Statistic on data: 4.17768
[#1] INFO:InputArguments -- Profiling conditional MLEs for Null.
[#1] INFO:InputArguments -- Using a ToyMCSampler. Now configuring for Null.
[#0] PROGRESS:Generation -- generated toys: 500 / 1000
[#1] INFO:InputArguments -- Profiling conditional MLEs for Alt.
[#1] INFO:InputArguments -- Using a ToyMCSampler. Now configuring for Alt.
[#0] PROGRESS:Generation -- generated toys: 500 / 1000
[#1] INFO:ObjectHandling -- RooWorkspace::saveSnaphot(w) replacing previous snapshot with name ModelConfig__snapshot
=== Using the following for ModelConfig ===
Observables: RooArgSet:: = (Nobs_SR,Nobs_CR)
Parameters of Interest: RooArgSet:: = (mu)
Nuisance Parameters: RooArgSet:: = (B)
PDF: RooProdPdf::model[ model_SR * model_CR ] = 1.20179e-05
Snapshot:
1) 0x7f839172bdf0 RooRealVar:: mu = 2.48276 L(-1 - 10) "mu"
=== Using the following for BonlyModel ===
Observables: RooArgSet:: = (Nobs_SR,Nobs_CR)
Parameters of Interest: RooArgSet:: = (mu)
Nuisance Parameters: RooArgSet:: = (B)
PDF: RooProdPdf::model[ model_SR * model_CR ] = 1.20179e-05
Snapshot:
1) 0x7f839172bdf0 RooRealVar:: mu = 0 L(-1 - 10) "mu"
[#0] PROGRESS:Generation -- Test Statistic on data: 5.04325
[#1] INFO:InputArguments -- Profiling conditional MLEs for Null.
[#1] INFO:InputArguments -- Using a ToyMCSampler. Now configuring for Null.
[#0] PROGRESS:Generation -- generated toys: 500 / 1000
[#1] INFO:InputArguments -- Profiling conditional MLEs for Alt.
[#1] INFO:InputArguments -- Using a ToyMCSampler. Now configuring for Alt.
[#0] PROGRESS:Generation -- generated toys: 500 / 1000
[#1] INFO:ObjectHandling -- RooWorkspace::saveSnaphot(w) replacing previous snapshot with name ModelConfig__snapshot
=== Using the following for ModelConfig ===
Observables: RooArgSet:: = (Nobs_SR,Nobs_CR)
Parameters of Interest: RooArgSet:: = (mu)
Nuisance Parameters: RooArgSet:: = (B)
PDF: RooProdPdf::model[ model_SR * model_CR ] = 4.69005e-06
Snapshot:
1) 0x7f8391624430 RooRealVar:: mu = 2.68966 L(-1 - 10) "mu"
=== Using the following for BonlyModel ===
Observables: RooArgSet:: = (Nobs_SR,Nobs_CR)
Parameters of Interest: RooArgSet:: = (mu)
Nuisance Parameters: RooArgSet:: = (B)
PDF: RooProdPdf::model[ model_SR * model_CR ] = 4.69005e-06
Snapshot:
1) 0x7f8391624430 RooRealVar:: mu = 0 L(-1 - 10) "mu"
[#0] PROGRESS:Generation -- Test Statistic on data: 5.96288
[#1] INFO:InputArguments -- Profiling conditional MLEs for Null.
[#1] INFO:InputArguments -- Using a ToyMCSampler. Now configuring for Null.
[#0] PROGRESS:Generation -- generated toys: 500 / 1000
[#1] INFO:InputArguments -- Profiling conditional MLEs for Alt.
[#1] INFO:InputArguments -- Using a ToyMCSampler. Now configuring for Alt.
[#0] PROGRESS:Generation -- generated toys: 500 / 1000
[#1] INFO:ObjectHandling -- RooWorkspace::saveSnaphot(w) replacing previous snapshot with name ModelConfig__snapshot
=== Using the following for ModelConfig ===
Observables: RooArgSet:: = (Nobs_SR,Nobs_CR)
Parameters of Interest: RooArgSet:: = (mu)
Nuisance Parameters: RooArgSet:: = (B)
PDF: RooProdPdf::model[ model_SR * model_CR ] = 1.7433e-06
Snapshot:
1) 0x7f839172c370 RooRealVar:: mu = 2.89655 L(-1 - 10) "mu"
=== Using the following for BonlyModel ===
Observables: RooArgSet:: = (Nobs_SR,Nobs_CR)
Parameters of Interest: RooArgSet:: = (mu)
Nuisance Parameters: RooArgSet:: = (B)
PDF: RooProdPdf::model[ model_SR * model_CR ] = 1.7433e-06
Snapshot:
1) 0x7f839172c370 RooRealVar:: mu = 0 L(-1 - 10) "mu"
[#0] PROGRESS:Generation -- Test Statistic on data: 6.93201
[#1] INFO:InputArguments -- Profiling conditional MLEs for Null.
[#1] INFO:InputArguments -- Using a ToyMCSampler. Now configuring for Null.
[#0] PROGRESS:Generation -- generated toys: 500 / 1000
[#1] INFO:InputArguments -- Profiling conditional MLEs for Alt.
[#1] INFO:InputArguments -- Using a ToyMCSampler. Now configuring for Alt.
[#0] PROGRESS:Generation -- generated toys: 500 / 1000
[#1] INFO:ObjectHandling -- RooWorkspace::saveSnaphot(w) replacing previous snapshot with name ModelConfig__snapshot
=== Using the following for ModelConfig ===
Observables: RooArgSet:: = (Nobs_SR,Nobs_CR)
Parameters of Interest: RooArgSet:: = (mu)
Nuisance Parameters: RooArgSet:: = (B)
PDF: RooProdPdf::model[ model_SR * model_CR ] = 6.19679e-07
Snapshot:
1) 0x7f839172bdf0 RooRealVar:: mu = 3.10345 L(-1 - 10) "mu"
=== Using the following for BonlyModel ===
Observables: RooArgSet:: = (Nobs_SR,Nobs_CR)
Parameters of Interest: RooArgSet:: = (mu)
Nuisance Parameters: RooArgSet:: = (B)
PDF: RooProdPdf::model[ model_SR * model_CR ] = 6.19679e-07
Snapshot:
1) 0x7f839172bdf0 RooRealVar:: mu = 0 L(-1 - 10) "mu"
[#0] PROGRESS:Generation -- Test Statistic on data: 7.94662
[#1] INFO:InputArguments -- Profiling conditional MLEs for Null.
[#1] INFO:InputArguments -- Using a ToyMCSampler. Now configuring for Null.
[#0] PROGRESS:Generation -- generated toys: 500 / 1000
[#1] INFO:InputArguments -- Profiling conditional MLEs for Alt.
[#1] INFO:InputArguments -- Using a ToyMCSampler. Now configuring for Alt.
[#0] PROGRESS:Generation -- generated toys: 500 / 1000
[#1] INFO:ObjectHandling -- RooWorkspace::saveSnaphot(w) replacing previous snapshot with name ModelConfig__snapshot
=== Using the following for ModelConfig ===
Observables: RooArgSet:: = (Nobs_SR,Nobs_CR)
Parameters of Interest: RooArgSet:: = (mu)
Nuisance Parameters: RooArgSet:: = (B)
PDF: RooProdPdf::model[ model_SR * model_CR ] = 2.11399e-07
Snapshot:
1) 0x7f8391624430 RooRealVar:: mu = 3.31034 L(-1 - 10) "mu"
=== Using the following for BonlyModel ===
Observables: RooArgSet:: = (Nobs_SR,Nobs_CR)
Parameters of Interest: RooArgSet:: = (mu)
Nuisance Parameters: RooArgSet:: = (B)
PDF: RooProdPdf::model[ model_SR * model_CR ] = 2.11399e-07
Snapshot:
1) 0x7f8391624430 RooRealVar:: mu = 0 L(-1 - 10) "mu"
[#0] PROGRESS:Generation -- Test Statistic on data: 9.00319
[#1] INFO:InputArguments -- Profiling conditional MLEs for Null.
[#1] INFO:InputArguments -- Using a ToyMCSampler. Now configuring for Null.
[#0] PROGRESS:Generation -- generated toys: 500 / 1000
[#1] INFO:InputArguments -- Profiling conditional MLEs for Alt.
[#1] INFO:InputArguments -- Using a ToyMCSampler. Now configuring for Alt.
[#0] PROGRESS:Generation -- generated toys: 500 / 1000
[#1] INFO:ObjectHandling -- RooWorkspace::saveSnaphot(w) replacing previous snapshot with name ModelConfig__snapshot
=== Using the following for ModelConfig ===
Observables: RooArgSet:: = (Nobs_SR,Nobs_CR)
Parameters of Interest: RooArgSet:: = (mu)
Nuisance Parameters: RooArgSet:: = (B)
PDF: RooProdPdf::model[ model_SR * model_CR ] = 6.94294e-08
Snapshot:
1) 0x7f839172c370 RooRealVar:: mu = 3.51724 L(-1 - 10) "mu"
=== Using the following for BonlyModel ===
Observables: RooArgSet:: = (Nobs_SR,Nobs_CR)
Parameters of Interest: RooArgSet:: = (mu)
Nuisance Parameters: RooArgSet:: = (B)
PDF: RooProdPdf::model[ model_SR * model_CR ] = 6.94294e-08
Snapshot:
1) 0x7f839172c370 RooRealVar:: mu = 0 L(-1 - 10) "mu"
[#0] PROGRESS:Generation -- Test Statistic on data: 10.0985
[#1] INFO:InputArguments -- Profiling conditional MLEs for Null.
[#1] INFO:InputArguments -- Using a ToyMCSampler. Now configuring for Null.
[#0] PROGRESS:Generation -- generated toys: 500 / 1000
[#1] INFO:InputArguments -- Profiling conditional MLEs for Alt.
[#1] INFO:InputArguments -- Using a ToyMCSampler. Now configuring for Alt.
[#0] PROGRESS:Generation -- generated toys: 500 / 1000
[#1] INFO:ObjectHandling -- RooWorkspace::saveSnaphot(w) replacing previous snapshot with name ModelConfig__snapshot
=== Using the following for ModelConfig ===
Observables: RooArgSet:: = (Nobs_SR,Nobs_CR)
Parameters of Interest: RooArgSet:: = (mu)
Nuisance Parameters: RooArgSet:: = (B)
PDF: RooProdPdf::model[ model_SR * model_CR ] = 2.20143e-08
Snapshot:
1) 0x7f839172bdf0 RooRealVar:: mu = 3.72414 L(-1 - 10) "mu"
=== Using the following for BonlyModel ===
Observables: RooArgSet:: = (Nobs_SR,Nobs_CR)
Parameters of Interest: RooArgSet:: = (mu)
Nuisance Parameters: RooArgSet:: = (B)
PDF: RooProdPdf::model[ model_SR * model_CR ] = 2.20143e-08
Snapshot:
1) 0x7f839172bdf0 RooRealVar:: mu = 0 L(-1 - 10) "mu"
[#0] PROGRESS:Generation -- Test Statistic on data: 11.2299
[#1] INFO:InputArguments -- Profiling conditional MLEs for Null.
[#1] INFO:InputArguments -- Using a ToyMCSampler. Now configuring for Null.
[#0] PROGRESS:Generation -- generated toys: 500 / 1000
[#1] INFO:InputArguments -- Profiling conditional MLEs for Alt.
[#1] INFO:InputArguments -- Using a ToyMCSampler. Now configuring for Alt.
[#0] PROGRESS:Generation -- generated toys: 500 / 1000
[#1] INFO:ObjectHandling -- RooWorkspace::saveSnaphot(w) replacing previous snapshot with name ModelConfig__snapshot
=== Using the following for ModelConfig ===
Observables: RooArgSet:: = (Nobs_SR,Nobs_CR)
Parameters of Interest: RooArgSet:: = (mu)
Nuisance Parameters: RooArgSet:: = (B)
PDF: RooProdPdf::model[ model_SR * model_CR ] = 6.75576e-09
Snapshot:
1) 0x7f8391624430 RooRealVar:: mu = 3.93103 L(-1 - 10) "mu"
=== Using the following for BonlyModel ===
Observables: RooArgSet:: = (Nobs_SR,Nobs_CR)
Parameters of Interest: RooArgSet:: = (mu)
Nuisance Parameters: RooArgSet:: = (B)
PDF: RooProdPdf::model[ model_SR * model_CR ] = 6.75576e-09
Snapshot:
1) 0x7f8391624430 RooRealVar:: mu = 0 L(-1 - 10) "mu"
[#0] PROGRESS:Generation -- Test Statistic on data: 12.3946
[#1] INFO:InputArguments -- Profiling conditional MLEs for Null.
[#1] INFO:InputArguments -- Using a ToyMCSampler. Now configuring for Null.
[#0] PROGRESS:Generation -- generated toys: 500 / 1000
[#1] INFO:InputArguments -- Profiling conditional MLEs for Alt.
[#1] INFO:InputArguments -- Using a ToyMCSampler. Now configuring for Alt.
[#0] PROGRESS:Generation -- generated toys: 500 / 1000
[#1] INFO:ObjectHandling -- RooWorkspace::saveSnaphot(w) replacing previous snapshot with name ModelConfig__snapshot
=== Using the following for ModelConfig ===
Observables: RooArgSet:: = (Nobs_SR,Nobs_CR)
Parameters of Interest: RooArgSet:: = (mu)
Nuisance Parameters: RooArgSet:: = (B)
PDF: RooProdPdf::model[ model_SR * model_CR ] = 2.01105e-09
Snapshot:
1) 0x7f839172c370 RooRealVar:: mu = 4.13793 L(-1 - 10) "mu"
=== Using the following for BonlyModel ===
Observables: RooArgSet:: = (Nobs_SR,Nobs_CR)
Parameters of Interest: RooArgSet:: = (mu)
Nuisance Parameters: RooArgSet:: = (B)
PDF: RooProdPdf::model[ model_SR * model_CR ] = 2.01105e-09
Snapshot:
1) 0x7f839172c370 RooRealVar:: mu = 0 L(-1 - 10) "mu"
[#0] PROGRESS:Generation -- Test Statistic on data: 13.5905
[#1] INFO:InputArguments -- Profiling conditional MLEs for Null.
[#1] INFO:InputArguments -- Using a ToyMCSampler. Now configuring for Null.
[#0] PROGRESS:Generation -- generated toys: 500 / 1000
[#1] INFO:InputArguments -- Profiling conditional MLEs for Alt.
[#1] INFO:InputArguments -- Using a ToyMCSampler. Now configuring for Alt.
[#0] PROGRESS:Generation -- generated toys: 500 / 1000
[#1] INFO:ObjectHandling -- RooWorkspace::saveSnaphot(w) replacing previous snapshot with name ModelConfig__snapshot
=== Using the following for ModelConfig ===
Observables: RooArgSet:: = (Nobs_SR,Nobs_CR)
Parameters of Interest: RooArgSet:: = (mu)
Nuisance Parameters: RooArgSet:: = (B)
PDF: RooProdPdf::model[ model_SR * model_CR ] = 5.81873e-10
Snapshot:
1) 0x7f83916049a0 RooRealVar:: mu = 4.34483 L(-1 - 10) "mu"
=== Using the following for BonlyModel ===
Observables: RooArgSet:: = (Nobs_SR,Nobs_CR)
Parameters of Interest: RooArgSet:: = (mu)
Nuisance Parameters: RooArgSet:: = (B)
PDF: RooProdPdf::model[ model_SR * model_CR ] = 5.81873e-10
Snapshot:
1) 0x7f83916049a0 RooRealVar:: mu = 0 L(-1 - 10) "mu"
[#0] PROGRESS:Generation -- Test Statistic on data: 14.8156
[#1] INFO:InputArguments -- Profiling conditional MLEs for Null.
[#1] INFO:InputArguments -- Using a ToyMCSampler. Now configuring for Null.
[#0] PROGRESS:Generation -- generated toys: 500 / 1000
[#1] INFO:InputArguments -- Profiling conditional MLEs for Alt.
[#1] INFO:InputArguments -- Using a ToyMCSampler. Now configuring for Alt.
[#0] PROGRESS:Generation -- generated toys: 500 / 1000
[#1] INFO:ObjectHandling -- RooWorkspace::saveSnaphot(w) replacing previous snapshot with name ModelConfig__snapshot
=== Using the following for ModelConfig ===
Observables: RooArgSet:: = (Nobs_SR,Nobs_CR)
Parameters of Interest: RooArgSet:: = (mu)
Nuisance Parameters: RooArgSet:: = (B)
PDF: RooProdPdf::model[ model_SR * model_CR ] = 1.63939e-10
Snapshot:
1) 0x7f8391b953d0 RooRealVar:: mu = 4.55172 L(-1 - 10) "mu"
=== Using the following for BonlyModel ===
Observables: RooArgSet:: = (Nobs_SR,Nobs_CR)
Parameters of Interest: RooArgSet:: = (mu)
Nuisance Parameters: RooArgSet:: = (B)
PDF: RooProdPdf::model[ model_SR * model_CR ] = 1.63939e-10
Snapshot:
1) 0x7f8391b953d0 RooRealVar:: mu = 0 L(-1 - 10) "mu"
[#0] PROGRESS:Generation -- Test Statistic on data: 16.0679
[#1] INFO:InputArguments -- Profiling conditional MLEs for Null.
[#1] INFO:InputArguments -- Using a ToyMCSampler. Now configuring for Null.
[#0] PROGRESS:Generation -- generated toys: 500 / 1000
[#1] INFO:InputArguments -- Profiling conditional MLEs for Alt.
[#1] INFO:InputArguments -- Using a ToyMCSampler. Now configuring for Alt.
[#0] PROGRESS:Generation -- generated toys: 500 / 1000
[#1] INFO:ObjectHandling -- RooWorkspace::saveSnaphot(w) replacing previous snapshot with name ModelConfig__snapshot
=== Using the following for ModelConfig ===
Observables: RooArgSet:: = (Nobs_SR,Nobs_CR)
Parameters of Interest: RooArgSet:: = (mu)
Nuisance Parameters: RooArgSet:: = (B)
PDF: RooProdPdf::model[ model_SR * model_CR ] = 4.50509e-11
Snapshot:
1) 0x7f839172c370 RooRealVar:: mu = 4.75862 L(-1 - 10) "mu"
=== Using the following for BonlyModel ===
Observables: RooArgSet:: = (Nobs_SR,Nobs_CR)
Parameters of Interest: RooArgSet:: = (mu)
Nuisance Parameters: RooArgSet:: = (B)
PDF: RooProdPdf::model[ model_SR * model_CR ] = 4.50509e-11
Snapshot:
1) 0x7f839172c370 RooRealVar:: mu = 0 L(-1 - 10) "mu"
[#0] PROGRESS:Generation -- Test Statistic on data: 17.3457
[#1] INFO:InputArguments -- Profiling conditional MLEs for Null.
[#1] INFO:InputArguments -- Using a ToyMCSampler. Now configuring for Null.
[#0] PROGRESS:Generation -- generated toys: 500 / 1000
[#1] INFO:InputArguments -- Profiling conditional MLEs for Alt.
[#1] INFO:InputArguments -- Using a ToyMCSampler. Now configuring for Alt.
[#0] PROGRESS:Generation -- generated toys: 500 / 1000
[#1] INFO:ObjectHandling -- RooWorkspace::saveSnaphot(w) replacing previous snapshot with name ModelConfig__snapshot
=== Using the following for ModelConfig ===
Observables: RooArgSet:: = (Nobs_SR,Nobs_CR)
Parameters of Interest: RooArgSet:: = (mu)
Nuisance Parameters: RooArgSet:: = (B)
PDF: RooProdPdf::model[ model_SR * model_CR ] = 1.20933e-11
Snapshot:
1) 0x7f8391624430 RooRealVar:: mu = 4.96552 L(-1 - 10) "mu"
=== Using the following for BonlyModel ===
Observables: RooArgSet:: = (Nobs_SR,Nobs_CR)
Parameters of Interest: RooArgSet:: = (mu)
Nuisance Parameters: RooArgSet:: = (B)
PDF: RooProdPdf::model[ model_SR * model_CR ] = 1.20933e-11
Snapshot:
1) 0x7f8391624430 RooRealVar:: mu = 0 L(-1 - 10) "mu"
[#0] PROGRESS:Generation -- Test Statistic on data: 18.6475
[#1] INFO:InputArguments -- Profiling conditional MLEs for Null.
[#1] INFO:InputArguments -- Using a ToyMCSampler. Now configuring for Null.
[#0] PROGRESS:Generation -- generated toys: 500 / 1000
[#1] INFO:InputArguments -- Profiling conditional MLEs for Alt.
[#1] INFO:InputArguments -- Using a ToyMCSampler. Now configuring for Alt.
[#0] PROGRESS:Generation -- generated toys: 500 / 1000
[#1] INFO:ObjectHandling -- RooWorkspace::saveSnaphot(w) replacing previous snapshot with name ModelConfig__snapshot
=== Using the following for ModelConfig ===
Observables: RooArgSet:: = (Nobs_SR,Nobs_CR)
Parameters of Interest: RooArgSet:: = (mu)
Nuisance Parameters: RooArgSet:: = (B)
PDF: RooProdPdf::model[ model_SR * model_CR ] = 3.17544e-12
Snapshot:
1) 0x7f8391b953d0 RooRealVar:: mu = 5.17241 L(-1 - 10) "mu"
=== Using the following for BonlyModel ===
Observables: RooArgSet:: = (Nobs_SR,Nobs_CR)
Parameters of Interest: RooArgSet:: = (mu)
Nuisance Parameters: RooArgSet:: = (B)
PDF: RooProdPdf::model[ model_SR * model_CR ] = 3.17544e-12
Snapshot:
1) 0x7f8391b953d0 RooRealVar:: mu = 0 L(-1 - 10) "mu"
[#0] PROGRESS:Generation -- Test Statistic on data: 19.9717
[#1] INFO:InputArguments -- Profiling conditional MLEs for Null.
[#1] INFO:InputArguments -- Using a ToyMCSampler. Now configuring for Null.
[#0] PROGRESS:Generation -- generated toys: 500 / 1000
[#1] INFO:InputArguments -- Profiling conditional MLEs for Alt.
[#1] INFO:InputArguments -- Using a ToyMCSampler. Now configuring for Alt.
[#0] PROGRESS:Generation -- generated toys: 500 / 1000
[#1] INFO:ObjectHandling -- RooWorkspace::saveSnaphot(w) replacing previous snapshot with name ModelConfig__snapshot
=== Using the following for ModelConfig ===
Observables: RooArgSet:: = (Nobs_SR,Nobs_CR)
Parameters of Interest: RooArgSet:: = (mu)
Nuisance Parameters: RooArgSet:: = (B)
PDF: RooProdPdf::model[ model_SR * model_CR ] = 8.1663e-13
Snapshot:
1) 0x7f839172c370 RooRealVar:: mu = 5.37931 L(-1 - 10) "mu"
=== Using the following for BonlyModel ===
Observables: RooArgSet:: = (Nobs_SR,Nobs_CR)
Parameters of Interest: RooArgSet:: = (mu)
Nuisance Parameters: RooArgSet:: = (B)
PDF: RooProdPdf::model[ model_SR * model_CR ] = 8.1663e-13
Snapshot:
1) 0x7f839172c370 RooRealVar:: mu = 0 L(-1 - 10) "mu"
[#0] PROGRESS:Generation -- Test Statistic on data: 21.3168
[#1] INFO:InputArguments -- Profiling conditional MLEs for Null.
[#1] INFO:InputArguments -- Using a ToyMCSampler. Now configuring for Null.
[#0] PROGRESS:Generation -- generated toys: 500 / 1000
[#1] INFO:InputArguments -- Profiling conditional MLEs for Alt.
[#1] INFO:InputArguments -- Using a ToyMCSampler. Now configuring for Alt.
[#0] PROGRESS:Generation -- generated toys: 500 / 1000
[#1] INFO:ObjectHandling -- RooWorkspace::saveSnaphot(w) replacing previous snapshot with name ModelConfig__snapshot
=== Using the following for ModelConfig ===
Observables: RooArgSet:: = (Nobs_SR,Nobs_CR)
Parameters of Interest: RooArgSet:: = (mu)
Nuisance Parameters: RooArgSet:: = (B)
PDF: RooProdPdf::model[ model_SR * model_CR ] = 2.05924e-13
Snapshot:
1) 0x7f8391624430 RooRealVar:: mu = 5.58621 L(-1 - 10) "mu"
=== Using the following for BonlyModel ===
Observables: RooArgSet:: = (Nobs_SR,Nobs_CR)
Parameters of Interest: RooArgSet:: = (mu)
Nuisance Parameters: RooArgSet:: = (B)
PDF: RooProdPdf::model[ model_SR * model_CR ] = 2.05924e-13
Snapshot:
1) 0x7f8391624430 RooRealVar:: mu = 0 L(-1 - 10) "mu"
[#0] PROGRESS:Generation -- Test Statistic on data: 22.6812
[#1] INFO:InputArguments -- Profiling conditional MLEs for Null.
[#1] INFO:InputArguments -- Using a ToyMCSampler. Now configuring for Null.
[#0] PROGRESS:Generation -- generated toys: 500 / 1000
[#1] INFO:InputArguments -- Profiling conditional MLEs for Alt.
[#1] INFO:InputArguments -- Using a ToyMCSampler. Now configuring for Alt.
[#0] PROGRESS:Generation -- generated toys: 500 / 1000
[#1] INFO:ObjectHandling -- RooWorkspace::saveSnaphot(w) replacing previous snapshot with name ModelConfig__snapshot
=== Using the following for ModelConfig ===
Observables: RooArgSet:: = (Nobs_SR,Nobs_CR)
Parameters of Interest: RooArgSet:: = (mu)
Nuisance Parameters: RooArgSet:: = (B)
PDF: RooProdPdf::model[ model_SR * model_CR ] = 5.09696e-14
Snapshot:
1) 0x7f8391b953d0 RooRealVar:: mu = 5.7931 L(-1 - 10) "mu"
=== Using the following for BonlyModel ===
Observables: RooArgSet:: = (Nobs_SR,Nobs_CR)
Parameters of Interest: RooArgSet:: = (mu)
Nuisance Parameters: RooArgSet:: = (B)
PDF: RooProdPdf::model[ model_SR * model_CR ] = 5.09696e-14
Snapshot:
1) 0x7f8391b953d0 RooRealVar:: mu = 0 L(-1 - 10) "mu"
[#0] PROGRESS:Generation -- Test Statistic on data: 24.0632
[#1] INFO:InputArguments -- Profiling conditional MLEs for Null.
[#1] INFO:InputArguments -- Using a ToyMCSampler. Now configuring for Null.
[#0] PROGRESS:Generation -- generated toys: 500 / 1000
[#1] INFO:InputArguments -- Profiling conditional MLEs for Alt.
[#1] INFO:InputArguments -- Using a ToyMCSampler. Now configuring for Alt.
[#0] PROGRESS:Generation -- generated toys: 500 / 1000
[#1] INFO:ObjectHandling -- RooWorkspace::saveSnaphot(w) replacing previous snapshot with name ModelConfig__snapshot
=== Using the following for ModelConfig ===
Observables: RooArgSet:: = (Nobs_SR,Nobs_CR)
Parameters of Interest: RooArgSet:: = (mu)
Nuisance Parameters: RooArgSet:: = (B)
PDF: RooProdPdf::model[ model_SR * model_CR ] = 1.23954e-14
Snapshot:
1) 0x7f839172c370 RooRealVar:: mu = 6 L(-1 - 10) "mu"
=== Using the following for BonlyModel ===
Observables: RooArgSet:: = (Nobs_SR,Nobs_CR)
Parameters of Interest: RooArgSet:: = (mu)
Nuisance Parameters: RooArgSet:: = (B)
PDF: RooProdPdf::model[ model_SR * model_CR ] = 1.23954e-14
Snapshot:
1) 0x7f839172c370 RooRealVar:: mu = 0 L(-1 - 10) "mu"
[#0] PROGRESS:Generation -- Test Statistic on data: 25.4606
[#1] INFO:InputArguments -- Profiling conditional MLEs for Null.
[#1] INFO:InputArguments -- Using a ToyMCSampler. Now configuring for Null.
[#0] PROGRESS:Generation -- generated toys: 500 / 1000
[#1] INFO:InputArguments -- Profiling conditional MLEs for Alt.
[#1] INFO:InputArguments -- Using a ToyMCSampler. Now configuring for Alt.
[#0] PROGRESS:Generation -- generated toys: 500 / 1000
Print observed limit
In [17]:
cout << 100*inverter.ConfidenceLevel() << "% upper limit : " << result->UpperLimit() << endl;
90% upper limit : 1.29286
compute expected limit
In [18]:
std::cout << "Expected upper limits, using the B (alternate) model : " << std::endl;
std::cout << " expected limit (median) " << result->GetExpectedUpperLimit(0) << std::endl;
std::cout << " expected limit (-1 sig) " << result->GetExpectedUpperLimit(-1) << std::endl;
std::cout << " expected limit (+1 sig) " << result->GetExpectedUpperLimit(1) << std::endl;
std::cout << " expected limit (-2 sig) " << result->GetExpectedUpperLimit(-2) << std::endl;
std::cout << " expected limit (+2 sig) " << result->GetExpectedUpperLimit(2) << std::endl;
Expected upper limits, using the B (alternate) model :
expected limit (median) 0.869595
expected limit (-1 sig) 0.640249
expected limit (+1 sig) 1.27409
expected limit (-2 sig) 0.534798
expected limit (+2 sig) 1.79995
Use the visualization tool of the PLC to show how the interval was calculated
In [19]:
TCanvas* c1 = new TCanvas();
RooStats::HypoTestInverterPlot* plot = new RooStats::HypoTestInverterPlot("HTI_Result_Plot","HypoTest Scan Result",result);
plot->Draw("CLb 2CL"); // plot also CLb and CLs+b
c1->Draw()
