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Reference Guide
StandardFrequentistDiscovery.C File Reference

Detailed Description

View in nbviewer Open in SWAN StandardFrequentistDiscovery

This is a standard demo that can be used with any ROOT file prepared in the standard way. You specify:

  • name for input ROOT file
  • name of workspace inside ROOT file that holds model and data
  • name of ModelConfig that specifies details for calculator tools
  • name of dataset

With default parameters the macro will attempt to run the standard hist2workspace example and read the ROOT file that it produces.

pict1_StandardFrequentistDiscovery.C.png
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
=== Using the following for ModelConfigNull ===
Observables: RooArgSet:: = (obs_x_channel1)
Parameters of Interest: RooArgSet:: = (SigXsecOverSM)
Nuisance Parameters: RooArgSet:: = (alpha_syst3,beta_syst2,gamma_stat_channel1_bin_0,gamma_stat_channel1_bin_1)
Global Observables: RooArgSet:: = (nom_beta_syst2,nom_alpha_syst3,nom_gamma_stat_channel1_bin_0,nom_gamma_stat_channel1_bin_1)
PDF: RooProdPdf::model_channel1[ lumiConstraint * alpha_syst1Constraint * beta_syst2Constraint * alpha_syst3Constraint * gamma_stat_channel1_bin_0_constraint * gamma_stat_channel1_bin_1_constraint * channel1_model(obs_x_channel1) ] = 0.208662
Snapshot:
1) 0x41b4f00 RooRealVar:: SigXsecOverSM = 0 L(0 - 3) "SigXsecOverSM"
=== Using the following for ModelConfig ===
Observables: RooArgSet:: = (obs_x_channel1)
Parameters of Interest: RooArgSet:: = (SigXsecOverSM)
Nuisance Parameters: RooArgSet:: = (alpha_syst3,beta_syst2,gamma_stat_channel1_bin_0,gamma_stat_channel1_bin_1)
Global Observables: RooArgSet:: = (nom_beta_syst2,nom_alpha_syst3,nom_gamma_stat_channel1_bin_0,nom_gamma_stat_channel1_bin_1)
PDF: RooProdPdf::model_channel1[ lumiConstraint * alpha_syst1Constraint * beta_syst2Constraint * alpha_syst3Constraint * gamma_stat_channel1_bin_0_constraint * gamma_stat_channel1_bin_1_constraint * channel1_model(obs_x_channel1) ] = 0.208662
Snapshot:
1) 0x41b4870 RooRealVar:: SigXsecOverSM = 1 L(0 - 3) "SigXsecOverSM"
[#0] PROGRESS:Generation -- Test Statistic on data: 2.00338
[#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
Results HypoTestCalculator_result:
- Null p-value = 0.515 +/- 0.0158043
- Significance = -0.0376083 +/- 0.0396435 sigma
- Number of Alt toys: 1000
- Number of Null toys: 1000
- Test statistic evaluated on data: 2.00338
- CL_b: 0.515 +/- 0.0158043
- CL_s+b: 0.767 +/- 0.0133683
- CL_s: 1.48932 +/- 0.0525612
total CPU time: 14.86
total real time: 15.14
(double) 0.51500000
#include "TFile.h"
#include "TROOT.h"
#include "TH1F.h"
#include "TF1.h"
#include "TCanvas.h"
#include "TStopwatch.h"
#include "RooWorkspace.h"
#include "RooAbsData.h"
#include "RooRandom.h"
#include "RooRealSumPdf.h"
#include "TSystem.h"
#include <vector>
using namespace RooFit;
using namespace RooStats;
double StandardFrequentistDiscovery(const char *infile = "", const char *workspaceName = "channel1",
const char *modelConfigNameSB = "ModelConfig", const char *dataName = "obsData",
int toys = 1000, double poiValueForBackground = 0.0, double poiValueForSignal = 1.0)
{
// The workspace contains the model for s+b. The b model is "autogenerated"
// by copying s+b and setting the one parameter of interest to zero.
// To keep the script simple, multiple parameters of interest or different
// functional forms of the b model are not supported.
// for now, assume there is only one parameter of interest, and these are
// its values:
// -------------------------------------------------------
// First part is just to access a user-defined file
// or create the standard example file if it doesn't exist
const char *filename = "";
if (!strcmp(infile, "")) {
filename = "results/example_channel1_GammaExample_model.root";
bool fileExist = !gSystem->AccessPathName(filename); // note opposite return code
// if file does not exists generate with histfactory
if (!fileExist) {
#ifdef _WIN32
cout << "HistFactory file cannot be generated on Windows - exit" << endl;
return -1;
#endif
// Normally this would be run on the command line
cout << "will run standard hist2workspace example" << endl;
gROOT->ProcessLine(".! prepareHistFactory .");
gROOT->ProcessLine(".! hist2workspace config/example.xml");
cout << "\n\n---------------------" << endl;
cout << "Done creating example input" << endl;
cout << "---------------------\n\n" << endl;
}
} else
filename = infile;
// Try to open the file
TFile *file = TFile::Open(filename);
// if input file was specified byt not found, quit
if (!file) {
cout << "StandardRooStatsDemoMacro: Input file " << filename << " is not found" << endl;
return -1;
}
// -------------------------------------------------------
// Tutorial starts here
// -------------------------------------------------------
TStopwatch *mn_t = new TStopwatch;
mn_t->Start();
// get the workspace out of the file
RooWorkspace *w = (RooWorkspace *)file->Get(workspaceName);
if (!w) {
cout << "workspace not found" << endl;
return -1.0;
}
// get the modelConfig out of the file
ModelConfig *mc = (ModelConfig *)w->obj(modelConfigNameSB);
// get the data out of the file
RooAbsData *data = w->data(dataName);
// make sure ingredients are found
if (!data || !mc) {
w->Print();
cout << "data or ModelConfig was not found" << endl;
return -1.0;
}
firstPOI->setVal(poiValueForSignal);
// create null model
ModelConfig *mcNull = mc->Clone("ModelConfigNull");
firstPOI->setVal(poiValueForBackground);
// ----------------------------------------------------
// Configure a ProfileLikelihoodTestStat and a SimpleLikelihoodRatioTestStat
// to use simultaneously with ToyMCSampler
plts->SetOneSidedDiscovery(true);
plts->SetVarName("q_{0}/2");
// ----------------------------------------------------
// configure the ToyMCImportanceSampler with two test statistics
ToyMCSampler toymcs(*plts, 50);
// Since this tool needs to throw toy MC the PDF needs to be
// extended or the tool needs to know how many entries in a dataset
// per pseudo experiment.
// In the 'number counting form' where the entries in the dataset
// are counts, and not values of discriminating variables, the
// datasets typically only have one entry and the PDF is not
// extended.
if (!mc->GetPdf()->canBeExtended()) {
if (data->numEntries() == 1) {
toymcs.SetNEventsPerToy(1);
} else
cout << "Not sure what to do about this model" << endl;
}
// We can use PROOF to speed things along in parallel
// ProofConfig pc(*w, 2, "user@yourfavoriteproofcluster", false);
ProofConfig pc(*w, 2, "", false);
// toymcs.SetProofConfig(&pc); // enable proof
// instantiate the calculator
FrequentistCalculator freqCalc(*data, *mc, *mcNull, &toymcs);
freqCalc.SetToys(toys, toys); // null toys, alt toys
// Run the calculator and print result
HypoTestResult *freqCalcResult = freqCalc.GetHypoTest();
freqCalcResult->GetNullDistribution()->SetTitle("b only");
freqCalcResult->GetAltDistribution()->SetTitle("s+b");
freqCalcResult->Print();
double pvalue = freqCalcResult->NullPValue();
// stop timing
mn_t->Stop();
cout << "total CPU time: " << mn_t->CpuTime() << endl;
cout << "total real time: " << mn_t->RealTime() << endl;
// plot
TCanvas *c1 = new TCanvas();
HypoTestPlot *plot = new HypoTestPlot(*freqCalcResult, 100, -0.49, 9.51);
plot->SetLogYaxis(true);
// add chi2 to plot
int nPOI = 1;
TF1 *f = new TF1("f", TString::Format("1*ROOT::Math::chisquared_pdf(2*x,%d,0)", nPOI), 0, 20);
f->SetLineColor(kBlack);
f->SetLineStyle(7);
plot->AddTF1(f, TString::Format("#chi^{2}(2x,%d)", nPOI));
plot->Draw();
c1->SaveAs("standard_discovery_output.pdf");
return pvalue;
}
Authors
Sven Kreiss, Kyle Cranmer

Definition in file StandardFrequentistDiscovery.C.