rs401c_FeldmanCousins.C

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/// \file
/// \ingroup tutorial_roostats
/// \notebook
/// Produces an interval on the mean signal in a number counting
/// experiment with known background using the Feldman-Cousins technique.
///
/// Using the RooStats FeldmanCousins tool with 200 bins
/// it takes 1 min and the interval is [0.2625, 10.6125]
/// with a step size of 0.075.
/// The interval in Feldman & Cousins's original paper is [.29, 10.81]
///  Phys.Rev.D57:3873-3889,1998.
////
/// \macro_image
/// \macro_output
/// \macro_code
///
/// \author Kyle Cranmer
 
#include "RooGlobalFunc.h"
#include "RooStats/ConfInterval.h"
#include "RooStats/PointSetInterval.h"
#include "RooStats/ConfidenceBelt.h"
#include "RooStats/FeldmanCousins.h"
#include "RooStats/ModelConfig.h"
 
#include "RooWorkspace.h"
#include "RooDataSet.h"
#include "RooRealVar.h"
#include "RooConstVar.h"
#include "RooAddition.h"
 
#include "RooDataHist.h"
 
#include "RooPoisson.h"
#include "RooPlot.h"
 
#include "TCanvas.h"
#include "TTree.h"
#include "TH1F.h"
#include "TMarker.h"
#include "TStopwatch.h"
 
#include <iostream>
 
// use this order for safety on library loading
using namespace RooFit;
using namespace RooStats;
 
 
void rs401c_FeldmanCousins()
{
   // to time the macro... about 30 s
   TStopwatch t;
   t.Start();
 
   // make a simple model
   RooRealVar x("x","", 1,0,50);
   RooRealVar mu("mu","", 2.5,0, 15); // with a limit on mu>=0
   RooConstVar b("b","", 3.);
   RooAddition mean("mean","",RooArgList(mu,b));
   RooPoisson pois("pois", "", x, mean);
   RooArgSet parameters(mu);
 
   // create a toy dataset
   RooDataSet* data = pois.generate(RooArgSet(x), 1);
   data->Print("v");
 
   TCanvas* dataCanvas = new TCanvas("dataCanvas");
   RooPlot* frame = x.frame();
   data->plotOn(frame);
   frame->Draw();
   dataCanvas->Update();
 
   RooWorkspace* w = new RooWorkspace();
   ModelConfig modelConfig("poissonProblem",w);
   modelConfig.SetPdf(pois);
   modelConfig.SetParametersOfInterest(parameters);
   modelConfig.SetObservables(RooArgSet(x));
   w->Print();
 
   //////// show use of Feldman-Cousins
   RooStats::FeldmanCousins fc(*data,modelConfig);
   fc.SetTestSize(.05); // set size of test
   fc.UseAdaptiveSampling(true);
   fc.FluctuateNumDataEntries(false); // number counting analysis: dataset always has 1 entry with N events observed
   fc.SetNBins(100); // number of points to test per parameter
 
   // use the Feldman-Cousins tool
   PointSetInterval* interval = (PointSetInterval*)fc.GetInterval();
 
   // make a canvas for plots
   TCanvas* intervalCanvas =  new TCanvas("intervalCanvas");
 
   std::cout << "is this point in the interval? " <<
      interval->IsInInterval(parameters) << std::endl;
 
   std::cout << "interval is ["<<
      interval->LowerLimit(mu)  << ", "  <<
      interval->UpperLimit(mu) << "]" << endl;
 
   // using 200 bins it takes 1 min and the answer is
   // interval is [0.2625, 10.6125] with a step size of .075
   // The interval in Feldman & Cousins's original paper is [.29, 10.81]
   //  Phys.Rev.D57:3873-3889,1998.
 
   // No dedicated plotting class yet, so do it by hand:
 
   RooDataHist* parameterScan = (RooDataHist*) fc.GetPointsToScan();
   TH1F* hist = (TH1F*) parameterScan->createHistogram("mu",30);
   hist->Draw();
 
 
   RooArgSet* tmpPoint;
   // loop over points to test
   for(Int_t i=0; i<parameterScan->numEntries(); ++i){
      //    cout << "on parameter point " << i << " out of " << parameterScan->numEntries() << endl;
      // get a parameter point from the list of points to test.
      tmpPoint = (RooArgSet*) parameterScan->get(i)->clone("temp");
 
      TMarker* mark = new TMarker(tmpPoint->getRealValue("mu"), 1, 25);
      if (interval->IsInInterval( *tmpPoint ) )
         mark->SetMarkerColor(kBlue);
      else
         mark->SetMarkerColor(kRed);
 
      mark->Draw("s");
      //delete tmpPoint;
      //    delete mark;
   }
   t.Stop();
   t.Print();
 
 
}