using namespace RooFit;
using namespace RooStats;

void exercise_2() {
  //Open the rootfile and get the workspace from the exercise_0
  TFile *fInput = new TFile("Workspace_mumufit.root");
  RooWorkspace *w = (RooWorkspace*)fInput->Get("w");
  w->Print();

  // You can set constant parameters that are known
  // If you leave them floating, the fit procedure will determine their uncertainty
  // Right now we will fix all the nuisance parameters just to speed up the computing time
  w->var("meanJpsi")->setConstant(1);
  w->var("sigmaJpsi")->setConstant(1);
  w->var("alphaJpsi")->setConstant(1);
  w->var("nJpsi")->setConstant(1);
  w->var("NJpsi")->setConstant(1);
  w->var("meanpsi2S")->setConstant(1);
  w->var("Nbkg")->setConstant(1);
  w->var("a1")->setConstant(1);
  w->var("a2")->setConstant(1);
  w->var("a3")->setConstant(1);


  // Configure the model, we need both the S+B and the B only models
  ModelConfig sbModel = ModelConfig();
  sbModel.SetWorkspace(*w);
  sbModel.SetPdf("totPDF");
  sbModel.SetName("S+B Model");
  RooRealVar varpoi = (*(w->var("Npsi")));
  varpoi.setRange(0.,20.);  // this is mostly for plotting
  RooArgSet poi(varpoi);
  sbModel.SetParametersOfInterest(RooArgSet(varpoi));

  sbModel.Print();

  // the B only model
  ModelConfig bModel = ModelConfig();
  bModel.SetWorkspace(*w);
  bModel.SetPdf("totPDF");
  bModel.SetName( (TString::Format("%s_with_poi_0",sbModel.GetName()).Data()));
  varpoi.setVal(0);
  bModel.SetSnapshot(poi);
  bModel.SetParametersOfInterest(RooArgSet(varpoi));

  bModel.Print();

  // First example is with a frequentist approach
  FrequentistCalculator fc(*(w->data("data")), bModel, sbModel);
  fc.SetToys(2500,1500);

  // Create hypotest inverter passing the desired calculator 
  HypoTestInverter calc(fc);

   
}