def frequentistCalculator( ):
"""Compute the significance (hypothesis test) using a frequentist calculator"""
warnings.filterwarnings( action='ignore', category=RuntimeWarning, message='.*class stack<RooAbsArg\*,deque<RooAbsArg\*> >' )
inFile = TFile('Rootfiles/workspace_QCD_RPVSt100tojj_FitP4Gaus_rooFit_1fb.root')
myWS = inFile.Get("myWS")
data = myWS.data("data_obs")
sbModel = myWS.obj("modelConfig")
sbModel.SetName("S+B Model")
#sbModel.GetParametersOfInterest().first().setVal(5.)
#sbModel.GetParametersOfInterest().first().setConstant()
sbModel.SetSnapshot( sbModel.GetParametersOfInterest() )
bModel = sbModel.Clone()
bModel.SetName("B Model")
bModel.GetParametersOfInterest().first().setVal(0.)
bModel.GetParametersOfInterest().first().setConstant()
bModel.SetSnapshot( bModel.GetParametersOfInterest() )
#c1 = TCanvas('c1', 'c1', 10, 10, 750, 500 )
#test = data.reduce( RooFit.Name('test'))
#testHisto = TH1D('test','test', 10, 80, 180)
#testHisto = test.fillHistogram( testHisto, RooArgList(x) )
#testHisto.Draw()
#x = RooRealVar( "x", "x", 50., 180. )
#testHisto = sbModel.GetPdf()
#xframe = x.frame()
#testHisto.plotOn( xframe )
#c1.SaveAs("test.pdf")
# create the AsymptoticCalculator from data,alt model, null model
################################### Here, roostats is fitting again and the parameters are wrong.
asym_calc = RooStats.AsymptoticCalculator(data, bModel, sbModel)
asym_calc.SetOneSidedDiscovery( True )
result = asym_calc.GetHypoTest()
result.Print()
tw = TStopwatch()
tw.Start()
# Frequentist calculator
fc = RooStats.FrequentistCalculator(data, bModel, sbModel)
fc.SetToys(10,10)
# create the test statistics
profll = RooStats.ProfileLikelihoodTestStat( sbModel.GetPdf() )
profll.SetOneSidedDiscovery( True )
# configure ToyMCSampler and set the test statistics
toymcs = RooStats.ToyMCSampler( fc.GetTestStatSampler() )
toymcs.SetTestStatistic( profll )
pc = RooStats.ProofConfig( myWS, 10, "", 0 ) #ROOT.kFALSE)
toymcs.SetProofConfig(pc) # enable proof
########################################## change to 0
if not sbModel.GetPdf().canBeExtended(): toymcs.SetNEventsPerToy(0)
# run the test
fqResult = RooStats.HypoTestResult( fc.GetHypoTest() )
fqResult.Print()
tw.Stop()
print tw.CpuTime(), tw.RealTime()
c1 = TCanvas('c1', 'c1', 10, 10, 750, 500 )
plot = RooStats.HypoTestPlot( fqResult )
plot.SetLogYaxis(true)
plot.Draw()
c1.SaveAs("Plots/Significance.pdf")
pod = w.var("mu").getVal()
w.var("mu").setVal(float(sys.argv[3]))
mu_val = str(sys.argv[3])
bMod.SetSnapshot(w.argSet("mu"))
w.var("mu").setVal(pod)
mc.SetSnapshot(w.argSet("mu"))
# Freq. Calcf
#fcalc = RooStats.FrequentistCalculator(dh, bMod, mc)
#fcalc.SetToys(300,300)
# Asymp. Calc
print("dh", dh)
print("bMod", bMod)
print("mc", mc)
fcalc = RooStats.AsymptoticCalculator(dh, bMod, mc)
# fcalc.SetToys(300,300)
# Hypo Test Inverter
hi = RooStats.HypoTestInverter(fcalc)
hi.SetConfidenceLevel(0.95)
useCLs = False
hi.UseCLs(useCLs)
toymcs = hi.GetHypoTestCalculator().GetTestStatSampler()
# profile likelihood test statistics
profll = RooStats.ProfileLikelihoodTestStat(mc.GetPdf())
# for CLs (bounded intervals) use one-sided profile likelihood
if (useCLs): profll.SetOneSided(True)
# ratio of profile likelihood - need to pass snapshot for the alt
