from ROOT import *

# Model built with Low Level Factory
export_namespace=True
w = RooWorkspace("CMGWs",export_namespace)
w.factory("Gaussian::signal(imass[110,120],sigmean[115,105,120],sigwidth[1])")
w.factory("Exponential::background(imass,exppar[-.1,-1,0])")
w.factory("SUM::modelbase(nsig[50,0,120]*signal,nbkg[1000,0,10000]*background)")
w.factory("Gaussian::nbkgConstraint(nbkg,1000,1)") # 0.1% background uncertainty
w.factory("PROD::model(modelbase,nbkgConstraint)") #implement a systematic

# Promote everithing to global scope
# You could have accessed everithing via CMGWs.<name>
for name,obj in CMGWs.__dict__.items():
  if type(obj) == PropertyProxy: 
    exec("%s=CMGWs.%s" %(name,name))

imass.setBins(30)

# Create an example dataset (binned is fast..)
data = CMGWs.model.generateBinned(RooArgSet(imass))

# Model Config
modelConfig = RooStats.ModelConfig(w)
modelConfig.SetPdf(model)
modelConfig.SetParametersOfInterest(RooArgSet(nsig))

# Let's use a Calculator based on the Profile Likelihood Ratio
CL = .68; size = 1-CL # size of the test
plc=RooStats.ProfileLikelihoodCalculator(data,modelConfig,size)
lrint = plc.GetInterval()

# Calculate the significance: SL2 estimator
nsig.setVal(0)
plc.SetNullParameters(RooArgSet(nsig))
SL2 = plc.GetHypoTest().Significance()

print "Limits [%.2f-%.2f] - Significance %.2f" %(lrint.LowerLimit(nsig),lrint.UpperLimit(nsig),SL2)

raw_input ("Press a key to continue")