def GetLimits(tl,f):
from ROOT import RooStats,Util
#w=gDirectory.Get("w")
print "analysis name: ",tl.name
print "workspace name: ",tl.wsFileName
if not ("SU" in tl.name):
print "Do no hypothesis test for bkg only or discovery fit!\n"
return
print "Need to load workspace"
Util.ReadWorkspace(tl.wsFileName,"combined")
w=gDirectory.Get("w")
result = RooStats.MakeUpperLimitPlot(tl.name,w,2,3,1000,True,20,True)
if not result==0:
result.Print()
print result.UpperLimit()
return
def latexfitresults(filename, poiname='mu_Sig', lumiFB=1.0,
nTOYS=3000, asimov=False, wname='combined'):
workspacename=wname
w = Util.GetWorkspaceFromFile(filename,workspacename)
if w==None:
print "ERROR : Cannot open workspace : ", workspacename
sys.exit(1)
if len(poiname)==0:
print " "
else:
modelConfig = w.obj("ModelConfig")
poi = w.var(poiname)
if poi==None:
print "ERROR : Cannot find POI with name: ", poiname, " in workspace from file ", filename
sys.exit(1)
modelConfig.SetParametersOfInterest(RooArgSet(poi))
modelConfig.GetNuisanceParameters().remove(poi)
ntoys = 3000
calctype = 0 # toys = 0, asymptotic (asimov) = 2
npoints = 20
if nTOYS != 3000 and nTOYS>0:
ntoys = nTOYS
if asimov:
calctype = 2
hti_result = RooStats.MakeUpperLimitPlot(
poiname,w,calctype,3,ntoys,True,npoints)
outFileName = "./htiResult_poi_" + poiname + "_ntoys_" + str(ntoys) + "_calctype_" + str(calctype) + "_npoints_" + str(npoints) + ".root"
hti_result.SaveAs(outFileName)
hti_result.Print()
uL_nobsinSR = hti_result.UpperLimit()
uL_visXsec = uL_nobsinSR / lumiFB
# uL_visXsecErrorUp = uL_visXsec - uL_nobsinSR/(lumiFB * (1. + lumiRelUncert))
# uL_visXsecErrorDown = uL_nobsinSR/(lumiFB * (1. - lumiRelUncert)) - uL_visXsec
uL_nexpinSR = hti_result.GetExpectedUpperLimit(0)
uL_nexpinSR_P = hti_result.GetExpectedUpperLimit(1)
uL_nexpinSR_M = hti_result.GetExpectedUpperLimit(-1)
if uL_nexpinSR > uL_nexpinSR_P or uL_nexpinSR < uL_nexpinSR_M:
print " \n something very strange, either the uL_nexpinSR > uL_nexpinSR_P or uL_nexpinSR < uL_nexpinSR_M"
print " uL_nexpinSR = ", uL_nexpinSR , " uL_nexpinSR_P = ", uL_nexpinSR_P, " uL_nexpinSR_M = ", uL_nexpinSR_M
uL_nexpinSRerrP = hti_result.GetExpectedUpperLimit(1) - uL_nexpinSR
uL_nexpinSRerrM = uL_nexpinSR - hti_result.GetExpectedUpperLimit(-1)
# find the CLB values at indexes above and below observed CLs p-value
CLB_P = 0.
CLB_M = 0.
mu_P = 0.
mu_M = 0.
index_P = 0
indexFound = False
for iresult in range(hti_result.ArraySize()):
xval = hti_result.GetXValue(iresult)
yval = hti_result.GetYValue(iresult)
if xval>uL_nobsinSR and not indexFound:
index_P = iresult
CLB_P = hti_result.CLb(iresult)
mu_P = xval
if iresult>0:
CLB_M = hti_result.CLb(iresult-1)
mu_M = hti_result.GetXValue(iresult-1)
indexFound = True
# print " \n found the CLB values to interpolate"
# print " CLB_M =", CLB_M, " CLB_P =", CLB_P, " mu_P = ", mu_P, " mu_M = ", mu_M
# interpolate the value of CLB to be exactly above upperlimit p-val
alpha_CLB = (CLB_P - CLB_M) / (mu_P - mu_M)
beta_CLB = CLB_P - alpha_CLB*mu_P
# CLB is taken as the point on the CLB curve for the same poi value,
# as the observed upperlimit
CLB = alpha_CLB * uL_nobsinSR + beta_CLB
#print " CLB = " , CLB
print "\n\n\n\n ***--- now doing p-value calculation ---*** \n\n\n\n"
pval = RooStats.get_Presult(w,False,1000,2)
print "p-value is: ", pval
ulList = [uL_visXsec, uL_nobsinSR, uL_nexpinSR, uL_nexpinSRerrP, uL_nexpinSRerrM, CLB, pval ]
return ulList
