def makeOptGraphs(category, higgswindow, compileOrLoad):
#cosThetaCutValue = 0.7
print "making optgraphs for category %s, window (%i-%i)" % (
category, higgswindow[0], higgswindow[1])
graphs = []
massWindows = getMassWindows()
massWindows.pop(2000)
massWindows.pop(3000)
cutValues = getCutValues()
pToverMcutValue = cutValues["ptOverM"]
deltaRcutValue = cutValues["deltaR"]
jetEtaCutValue = cutValues["jetEta"]
phoEtaCutValue = cutValues["phEta"]
for mass in getSortedDictKeys(massWindows):
print "making S/rootB optGraph for mass %s" % mass
masswindow = massWindows[mass]
graphs.append(TGraph())
graphs[-1].SetNameTitle(
"HbbOpt", "S/#sqrt{B}, M=%s, higgs window %s-%s" %
(str(mass), str(higgswindow[0]), str(higgswindow[1])))
#print "Signal mass %f" % mass
# just keep the name from TTree::MakeClass(), don't give it a special name
samplesDirs = getSamplesDirs()
fillGraph(graphs[-1], dataOrMCbg, str(mass), higgswindow, masswindow,
category, pToverMcutValue, deltaRcutValue, jetEtaCutValue,
phoEtaCutValue, compileOrLoad)
compileOrLoad = "load"
canvas = TCanvas()
canvas.cd()
option = ""
iGraph = 0
for graph in graphs:
graph.Draw(option)
x = TColor()
graph.SetLineColor(x.GetColor(0, 0.9 - iGraph * 0.15, iGraph * 0.15))
graph.SetFillColor(kWhite)
iGraph += 1
option = "SAME"
outfile = TFile(
"HbbOpt_SoverRootB_higgsWindow_%i-%i.root" %
(higgswindow[0], higgswindow[1]), "RECREATE")
outfile.cd()
canvas.BuildLegend()
canvas.Draw()
legend = canvas.GetPrimitive("TPave")
legend.SetHeader("%s category" % category)
for prim in canvas.GetListOfPrimitives():
if "HbbOpt" in prim:
prim.SetTitle("H(b#bar{b})#gamma optimization: S/#sqrt{B}")
prim.GetXaxis().SetRangeUser(0, 2500)
canvas.Write()
outfile.Close()
def processHg(inputFileName, outputFileName, load, loopMode = False, btagVariation=0):
if inputFileName is None:
print "\nPlease specify the input file with the -i option."
exit(1)
elif outputFileName is None:
print "\nPlease specify the output filename with the -o option."
exit(1)
elif not os.path.isfile(inputFileName):
print "\nThe input file specified was not found: %s" % inputfileName
exit(1)
print "\nInput file is %s\n" % inputFileName
presentTense = "load" if load else "compile"
pastTense = "loaded" if load else "compiled"
print "\nAttempting to %s HgammaSelector.\n" % presentTense
# call the compiling function to compile the HgammaSelector, then run its Loop() method
if presentTense=="compile" and not loopMode:
deleteLibs("HgammaSelector")
# compile the macro using g++ and check compilation status
exitCode = gSystem.CompileMacro("HgammaSelector.C", "gOck")
success=(exitCode==1)
elif presentTense=="load" and not loopMode:
exitCode = gSystem.Load('HgammaSelector_C')
success=(exitCode>=-1)
if not loopMode:
if not success:
print "\nError... HgammaSelector failed to %s. :-("%presentTense
print "Make sure you're using an up-to-date version of ROOT by running cmsenv in a 7_4_X>=16 CMSSW area."
exit(1)
print "\nHgammaSelector %s successfully."%pastTense
if presentTense=="compile" and not loopMode:
gSystem.Load('HgammaSelector_C')
inputFile = TFile(inputFileName)
print "testing"
from pprint import pprint
from os.path import basename
sampleDirs = getSamplesDirs()
weights = getMCbgWeightsDict(sampleDirs["bkgSmall3sDir"])
pprint(weights)
shortName = basename(inputFile.GetName()).replace("smallified_", "")
print shortName
weight = 1.
if shortName in weights.keys():
weight = weights[shortName][0]
print "weight for this sample:", weight
# get the ntuplizer/tree tree from the file specified by argument 1
tree = inputFile.Get("ntuplizer/tree")
instance = HgammaSelector(tree)
# run the HgammaSelector::Loop method
instance.Loop(outputFileName, btagVariation, weight)
print "Number of events for signal with mass %i is %i" % (mass, nGenEvents)
eff = sigAndBGinfo["S"]/nGenEvents
seff = eff*quadratureUncertainties
bck = sigAndBGinfo["B"]
sbck = sigAndBGinfo["B"]*quadratureUncertainties
expectedLimit = CLA(ilum, slum, eff, seff, bck, sbck)
print "expected limit is: %f" % expectedLimit
compileOrLoad = "load"
response = {}
response["compileOrLoad"]="load"
response["expectedLimit"]=expectedLimit
return response
samplesDirs = getSamplesDirs()
small3sDir = samplesDirs["small3sDir"]
ddDir = samplesDirs["ddDir"]
massWindows = getMassWindows()
def useHbbTag(cosThetaCutValue):
if testTwoMasses:
del massWindows[1000]
del massWindows[2000]
graphs = []
compileOrLoad = "compile"
for mass in massWindows.keys():
graphs.append(TGraph())
graphs[-1].SetNameTitle(str(mass), str(mass))
#for i in range(-10, 20): # TODO make some reasonable way of chosing the step size and bounds for the optimization scan
# HbbCutValue = i/float(20)
