def add_points(graph, directory, layer, usePU):
ipt = graph.GetN()
# List runs
for root, directories, files in os.walk(directory):
for rundir in sorted(directories):
if "run_" in rundir:
# start to process run
run = rundir[4:]
#print "processing run ", run
lumi = 0
lumi_err = 0
# Get informations for a given run
frun = TFile(directory + "/" + rundir +
"/withMasking/rootfile/SiStripHitEffHistos_run" +
run + ".root")
fdir = frun.GetDirectory("SiStripHitEff")
# for efficiency
hfound = fdir.Get("found")
htotal = fdir.Get("all")
if htotal == None:
print ' Missing histogram in file ' + frun.GetName()
continue
# lumi
if usePU == 0: hlumi = fdir.Get("instLumi")
else: hlumi = fdir.Get("PU")
if hlumi == None:
print ' Missing lumi/pu histogram in file ' + frun.GetName(
)
continue
lumi = hlumi.GetMean()
lumi_err = hlumi.GetRMS()
#print "lumi (avg+/-rms): ", lumi, "+/-", lumi_err
# efficiency for a given layer
found = hfound.GetBinContent(layer)
total = htotal.GetBinContent(layer)
if total > 0: eff = found / total
else: eff = 0
#print run, eff, lumi, lumi_err
# remove run without lumi informations
if lumi > 1:
eff_vs_lumi.SetPoint(ipt, lumi, eff)
low = TEfficiency.Bayesian(total, found, .683, 1, 1, False)
up = TEfficiency.Bayesian(total, found, .683, 1, 1, True)
if eff - low > 0.01:
print 'large error bar for run', run, 'layer', layer, 'eff:', '{:.4f}'.format(
eff), 'err:', '{:.4f}'.format(eff - low)
#if lumi_err > lumi/3.: print 'wide lumi range for run', run, 'layer', layer, 'eff:', '{:.4f}'.format(eff), 'lumi/pu:', '{:.4f}'.format(lumi), 'rms:', '{:.4f}'.format(lumi_err)
eff_vs_lumi.SetPointError(ipt, lumi_err, lumi_err,
eff - low, up - eff)
ipt += 1
frun.Close()
def add_points(graph, directory, subdir, layer):
ipt = graph.GetN()
labels = []
# List runs
for root, directories, files in os.walk(directory):
for rundir in sorted(directories):
if "run_" in rundir:
# start to process run
run = rundir[4:]
#print "processing run ", run
# for efficiency
frun = TFile(directory + "/" + rundir + "/" + subdir +
"/rootfile/SiStripHitEffHistos_run" + run +
".root")
fdir = frun.GetDirectory("SiStripHitEff")
hfound = fdir.Get("found")
htotal = fdir.Get("all")
if htotal == None:
print ' Missing histogram in file ' + frun.GetName()
continue
# efficiency for a given layer
found = hfound.GetBinContent(int(layer))
total = htotal.GetBinContent(int(layer))
if total > 0: eff = found / total
else: eff = 0
#print run, eff
graph.SetPoint(ipt, ipt + 1, eff)
labels.append(run)
low = TEfficiency.Bayesian(total, found, .683, 1, 1, False)
up = TEfficiency.Bayesian(total, found, .683, 1, 1, True)
#eff_vs_run.SetPointError(ipt, 0, 0, eff-low, up-eff)
ipt += 1
frun.Close()
axis = graph.GetXaxis()
for i in range(graph.GetN()):
axis.SetBinLabel(axis.FindBin(i + 1), labels[i])
#print i, axis.FindBin(i+1), labels[i]
return labels
def PrintEff(self, Nev):
table = PrettyTable([self.SRname, 'cut-name', 'Eff'])
table.padding_width = 2
nden = int(Nev)
OrderedDict(sorted(self.id.items(), key=lambda t: t[1]))
for name, idd in self.id.iteritems():
nsel = int(self.cut[name])
Eff = float(nsel) / float(Nev)
err_plus = TEfficiency.Bayesian(nden, nsel, .6827, 0.5,0.5, True)
err_minus = TEfficiency.Bayesian(nden, nsel, .6827, 0.5,0.5, False)
Eff = str(Eff) + ' + ' + str(abs(err_plus-Eff)) +" - " +str(abs(err_minus-Eff))
table.add_row( [idd, name, Eff] )
#print '='*10 +' '+ self.SRname +' '+ '='*10
print table
