def addSRdata(region='SR_OS', pol=''):
# first get QCD estimate with data driven W
if pol:
groups = mu.MC + [getattr(mu, pol)]
else:
groups = mu.MC + [mu.signal]
data = hist.get_QCDW(rf,
mu,
entry,
'SR_SS',
rqcd=rQCD,
verbose=False,
groups=groups)
for group in groups:
if group.name == 'Wlnu':
h = hist.get_dataW(rf,
mu,
entry,
'WCR_OS',
verbose=False,
groups=groups)
else:
h = hist.get_OS(rf, entry, group, region)
data.Add(h)
data.SetName('h_upsilon_SRData%s_SR_OS' % pol)
for bin in xrange(data.GetNbinsX() + 1):
data.SetBinError(bin, math.sqrt(data.GetBinContent(bin)))
print ErrorFloat(*hist.IntegralError(data))
#check similar errors
#d1 = rf.Get('h_visMass_Muons_SR_OS')
#print ErrorFloat(*hist.IntegralError(d1))
data.Write()
def compare_scales():
rf = ROOT.TFile('../output/%s/%s_regions.root' %
(stream + '_Zpt_NoWeight', stream))
wf = ROOT.TFile('../output/%s/%s_regions.root' % (stream + '_Zpt', stream))
tname = 'h_upsilon_Ztautau_SR_OS'
lname = 'h_upsilon_LH_Ztautau_SR_OS'
rname = 'h_upsilon_RH_Ztautau_SR_OS'
for name in [tname, lname, rname]:
t1 = rf.Get(name).Clone('t1')
t2 = wf.Get(name).Clone('t2')
n1 = ErrorFloat(*hist.IntegralError(t1))
n2 = ErrorFloat(*hist.IntegralError(t2))
print n1
print n2
print n2 / n1
def stat_error(mu):
rf = ROOT.TFile('%s/%s_regions.root' % (OUTPUT_DIR,mu.name))
k_entry = Drawer.upsilon_28
wSR_MC = rf.Get('h_%s_%s_%s' % (k_entry.name,mu.Wlnu.name,'SR_OS'))
nMC = ErrorFloat(*hist.IntegralError(wSR_MC))
# print ErrorFloat( wSR_MC.GetBinContent(10), wSR_MC.GetBinError(10) )
kW_OS = hist.calc_kX(rf,mu,k_entry,'WCR','Wlnu',OS='OS')
# print kW_OS * nMC
# wSR_MC.Scale(kW_OS.val)
for bin in xrange(wSR_MC.GetNbinsX()+1):
bi0 = ErrorFloat(wSR_MC.GetBinContent(bin), wSR_MC.GetBinError(bin))
bi1 = bi0 * ErrorFloat(kW_OS.val,0)
bi2 = bi0 * kW_OS
# print bi0,bi1,bi2
wSR_MC.SetBinContent(bin,bi2.val)
wSR_MC.SetBinError(bin,bi2.err)
nMCkw = ErrorFloat(*hist.IntegralError(wSR_MC))
print nMCkw
def backgrounds(mu):
rf = ROOT.TFile('%s/%s_regions.root' % (OUTPUT_DIR,mu.name))
#rf = ROOT.TFile('~/panalysis/output/%s_Zpt_NoWeight/%s_regions.root' % (mu.name,mu.name))
eff = True
f = False
fcol=15;col=15;fmt="latex"
entry = Drawer.visMass
k_entry = Drawer.upsilon_CR
regions = mu.cutflow
#regions = mu.SR
verbose = True
groups = [mu.Zltau,mu.Zlljet,mu.ttbar,mu.Wlnu]
kW_OS = hist.calc_kX(rf,mu,k_entry,'WCR','Wlnu',OS='OS', verbose = verbose)
a = []
for i,region in enumerate(regions):
cutgroup = []
n = []
mc = 0
for group in groups:
h = rf.Get('h_%s_%s_%s' % (entry.name,group.name,region.name))
if 'W' not in group.name:
cutgroup.append( '%i +/- %i' % hist.IntegralError(h))
n.append(h.Integral(0,h.GetNbinsX()+1))
else:
nW = ErrorFloat(*hist.IntegralError(h))*kW_OS
cutgroup.append('%i +/- %i' % (nW.val,nW.err))
n.append(nW.val)
if group.name not in ['Muons','Egamma','LH_Ztautau','RH_Ztautau']:
mc += h.Integral(0,h.GetNbinsX()+1)
if i == 0: a = list(n); l=a
else: print row(cuts[i]+'\t\t',cutgroup,fcol=fcol,col=col, fmt = fmt)
if f:
print row(region.name, [''] + [x/mc for x in n[1:]],fcol=fcol,col=col,fmt=fmt)
if eff:
print row('',[x/y for (x,y) in zip(n,a)],fcol=fcol,col=col, fmt = fmt)
print row('',[x/y for (x,y) in zip(n,l)],fcol=fcol,col=col, fmt = fmt)
l = n
def print_region(mu,reg, pdg=False):#,regions,groups,entry=Drawer.upsilon_CR,eff=False,twiki=False, fmt = None, f = False):
a = []
rf = ROOT.TFile('%s/%s_regions.root' % (OUTPUT_DIR, mu.name))
regions = getattr(mu,reg)
groups = [mu.data, mu.signal, mu.LH, mu.RH, mu.ttbar, mu.Zlljet, mu.Zltau, mu.Wlnu]
entry = Drawer.upsilon_CR
fmt = ''
if pdg: fmt = 'latex'
print row('',[group.name for group in groups],fcol=fcol,col=col,fmt=fmt)
for i,region in enumerate(regions):
cutgroup = []
n = []
mc = 0
nEW = 0
for group in groups:
if 'Wlnu' in group.name:
wreg = region.name.replace('QCD','WCR')
wreg = wreg.replace('SR','WCR')
#print region
h = hist.get_dataW(rf,mu,entry, wreg, where = reg)
#print h.Integral()
else:
h = rf.Get('h_%s_%s_%s' % (entry.name,group.name,region.name))
norm = h.Integral(0,h.GetNbinsX()+1)
if group.isData:
cutgroup.append(int(norm))
else:
#print h.GetName()
v,e = hist.IntegralError(h, of = True)
if pdg:
cutgroup.append( '%g +/- %g' % pdg_simple.pdg_round(v,e))
else:
cutgroup.append( '%.2f +/- %.2f' % (v,e))
n.append(norm)
if group.isData:
nData = norm
elif 'LH' in group.name:
nL = norm
elif 'RH' in group.name:
nR = norm
elif 'Ztautau' in group.name:
nS = norm
elif 'Wlnu' not in group.name:
nEW += norm
if i == 0: a = list(n); l=a
#if twiki: print twikirow(region.name,cutgroup)
print row(region.name,cutgroup,fcol=fcol,col=col, fmt = fmt)
def sim_modes(sim="Reco"):
rf = ROOT.TFile('~/analysis/truth/cxx/thesis/PythiaFull30.root')
entries = ['upsilon','upsilon20','upsilon40','upsilon60']
modes = ['0','3','4','5']
fracs = []
for i,mode in enumerate(modes):
fracs.append([])
for j,entry in enumerate(entries):
fracs[i].append( ErrorFloat(*hist.IntegralError(rf.Get('%s_%s_%s_LH' % (sim,entry,mode)))))
fracs[i].append(ErrorFloat(*hist.IntegralError(rf.Get('%s_%s_%s_RH' % (sim,entry,mode)))))
nTotal = list(fracs[0])
nOther = None
for i,m in enumerate(modes):
if i == 1: nOther = list(fracs[0])
for j in xrange(len(fracs[i])):
fracs[i][j] = fracs[i][j]/nTotal[j]
fracs[i][j] = round(fracs[i][j].val,2)
if nOther:
nOther[j]-=fracs[i][j]
print row( modelegend[m], fracs[i], fmt='latex' , flt = '%.2f')
print row('Other',nOther, fmt = 'latex', flt = '%.2f')
def sensitivity(rh, lh, p):
c = ROOT.TCanvas()
lh.Scale(1.0 / (lh.Integral())) #(0,lh.GetNbinsX()+1)))
rh.Scale(1.0 / (rh.Integral())) #(0,rh.GetNbinsX()+1)))
summ = lh.Clone()
diff = lh.Clone()
multi = lh.Clone()
ratio = lh.Clone()
sump = lh.Clone()
summ.Add(lh, rh, 1.0, 1.0)
diff.Add(rh, lh, 1.0, -1.0)
scale = 1 / (summ.Integral()) #(0,summ.GetNbinsX()+1 ))
summ.Scale(scale)
diff.Scale(scale)
summ.SetLineColor(2)
diff.SetLineColor(4)
summ.SetAxisRange(-1, 1)
diff.SetAxisRange(-1, 1)
summ.SetMinimum(1.2 * diff.GetMinimum())
summ.Draw()
diff.Draw("SAME")
#diff.Draw()
multi.Multiply(diff, diff)
sump.Add(summ, diff, 1, p)
ratio.Divide(multi, sump)
c.SaveAs('sensTest.gif+1')
s_square = ErrorFloat(*hist.IntegralError(ratio))
s = math.sqrt(s_square.val)
s_err = 0.5 * s_square.err / s_square.val
return ErrorFloat(round(s, 2), round(s_err, 2))
def print_region(rf,regions,groups,entry=Drawer.upsilon,eff=False,twiki=False, fmt = None, f = False):
a = []
for i,region in enumerate(regions):
cutgroup = []
n = []
mc = 0
for group in groups:
h = rf.Get('h_%s_%s_%s' % (entry.name,group.name,region.name))
cutgroup.append( '%i +/- %i' % hist.IntegralError(h))
n.append(h.Integral(0,h.GetNbinsX()+1))
if group.name not in ['Muons','Egamma','LH_Ztautau','RH_Ztautau']:
#print group.name
mc += h.Integral(0,h.GetNbinsX()+1)
if i == 0: a = list(n); l=a
if twiki: print twikirow(region.name,cutgroup)
else: print row(region.name,cutgroup,fcol=fcol,col=col, fmt = fmt)
if f:
print row(region.name, [''] + [x/mc for x in n[1:]],fcol=fcol,col=col,fmt=fmt)
if eff:
print row('',[x/y for (x,y) in zip(n,a)],fcol=fcol,col=col, fmt = fmt)
print row('',[x/y for (x,y) in zip(n,l)],fcol=fcol,col=col, fmt = fmt)
l = n
def cutflow(mu, pdg = True, smnorm = False):
rf = ROOT.TFile('%s/%s_regions.root' % (OUTPUT_DIR, mu.name))
eff = False
do_pol = False
f = False
fcol=25;col=22;fmt="latex"
entry = Drawer.upsilon
regions = mu.noteflow
pt = -0.144
groups = [mu.data, mu.signal, mu.LH, mu.RH, mu.ttbar, mu.Zlljet, mu.Zltau, mu.Wlnu]
a = []
for i,region in enumerate(regions):
cutgroup = []
n = []
mc = 0
nL = None
for group in groups:
if group.isData:
h = rf.Get('h_%s_%s_%s' % ('upsilon',group.name,region.name))
else:
h = rf.Get('h_%s_%s_%s' % (entry.name,group.name,region.name))
#print 'h_%s_%s_%s' % (entry.name,group.name,region.name)
norm = h.Integral(0,h.GetNbinsX()+1)
if group.isData:
cutgroup.append(int(norm))
else:
v,e = hist.IntegralError(h, of = True)
if smnorm:
if 'LH' in group.name:
v = v*sm_lh
e = e*sm_lh
if 'RH' in group.name:
v = v*sm_rh
e = e*sm_rh
if pdg:
cutgroup.append( '%i +/- %i' % pdg_simple.pdg_round(v,e))
else:
cutgroup.append( '%.2f +/- %.2f' % (v,e))
n.append(h.Integral(0,h.GetNbinsX()+1))
if 'L' in group.name: nL = norm
elif 'R' in group.name: nR = norm
if group.name not in ['Muons','Egamma','LH_Ztautau','RH_Ztautau']:
#print group.name
mc += h.Integral(0,h.GetNbinsX()+1)
if i == 0:
a = list(n); l=a
print row('', [group.name for group in groups], fcol =fcol, col = col)
if nL and do_pol:
nL = 0.5*(1-pt)*nL
nR = 0.5*(1+pt)*nR
print row(cuts[i]+'\t\t',cutgroup + [(nR-nL)/(nR+nL)],fcol=fcol,col=col, fmt = fmt)
else:
#print row(region.name , cutgroup , fcol=fcol,col=col, fmt = fmt)
print row(cuts[i], cutgroup , fcol=fcol,col=col, fmt = fmt)
#print (nR-nL)/nR
if f:
print row(region.name, [''] + [x/mc for x in n[1:]],fcol=fcol,col=col,fmt=fmt)
if eff:
print row('',[x/y for (x,y) in zip(n,a)],fcol=fcol,col=col, fmt = fmt)
print row('',[x/y for (x,y) in zip(n,l)],fcol=fcol,col=col, fmt = fmt)
l = n
def signal_region(mu):
#rf = ROOT.TFile('~/panalysis/output/%s_thesis/test/%s_regions.root' % (mu.name,mu.name))
rf = ROOT.TFile('%s/%s_regions.root' % (OUTPUT_DIR, mu.name))
region = 'SR_OS'
k_entry = Drawer.upsilon_CR
entry = Drawer.upsilon
verbose = False
fmt = 'latex'
kW_OS = hist.calc_kX(rf,mu,k_entry,'WCR','Wlnu',OS='OS', verbose = verbose)
kW_OS_L = hist.calc_kX(rf,mu,k_entry,'WCR','Wlnu',OS='OS', verbose = verbose, groups = mu.MC+[mu.LH])
kW_OS_R = hist.calc_kX(rf,mu,k_entry,'WCR','Wlnu',OS='OS', verbose = verbose, groups = mu.MC+[mu.RH])
pdg_simple.testpdg(kW_OS.val,kW_OS.err)
print 'kWOS %g +/ %g' % ( pdg_simple.pdg_round(kW_OS.val,kW_OS.err))
EST = [ErrorFloat(0),ErrorFloat(0),ErrorFloat(0)]
BG = [ErrorFloat(0),ErrorFloat(0),ErrorFloat(0)]
for group in [mu.data,mu.Zlljet,mu.Zltau,mu.ttbar]:
h = rf.Get('h_%s_%s_%s' % (entry.name,group.name,region))
nG = ErrorFloat(*hist.IntegralError(h))
if group.isData:
print row( group.latex, [int(nG.val),'',''], fmt=fmt)
else:
print row( group.latex, ['%i +/- %i'%(nG.val,nG.err),'',''], fmt=fmt, makeint=True)
if not group.isData:
for i in xrange(len(EST)):
EST[i]+=nG
BG[i]+=nG
print row('', ['SM','Left-Handed','Right-Handed'], fmt = fmt)
signal = []
SB = [ErrorFloat(0),ErrorFloat(0),ErrorFloat(0)]
for i,group in enumerate([mu.signal, mu.LH, mu.RH]):
h = rf.Get('h_%s_%s_%s' % (entry.name,group.name,region))
nG = ErrorFloat(*hist.IntegralError(h))
signal.append('%i +/- %i'%(nG.val,nG.err))
EST[i]+=nG
SB[i]=nG
print row(mu.signal.latex, signal, fmt=fmt, makeint = True)
wjets = []
for i,group in enumerate([mu.signal, mu.LH, mu.RH]):
h = hist.get_dataW(rf, mu, Drawer.upsilon, 'WCR_OS', verbose = False, groups = mu.MC + [group])
print '**'
nG = ErrorFloat(*hist.IntegralError(h))
wjets.append('%g +/- %g'%( pdg_simple.pdg_round((nG).val,(nG).err)))
EST[i]+=nG
BG[i]+=nG
print row(mu.Wlnu.latex, wjets, fmt=fmt)
#print row(group.latex, [nG])
QCD = []
for i,group in enumerate([mu.signal, mu.LH, mu.RH]):
kW = hist.calc_kX(rf,mu,k_entry,'WCR','Wlnu',OS='OS', verbose = verbose, groups = mu.MC+[group])
kWSS = hist.calc_kX(rf,mu,k_entry,'WCR','Wlnu',OS='SS', verbose = verbose, groups = mu.MC+[group])
rqcd = hist.calc_rQCD(rf,mu,k_entry,'QCD',kW_OS = kW, kW_SS = kWSS, verbose = verbose, groups = mu.MC+[group])
print '%g +/- %g' % pdg_simple.pdg_round(rqcd.val,rqcd.err)
qcd = hist.get_QCD(rf,mu,entry,'SR_SS', kW = kWSS, rqcd = rqcd, groups = mu.MC +[group])
nG = ErrorFloat(*hist.IntegralError(qcd))
QCD.append('%g +/- %g'% pdg_simple.pdg_round(nG.val,nG.err))
EST[i]+=nG
BG[i]+=nG
print row('Multijet', QCD, fmt=fmt)
for i in xrange(len(EST)):
EST[i] = '%i +/- %i'%(EST[i].val,EST[i].err)
SB[i] = SB[i]/BG[i]
print row('Total Estimate', EST, fmt = fmt)
print row('S:B', SB, fmt = fmt)
def kinematic_plots_SR(mu, entry, ratio=True, verbose=False):
rf = ROOT.TFile('~/panalysis/output/prod4/%s_fit/%s_regions.root' %
(mu.name, mu.name))
region = 'SR_OS'
# scale factors
k_entry = upsilon_CR
kW_OS = hist.calc_kX(rf,
mu,
k_entry,
'WCR',
'Wlnu',
OS='OS',
verbose=verbose)
kW_SS = hist.calc_kX(rf,
mu,
k_entry,
'WCR',
'Wlnu',
OS='SS',
verbose=verbose)
rQCD = hist.calc_rQCD(rf,
mu,
k_entry,
'QCD',
kW_OS=kW_OS,
kW_SS=kW_SS,
verbose=verbose)
# left and right handed
kW_OS_L = hist.calc_kX(rf,
mu,
k_entry,
'WCR',
'Wlnu',
OS='OS',
verbose=verbose,
groups=mu.MC + [mu.LH])
kW_OS_R = hist.calc_kX(rf,
mu,
k_entry,
'WCR',
'Wlnu',
OS='OS',
verbose=verbose,
groups=mu.MC + [mu.RH])
kW_SS_L = hist.calc_kX(rf,
mu,
k_entry,
'WCR',
'Wlnu',
OS='SS',
verbose=verbose,
groups=mu.MC + [mu.LH])
kW_SS_R = hist.calc_kX(rf,
mu,
k_entry,
'WCR',
'Wlnu',
OS='SS',
verbose=verbose,
groups=mu.MC + [mu.RH])
rQCD_L = hist.calc_rQCD(rf,
mu,
k_entry,
'QCD',
kW_OS=kW_OS_L,
kW_SS=kW_SS_L,
verbose=verbose,
groups=mu.MC + [mu.LH])
rQCD_R = hist.calc_rQCD(rf,
mu,
k_entry,
'QCD',
kW_OS=kW_OS_R,
kW_SS=kW_SS_R,
verbose=verbose,
groups=mu.MC + [mu.RH])
rb = entry.rebin
# Canvas
if entry.blind: ratio = False
ratio = False
cname = '%s_%s_%s' % (mu.name, entry.name, region)
pname = '%s_%s' % (mu.name, region.rstrip('_OS'))
if ratio:
c = ROOT.TCanvas(cname, cname, 1500, 1000)
#Split for ratio plot
c.Divide(1, 2)
c.cd(1).SetPad(0.0, 0.2, 1.0, 1.0)
c.cd(2).SetPad(0.0, 0.0, 1.0, 0.2)
c.cd(1)
else:
c = ROOT.TCanvas(cname, cname, 1200, 800)
# Data
dregion = region
data = rf.Get('h_%s_%s_%s' % (entry.name, mu.data.name, dregion)).Clone()
data.SetMarkerStyle(20)
data.SetMarkerSize(2)
data.SetLabelSize(0.04, "y")
data.Rebin(rb)
if entry.xmax:
data.SetAxisRange(entry.xmin or 0, entry.xmax)
# stat. unc. on stack
stacksum = data.Clone("tmp")
stacksum.Reset()
# Legend
x0 = 0.72
y0 = 0.5
step = 0.05
nl = 4 + len(mu.MC) - 1 * entry.blind
l = ROOT.TLegend(x0, y0, x0 + .17, y0 + nl * step)
if entry.leg:
leg = entry.leg
l = ROOT.TLegend(leg[0], leg[1], leg[2], leg[3])
l.SetTextSize(0.035)
l.SetBorderSize(0)
l.SetFillColor(0)
if not entry.blind:
l.AddEntry(data, 'Data 2012',
"P") # (%.0f)' % data.Integral(0,data.GetNbinsX()+1))
# Stack
st = ROOT.THStack(cname, "%s; %s; " % (cname, entry.xtitle))
# QCD ESTIMATE
#if region == 'SR_SS': rQCD = ErrorFloat(1.,0.)
qcd = hist.get_QCD(rf, mu, entry, 'SR_SS', kW=kW_SS, rqcd=rQCD)
qcd.SetLineWidth(0)
qcd.SetLineColor(3)
qcd.SetFillColor(3)
qcd.SetMarkerStyle(0)
qcd.SetMarkerColor(3)
qcd.Rebin(rb)
# left and right
lefthand = hist.get_QCD(rf,
mu,
entry,
'SR_SS',
kW=kW_SS_L,
rqcd=rQCD_L,
groups=mu.MC + [mu.LH])
righthand = hist.get_QCD(rf,
mu,
entry,
'SR_SS',
kW=kW_SS_R,
rqcd=rQCD_R,
groups=mu.MC + [mu.RH])
lefthand.Rebin(rb)
righthand.Rebin(rb)
if not 'SR' in region:
qcd.Reset()
lefthand.Reset()
righthand.Reset()
if entry.xmax:
qcd.SetAxisRange(entry.xmin or 0, entry.xmax)
lefthand.SetAxisRange(entry.xmin or 0, entry.xmax)
righthand.SetAxisRange(entry.xmin or 0, entry.xmax)
st.Add(qcd)
stacksum.Add(qcd)
if verbose:
total_est = ErrorFloat(*hist.IntegralError(qcd))
print 'Data: %.0f +/- %.0f' % (hist.IntegralError(data)[0],
hist.IntegralError(data)[1])
print 'NQCD: %.0f +/- %.0f' % (hist.IntegralError(qcd)[0],
hist.IntegralError(qcd)[1])
mc_leg = []
n_total = ErrorFloat(
*hist.IntegralError(hist.get_OS(rf, entry, mu.signal, region)))
groups = mu.MC + [mu.signal]
for group in groups:
entry.add_group(group)
kOS = ErrorFloat(1.0, 0.0)
kSS = ErrorFloat(1.0, 0.0)
if group.name == 'Wlnu':
kOS = kW_OS
kSS = kW_SS
if 'SS' not in region:
h = hist.get_OS(rf, entry, group, region, kOS=kOS)
else:
h = hist.get_SS(rf, entry, group, region, kSS=kSS)
h.Rebin(rb)
if entry.xmax:
h.SetAxisRange(entry.xmin or 0, entry.xmax)
if group.name != mu.signal.name:
lefthand.Add(h)
righthand.Add(h)
h.SetLineColor(entry[group.name]['fill'])
h.SetLineWidth(0)
h.SetMarkerStyle(0)
h.SetMarkerColor(entry[group.name]['fill'])
h.SetFillColor(entry[group.name]['fill'])
h.SetLabelSize(0.04, "y")
st.Add(h)
stacksum.Add(h)
mc_leg.append((h, group.legend, hist.IntegralError(h)[0],
hist.IntegralError(h)[1]))
if verbose:
print '%s: %.0f +/- %.0f' % (group.name, hist.IntegralError(h)[0],
hist.IntegralError(h)[1])
total_est += ErrorFloat(*hist.IntegralError(h))
if syst:
print '%s: %.0f +/- %.0f' % ('up', hist.IntegralError(h_up)[0],
hist.IntegralError(h_up)[1])
print '%s: %.0f +/- %.0f' % ('down',
hist.IntegralError(h_down)[0],
hist.IntegralError(h_down)[1])
if verbose:
print 'Total Estimated: %.0f +/- %.0f' % (total_est.val, total_est.err)
## Add left and right
hLeft = hist.get_OS(rf, entry, mu.LH, region)
hRight = hist.get_OS(rf, entry, mu.RH, region)
for h in [hLeft, hRight]:
h.Rebin(rb)
h.SetMarkerStyle(0)
h.SetLineWidth(1)
if entry.xmax:
h.SetAxisRange(entry.xmin or 0, entry.xmax)
lefthand.Add(hLeft)
righthand.Add(hRight)
lefthand.SetLineColor(mu.LH.fill)
righthand.SetLineColor(mu.RH.fill)
lefthand.SetLineStyle(2)
righthand.SetLineStyle(2)
for li in reversed(mc_leg):
l.AddEntry(li[0], '%s' % (li[1]))
#l.AddEntry(qcd,'QCD: %.0f +/- %.0f' % (hist.IntegralError(qcd)[0],hist.IntegralError(qcd)[1]))
if 'SR' in region:
l.AddEntry(
qcd, 'Multijet'
) #: %.0f +/- %.0f' % (hist.IntegralError(qcd)[0],hist.IntegralError(qcd)[1]))
l.AddEntry(lefthand, 'Left-Handed', "L")
l.AddEntry(righthand, 'Right-Handed', "L")
data.SetXTitle(entry.xtitle)
data.GetXaxis().SetTitleOffset(1.25)
stacksum.SetFillStyle(3354)
stacksum.SetLineColor(1)
stacksum.SetFillColor(12)
stacksum.SetMarkerStyle(1)
maxi = max(data.GetMaximum(), st.GetMaximum())
mini = 0.
data.SetMinimum(1.2 * mini)
data.SetMaximum(1.4 * maxi)
bw = data.GetXaxis().GetBinWidth(1)
data.GetYaxis().SetTitle('Events / %s %s' % (bw, entry.units))
if not entry.blind:
data.Draw("PE")
st.Draw("HIST,SAME")
stacksum.Draw("E2,SAME")
data.Draw("SAME, PE")
else:
data.Reset()
data.Draw()
st.SetTitle('')
st.SetMinimum(1.2 * st.GetMinimum())
st.SetMaximum(1.5 * st.GetMaximum())
st.Draw("HIST,SAME")
stacksum.Draw("E2,SAME")
lefthand.Draw("HIST,SAME")
righthand.Draw("HIST,SAME")
data.Draw("SAME,PE")
ROOT.gPad.RedrawAxis()
l.Draw()
atlas = ROOT.ATLASLabel(0.3, 0.87, " Work in Progress")
#td = ROOT.TPaveText(0.3,0.75,0.7,0.85,"NDC")
if 'SR' in region:
td = ROOT.TPaveText(0.52, 0.68, 0.65, 0.85, "NDC")
else:
td = ROOT.TPaveText(0.19, 0.68, 0.32, 0.85, "NDC")
td.SetTextAlign(13)
td.SetBorderSize(0)
td.SetFillColor(0)
td.SetTextSize(0.04)
#td.AddText('#sqrt{s} = 8 TeV #int Ldt = 20.3 fb^{-1}')
#td.AddText('#sqrt{s} = 8 TeV')
#td.AddText('#int Ldt = 20.3 fb^{-1}')
td.Draw()
# channel
tm = ROOT.TPaveText(0.19, 0.85, 0.22, 0.92, "NDC")
tm.SetBorderSize(0)
tm.SetFillColor(0)
tm.SetTextSize(0.05)
if mu.name == 'mu':
tm.AddText('#mu#tau_{had}')
elif mu.name == 'el':
tm.AddText('e#tau_{had}')
tm.Draw()
#atlas.Draw()
if ratio:
c.cd(2)
ROOT.gPad.SetTopMargin(0)
dataratio = data.Clone('ratio')
if entry.xmax:
dataratio.SetAxisRange(0, entry.xmax)
dataratio.GetYaxis().SetTitle('Data / MC')
dataratio.GetYaxis().SetTitleOffset(0.25)
dataratio.GetYaxis().SetTitleSize(0.16)
dataratio.SetLabelSize(.1, "y")
dataratio.Divide(stacksum)
dataratio.SetMaximum(1.5)
dataratio.SetMinimum(0.5)
err = stacksum.Clone('err')
err.Divide(err)
err.SetFillStyle(3354)
err.SetLineColor(1)
err.SetFillColor(12)
err.SetMarkerStyle(1)
xmin = dataratio.GetXaxis().GetXmin()
xmax = entry.xmax or dataratio.GetXaxis().GetXmax()
cl = ROOT.TLine(xmin, 1, xmax, 1)
cl.SetLineStyle(3)
dataratio.GetXaxis().SetLabelSize(0.04)
dataratio.Draw('PE')
cl.Draw("SAME")
err.Draw("SAME,E2")
c.Update()
c.Update()
c.Print('../plots/ttbar/%s.eps' % (cname))
def charged_asymmetry(mu):
rf = ROOT.TFile('~/panalysis/output/prodr/%s_ttbar/%s_regions.root' %
(mu.name, mu.name))
entry = upsilon_20
k_entry = upsilon_CR
verbose = False
region = 'TTBAR_OS'
# scale factors
k_entry = upsilon_CR
groups = mu.MC + [mu.signal]
kW_OS = hist.calc_kX(rf,
mu,
k_entry,
'WCR',
'Wlnu',
OS='OS',
verbose=verbose,
groups=groups)
kW_SS = hist.calc_kX(rf,
mu,
k_entry,
'WCR',
'Wlnu',
OS='SS',
verbose=verbose,
groups=groups)
rQCD = hist.calc_rQCD(rf,
mu,
k_entry,
'QCD',
kW_OS=kW_OS,
kW_SS=kW_SS,
verbose=verbose,
groups=groups)
# Canvas
if entry.blind: ratio = False
ratio = False
cname = '%s_%s_%s' % (mu.name, entry.name, region)
#pname = '%s_%s_%s' % (mu.name,region.rstrip('_OS'), hand)
if ratio:
c = ROOT.TCanvas(cname, cname, 1500, 1000)
#Split for ratio plot
c.Divide(1, 2)
c.cd(1).SetPad(0.0, 0.2, 1.0, 1.0)
c.cd(2).SetPad(0.0, 0.0, 1.0, 0.2)
c.cd(1)
else:
c = ROOT.TCanvas(cname, cname, 1200, 800)
rb = 1
# data
if 'SR_OS' in region: dregion = 'SR_OS'
if 'SR_SS' in region: dregion = 'SR_SS'
data = rf.Get('h_%s_%s_%s' % (entry.name, mu.data.name, dregion)).Clone()
data.SetMarkerStyle(20)
data.SetMarkerSize(2)
data.SetLabelSize(0.04, "y")
data.Rebin(rb)
# Blind data
data.Reset()
if entry.xmax:
data.SetAxisRange(entry.xmin or 0, entry.xmax)
# stat. unc. on stack
stacksum = data.Clone("tmp")
stacksum.Reset()
# Legend
x0 = 0.73
y0 = 0.55
step = 0.045
nl = 4 + len(mu.MC) - 1 * entry.blind
l = ROOT.TLegend(x0, y0, x0 + .16, y0 + nl * step)
l.SetTextSize(0.0345)
l.SetBorderSize(0)
l.SetFillColor(0)
# Data
# Stack
st = ROOT.THStack(cname, "%s; %s; " % (cname, entry.xtitle))
# QCD ESTIMATE
#if region == 'SR_SS': rQCD = ErrorFloat(1.,0.)
qcd = hist.get_QCDW(rf,
mu,
entry,
'SR_SS',
rqcd=rQCD,
verbose=False,
groups=groups)
qcd.SetLineWidth(0)
qcd.SetLineColor(3)
qcd.SetFillColor(3)
qcd.SetMarkerStyle(0)
qcd.SetMarkerColor(3)
qcd.Rebin(rb)
if entry.xmax:
qcd.SetAxisRange(entry.xmin or 0, entry.xmax)
st.Add(qcd)
stacksum.Add(qcd)
if verbose:
total_est = ErrorFloat(*hist.IntegralError(qcd))
print 'Data: %.0f +/- %.0f' % (hist.IntegralError(data)[0],
hist.IntegralError(data)[1])
print 'NQCD: %.0f +/- %.0f' % (hist.IntegralError(qcd)[0],
hist.IntegralError(qcd)[1])
mc_leg = []
n_total = ErrorFloat(
*hist.IntegralError(hist.get_OS(rf, entry, mu.signal, region)))
for group in groups:
entry.add_group(group)
if group.name == 'Wlnu':
h = hist.get_dataW(rf,
mu,
entry,
'WCR_OS',
verbose=False,
groups=groups)
else:
h = hist.get_OS(rf, entry, group, region)
h.Rebin(rb)
if entry.xmax:
h.SetAxisRange(entry.xmin or 0, entry.xmax)
h.SetLineColor(entry[group.name]['fill'])
h.SetLineWidth(0)
h.SetMarkerStyle(0)
h.SetMarkerColor(entry[group.name]['fill'])
h.SetFillColor(entry[group.name]['fill'])
h.SetLabelSize(0.04, "y")
st.Add(h)
stacksum.Add(h)
mc_leg.append((h, group.legend, hist.IntegralError(h)[0],
hist.IntegralError(h)[1]))
if verbose:
print '%s: %.0f +/- %.0f' % (group.name, hist.IntegralError(h)[0],
hist.IntegralError(h)[1])
total_est += ErrorFloat(*hist.IntegralError(h))
if verbose:
print 'Total Estimated: %.0f +/- %.0f' % (total_est.val, total_est.err)
for li in reversed(mc_leg):
l.AddEntry(li[0], '%s' % (li[1]))
l.AddEntry(
qcd, 'Multijet'
) #: %.0f +/- %.0f' % (hist.IntegralError(qcd)[0],hist.IntegralError(qcd)[1]))
data.SetXTitle(entry.xtitle)
data.GetXaxis().SetTitleOffset(1.25)
stacksum.SetFillStyle(3354)
stacksum.SetLineColor(1)
stacksum.SetFillColor(12)
stacksum.SetMarkerStyle(1)
maxi = max(data.GetMaximum(), st.GetMaximum())
maxi = 6250
mini = 0.
data.SetMinimum(1.2 * mini)
data.SetMaximum(maxi)
bw = data.GetXaxis().GetBinWidth(1)
data.GetYaxis().SetTitle('Events / %s %s' % (bw, entry.units))
if not entry.blind:
data.Draw("PE")
st.Draw("HIST,SAME")
stacksum.Draw("E2,SAME")
data.Draw("SAME, PE")
else:
data.Reset()
data.Draw()
st.SetTitle('')
st.SetMinimum(1.2 * st.GetMinimum())
st.SetMaximum(1.5 * st.GetMaximum())
st.Draw("HIST,SAME")
stacksum.Draw("E2,SAME")
ROOT.gPad.RedrawAxis()
l.Draw()
atlas = ROOT.ATLASLabel(0.32, 0.86, " Work in Progress")
td = ROOT.TPaveText(0.54, 0.68, 0.67, 0.85, "NDC")
td.SetTextAlign(13)
td.SetBorderSize(0)
td.SetFillColor(0)
td.SetTextSize(0.04)
td.AddText('#sqrt{s} = 8 TeV')
td.AddText('#int Ldt = 20.3 fb^{-1}')
td.Draw()
# channel
tm = ROOT.TPaveText(0.19, 0.83, 0.22, 0.90, "NDC")
tm.SetBorderSize(0)
tm.SetFillColor(0)
tm.SetTextSize(0.05)
if mu.name == 'mu':
tm.AddText('#mu#tau_{had}')
elif mu.name == 'el':
tm.AddText('e#tau_{had}')
tm.Draw()
c.Update()
c.Print('../plots/ttbar/%s.eps' % (cname))