def main(options,args) :
print 'Loading c++...'
anaplot.LoadRootCore()
ROOT.gROOT.SetBatch(False)
plotfunc.SetupStyle()
ROOT.gStyle.SetPaintTextFormat("4.3f ")
#
# Draw plots
#
print 'Drawing the plots'
cans = []
for v in options.variables.split(',') :
if not v : continue
xlabel = options.histformat[v][3]
n,low,high = options.histformat[v][:3]
bkg_hists = []
sig_hists = []
data_hist = None
rebin = []
if hasattr(options.usermodule,'rebin') and v in options.usermodule.rebin.keys() :
rebin = options.usermodule.rebin[v]
if options.file :
bkg_processes = options.processes.replace('data','').replace(',,',',')
bkg_hists = anaplot.GetPassEventBkgHistos(v,options.key,bkg_processes,options.file,normalize=options.normalize,rebin=rebin,n=n,low=low,high=high)
anaplot.PrepareBkgHistosForStack(bkg_hists)
if 'data' in options.processes :
data_hist = anaplot.GetPassEventBkgHistos(v,options.key,'data',options.file,normalize=options.normalize,rebin=rebin,n=n,low=low,high=high)[0]
#data_hist = anaplot.GetPassEventBkgHistos(v,'FFTool_z_mccl_ltt_allNum','zjetdd',options.file,normalize=options.normalize,rebin=rebin,n=n,low=low,high=high)[0]
if options.susy :
sig_hists = anaplot.GetPassEventSigHistos(v,options.key,options.susy,normalize=options.normalize,rebin=rebin)
cans.append(anaplot.DrawHistos('%s_%s'%(options.key,v),v,xlabel,bkg_hists,sig_hists,data_hist=data_hist,dostack=options.stack,log=options.log,ratio=options.ratio,fb=options.fb))
taxisfunc.SetXaxisRanges(cans[-1],low,high)
#
# Cutflow
#
f = ROOT.TFile(options.file)
if f.IsZombie() :
print 'exiting'
return
PrintCutflow(options.key
,f.Get('PassEvent_%s/PassEvent_%s_PassW'%(options.key,options.key))
,samp_list=options.processes.split(',')+['all']
,scientific=True)
f.Close()
raw_input('Pausing. Press enter to exit.')
if options.save :
for can in cans :
can.Print(can.GetName()+'.pdf')
can.Print(can.GetName()+'.eps')
print 'done.'
return
def main(options, args):
plotfunc.SetupStyle()
for i in options.histformat.keys():
print '\'%s\':' % (i), options.histformat[i]
anaplot.LoadRootCore()
files_b, trees_b, keys_b, cf_b = anaplot.GetTreesFromFiles(options.bkgs)
files_s, trees_s, keys_s, cf_s = anaplot.GetTreesFromFiles(options.susy)
file_d, tree_d, key_d, cf_d = anaplot.GetTreesFromFiles(options.data)
options.fb, lumi_scale_factor = helpers.GetTTreeLumiScaleFactor(
files_b + files_s, options.fb)
dweight = ''
weight = 'TotalWeightNoSF*lepSFRecoIdIso[lep0_index]*lepSFRecoIdIso[lep1_index]*lepSFRecoIdIso[lep2_index]*EvtTrigSF*AntiIDSF_lep3*PassEvent_SMWZsig'
#weight = 'TotalWeightNoPupNoSF'
if ''.join(options.cuts):
weight = weight + '*(%s)' % (' && '.join(options.cuts))
dweight = '(' + ' && '.join(options.cuts) + ')'
if hasattr(options.usermodule, 'weight'):
weight += '*(%s)' % (options.usermodule.weight)
if hasattr(options.usermodule, 'dataweight'):
dweight += '*(%s)' % (options.usermodule.dataweight)
cans = []
# get the histograms from the files
for vi, v1 in enumerate(options.variables.split(',')):
n1, low1, high1 = options.histformat[v1][:3]
xlabel1 = options.histformat[v1][3]
rebin1 = []
if hasattr(options.usermodule,
'rebin') and v1 in options.usermodule.rebin.keys():
rebin1 = options.usermodule.rebin[v1]
for vj, v2 in enumerate(options.variables.split(',')):
if v2 == v1: continue
if vj > vi: continue
n2, low2, high2 = options.histformat[v2][:3]
xlabel2 = options.histformat[v2][3]
rebin2 = []
if hasattr(options.usermodule,
'rebin') and v2 in options.usermodule.rebin.keys():
rebin2 = options.usermodule.rebin[v2]
bkg_hists = []
sig_hists = []
data_hist = None
if options.bkgs:
bkg_hists = anaplot.Get2dVariableHistsFromTrees(
trees_b,
keys_b,
v1,
v2,
weight,
n1,
low1,
high1,
n2,
low2,
high2,
normalize=options.normalize,
rebin1=rebin1,
rebin2=rebin2,
scale=lumi_scale_factor)
anaplot.PrepareBkgHistosForStack(bkg_hists)
for i, h in enumerate(bkg_hists):
canname = '%s_%s_%s' % (v1, v2, keys_b[i])
cans.append(ROOT.TCanvas(canname, canname, 500, 500))
h.SetMinimum(-0.00001)
plotfunc.AddHistogram(cans[-1], h, drawopt='colz')
plotfunc.FormatCanvasAxes(cans[-1])
plotfunc.SetAxisLabels(cans[-1], xlabel1, xlabel2)
if options.susy:
sig_hists = anaplot.Get2dVariableHistsFromTrees(
trees_s,
keys_s,
v1,
v2,
weight,
n1,
low1,
high1,
n2,
low2,
high2,
normalize=options.normalize,
rebin1=rebin1,
rebin2=rebin2,
scale=lumi_scale_factor)
for i, h in enumerate(sig_hists):
canname = '%s_%s_%s' % (v1, v2, keys_s[i])
cans.append(ROOT.TCanvas(canname, canname, 500, 500))
h.SetMinimum(-0.00001)
plotfunc.AddHistogram(cans[-1], h, drawopt='colz')
plotfunc.FormatCanvasAxes(cans[-1])
plotfunc.SetAxisLabels(cans[-1], xlabel1, xlabel2)
if options.data:
data_hist = anaplot.Get2dVariableHistsFromTrees(
tree_d,
key_d,
v1,
v2,
dweight,
n1,
low1,
high1,
n2,
low2,
high2,
normalize=options.normalize,
rebin1=rebin1,
rebin2=rebin2,
scale=lumi_scale_factor)[0]
data_hist.SetLineWidth(2)
data_hist.SetLineColor(1)
data_hist.SetMarkerColor(1)
canname = '%s_%s_%s' % (v1, v2, 'data')
cans.append(ROOT.TCanvas(canname, canname, 500, 500))
h.SetMinimum(-0.00001)
plotfunc.AddHistogram(cans[-1], h, drawopt='colz')
plotfunc.FormatCanvasAxes(cans[-1])
plotfunc.SetAxisLabels(cans[-1], xlabel1, xlabel2)
cans.append(
anaplot.DrawHistos(v,
v,
xlabel,
bkg_hists,
sig_hists,
data_hist,
dostack=options.stack,
log=options.log,
ratio=options.ratio,
fb=options.fb))
if not options.batch:
raw_input('Press enter to exit')
if options.save:
for can in cans:
can.Print(can.GetName() + '.pdf')
print 'done.'
return
def main(options, args):
print 'Loading c++...'
anaplot.LoadRootCore()
ROOT.gROOT.SetBatch(False)
plotfunc.SetupStyle()
options.keys = []
if not options.e:
options.keys += [
options.key + '_ttt_MuNum', options.key + '_ltt_MuDen'
]
if not options.mu:
options.keys += [
options.key + '_ttt_EleNum', options.key + '_ltt_EleDen'
]
print options.keys
#
# Draw plots
#
print 'Drawing the plots'
cans = []
for v in options.variables.split(','):
if not v: continue
n, low, high = options.histformat[v][:3]
lep_pt_dijet_num = None
lep_pt_dijet_den = None
for k in options.keys:
bkg_hists = []
sig_hists = []
data_hist = None
rebin = []
if hasattr(options.usermodule,
'rebin') and v in options.usermodule.rebin.keys():
rebin = options.usermodule.rebin[v]
if ('lepPt' in v) and ('Mu' in k):
rebin = [0, 9, 15, 20, 30, 100]
if options.file:
bkg_processes = options.processes.replace('data', '').replace(
',,', ',')
bkg_hists = anaplot.GetPassEventBkgHistos(
v,
k,
bkg_processes,
options.file,
normalize=options.normalize,
rebin=rebin,
n=n,
low=low,
high=high)
anaplot.PrepareBkgHistosForStack(bkg_hists)
if 'data' in options.processes:
data_hist = anaplot.GetPassEventBkgHistos(
v,
k,
'data',
options.file,
normalize=options.normalize,
rebin=rebin,
n=n,
low=low,
high=high)[0]
xlabel = ROOT.PSL.GetXaxisLabel(v.split('[')[0])
cans.append(
anaplot.DrawHistos('%s_%s' % (k, v),
v,
xlabel,
bkg_hists,
sig_hists,
data_hist=data_hist,
dostack=options.stack,
log=options.log,
ratio=options.ratio,
fb=options.fb))
taxisfunc.SetXaxisRanges(cans[-1], low, high)
#
# Specifically get the fake factor in pt:
#
cans_divide = []
v = 'lepPt[lepW_index]'
rebin_mu = [0, 9, 15, 20, 30, 100]
rebin_e = [0, 9, 15, 20, 30, 50, 100]
hists_MuNum = dict()
hists_MuDen = dict()
hists_EleNum = dict()
hists_EleDen = dict()
mu_options = options.file, options.normalize, rebin_mu
e_options = options.file, options.normalize, rebin_e
for p in options.processes.split(','):
hists_MuNum[p] = anaplot.GetPassEventBkgHistos(
v, options.key + '_ttt_MuNum', p, *mu_options)[0]
hists_MuDen[p] = anaplot.GetPassEventBkgHistos(
v, options.key + '_ltt_MuDen', p, *mu_options)[0]
hists_EleNum[p] = anaplot.GetPassEventBkgHistos(
v, options.key + '_ttt_EleNum', p, *e_options)[0]
hists_EleDen[p] = anaplot.GetPassEventBkgHistos(
v, options.key + '_ltt_EleDen', p, *e_options)[0]
z_w = ''
tmp = ROOT.TFile(options.file)
syst_check = 'PassEvent_FFTool_forsyst_%s_ttt_MuNum/PassEvent_FFTool_forsyst_%s_ttt_MuNum_zjet_lepPt_antilep0_index' % (
'wid', 'wid')
print syst_check
if tmp.Get(syst_check):
z_w = 'wid'
elif tmp.Get(syst_check.replace('wid', 'zid')):
z_w = 'zid'
if z_w and options.syst:
do_z = (z_w == 'zid')
# try to get SR FF
hists_MuNum['zjet_sr'] = anaplot.GetPassEventBkgHistos(
'lepPt_antilep0_index', 'FFTool_forsyst_%s_ttt_MuNum' % (z_w),
'zjet', *mu_options)[0]
if True:
hists_MuDen['zjet_sr'] = anaplot.GetPassEventBkgHistos(
'lepPt_lepW_index', 'FFTool_forsyst_ltt_MuDen', 'zjet',
*mu_options)[0]
if do_z:
hists_MuDen['zjet_sr'].Add(
anaplot.GetPassEventBkgHistos('lepPt_lepleadZ_index',
'FFTool_forsyst_tlt_MuDen',
'zjet', *mu_options)[0])
if do_z:
hists_MuDen['zjet_sr'].Add(
anaplot.GetPassEventBkgHistos('lepPt_lepsubleadZ_index',
'FFTool_forsyst_ttl_MuDen',
'zjet', *mu_options)[0])
hists_MuNum['zjet_sr'].Add(
anaplot.GetPassEventBkgHistos(
'lepPt_antilep0_index', 'FFTool_forsyst_%s_ttt_MuNum' % (z_w),
'zgam', *mu_options)[0])
if True:
hists_MuDen['zjet_sr'].Add(
anaplot.GetPassEventBkgHistos('lepPt_lepW_index',
'FFTool_forsyst_ltt_MuDen',
'zgam', *mu_options)[0])
if do_z:
hists_MuDen['zjet_sr'].Add(
anaplot.GetPassEventBkgHistos('lepPt_lepleadZ_index',
'FFTool_forsyst_tlt_MuDen',
'zgam', *mu_options)[0])
if do_z:
hists_MuDen['zjet_sr'].Add(
anaplot.GetPassEventBkgHistos('lepPt_lepsubleadZ_index',
'FFTool_forsyst_ttl_MuDen',
'zgam', *mu_options)[0])
hists_EleNum['zjet_sr'] = anaplot.GetPassEventBkgHistos(
'lepPt_antilep0_index', 'FFTool_forsyst_%s_ttt_EleNum' % (z_w),
'zjet', *e_options)[0]
if True:
hists_EleDen['zjet_sr'] = anaplot.GetPassEventBkgHistos(
'lepPt_lepW_index', 'FFTool_forsyst_ltt_EleDen', 'zjet',
*e_options)[0]
if do_z:
hists_EleDen['zjet_sr'].Add(
anaplot.GetPassEventBkgHistos('lepPt_lepleadZ_index',
'FFTool_forsyst_tlt_EleDen',
'zjet', *e_options)[0])
if do_z:
hists_EleDen['zjet_sr'].Add(
anaplot.GetPassEventBkgHistos('lepPt_lepsubleadZ_index',
'FFTool_forsyst_ttl_EleDen',
'zjet', *e_options)[0])
hists_EleNum['zjet_sr'].Add(
anaplot.GetPassEventBkgHistos(
'lepPt_antilep0_index', 'FFTool_forsyst_%s_ttt_EleNum' % (z_w),
'zgam', *e_options)[0])
if True:
hists_EleDen['zjet_sr'].Add(
anaplot.GetPassEventBkgHistos('lepPt_lepW_index',
'FFTool_forsyst_ltt_EleDen',
'zgam', *e_options)[0])
if do_z:
hists_EleDen['zjet_sr'].Add(
anaplot.GetPassEventBkgHistos('lepPt_lepleadZ_index',
'FFTool_forsyst_tlt_EleDen',
'zgam', *e_options)[0])
if do_z:
hists_EleDen['zjet_sr'].Add(
anaplot.GetPassEventBkgHistos('lepPt_lepsubleadZ_index',
'FFTool_forsyst_ttl_EleDen',
'zgam', *e_options)[0])
# now for ttbar
hists_MuNum['ttbar_sr'] = anaplot.GetPassEventBkgHistos(
'lepPt_antilep0_index', 'FFTool_forsyst_%s_ttt_MuNum' % (z_w),
'ttbar', *mu_options)[0]
if True:
hists_MuDen['ttbar_sr'] = anaplot.GetPassEventBkgHistos(
'lepPt_lepW_index', 'FFTool_forsyst_ltt_MuDen', 'ttbar',
*mu_options)[0]
if do_z:
hists_MuDen['ttbar_sr'].Add(
anaplot.GetPassEventBkgHistos('lepPt_lepleadZ_index',
'FFTool_forsyst_tlt_MuDen',
'ttbar', *mu_options)[0])
if do_z:
hists_MuDen['ttbar_sr'].Add(
anaplot.GetPassEventBkgHistos('lepPt_lepsubleadZ_index',
'FFTool_forsyst_ttl_MuDen',
'ttbar', *mu_options)[0])
hists_EleNum['ttbar_sr'] = anaplot.GetPassEventBkgHistos(
'lepPt_antilep0_index', 'FFTool_forsyst_%s_ttt_EleNum' % (z_w),
'ttbar', *e_options)[0]
if True:
hists_EleDen['ttbar_sr'] = anaplot.GetPassEventBkgHistos(
'lepPt_lepW_index', 'FFTool_forsyst_ltt_EleDen', 'ttbar',
*e_options)[0]
if do_z:
hists_EleDen['ttbar_sr'].Add(
anaplot.GetPassEventBkgHistos('lepPt_lepleadZ_index',
'FFTool_forsyst_tlt_EleDen',
'ttbar', *e_options)[0])
if do_z:
hists_EleDen['ttbar_sr'].Add(
anaplot.GetPassEventBkgHistos('lepPt_lepsubleadZ_index',
'FFTool_forsyst_ttl_EleDen',
'ttbar', *e_options)[0])
hists_MuNum['zjet_sr'].SetName('zjet_sr')
hists_MuNum['zjet_sr'].SetTitle('zjet+z#gamma SR FF')
hists_EleNum['zjet_sr'].SetName('zjet_sr')
hists_EleNum['zjet_sr'].SetTitle('zjet+z#gamma SR FF')
if False:
hists_MuDen['zjet_sr'].Add(hists_MuDen['ttbar_sr'])
hists_EleDen['zjet_sr'].Add(hists_EleDen['ttbar_sr'])
hists_MuNum['zjet_sr'].Add(hists_MuNum['ttbar_sr'])
hists_EleNum['zjet_sr'].Add(hists_EleNum['ttbar_sr'])
hists_MuNum['zjet_sr'].SetTitle('zjet+z#gamma+ttbar SR FF')
hists_EleNum['zjet_sr'].SetTitle('zjet+z#gamma+ttbar SR FF')
hists_MuNum['zjet_sr'].Divide(hists_MuDen['zjet_sr'])
hists_EleNum['zjet_sr'].Divide(hists_EleDen['zjet_sr'])
hists_MuNum['ttbar_sr'].SetName('ttbar_sr')
hists_MuNum['ttbar_sr'].SetTitle('ttbar SR FF')
hists_EleNum['ttbar_sr'].SetName('ttbar_sr')
hists_EleNum['ttbar_sr'].SetTitle('ttbar SR FF')
hists_MuNum['ttbar_sr'].Divide(hists_MuDen['ttbar_sr'])
hists_EleNum['ttbar_sr'].Divide(hists_EleDen['ttbar_sr'])
print hists_MuNum.keys()
if (options.region == 'dijet') and 'dijet' in hists_EleNum.keys():
hists_MuNum['dijet'].SetLineColor(ROOT.kBlue + 1)
hists_MuNum['dijet'].SetMarkerColor(ROOT.kBlue + 1)
hists_EleNum['dijet'].SetLineColor(ROOT.kBlue + 1)
hists_EleNum['dijet'].SetMarkerColor(ROOT.kBlue + 1)
hists_MuNum['dijet'].Divide(hists_MuDen['dijet'])
hists_EleNum['dijet'].Divide(hists_EleDen['dijet'])
if (options.region == 'zjet') and 'zjet' in hists_EleNum.keys():
hists_MuNum['zjet'].SetTitle('zjet (no z#gamma) MC')
hists_EleNum['zjet'].SetTitle('zjet (no z#gamma) MC')
if 'zgam' in hists_EleNum.keys():
print '##############################################################################'
print '## Adding zgam to your estimate'
print '##############################################################################'
hists_MuNum['zjet'].Add(hists_MuNum['zgam'])
hists_EleNum['zjet'].Add(hists_EleNum['zgam'])
hists_MuNum['zjet'].SetTitle('zjet+z#gamma MC')
hists_EleNum['zjet'].SetTitle('zjet+z#gamma MC')
hists_MuNum['zjet'].SetLineColor(ROOT.kBlue + 1)
hists_MuNum['zjet'].SetMarkerColor(ROOT.kBlue + 1)
hists_EleNum['zjet'].SetLineColor(ROOT.kBlue + 1)
hists_EleNum['zjet'].SetMarkerColor(ROOT.kBlue + 1)
hists_MuNum['zjet'].Divide(hists_MuDen['zjet'])
hists_EleNum['zjet'].Divide(hists_EleDen['zjet'])
# cans.append(ROOT.TCanvas('%s_Mu_ff_dijet'%(v),'%s_Mu_ff'%(v),500,500))
# plotfunc.AddHistogram(cans[-1],dijet_hist_MuNum)
# plotfunc.FormatCanvasAxes(cans[-1])
# taxisfunc.SetYaxisRanges(cans[-1],0,0.5)
# cans.append(ROOT.TCanvas('%s_Ele_ff_dijet'%(v),'%s_Ele_ff'%(v),500,500))
# plotfunc.AddHistogram(cans[-1],dijet_hist_EleNum)
# plotfunc.FormatCanvasAxes(cans[-1])
# taxisfunc.SetYaxisRanges(cans[-1],0,0.5)
if 'data' in hists_EleNum.keys():
hists_EleNum['data'].SetTitle('With VV subtraction')
hists_EleDen['data'].SetTitle('With VV subtraction')
hists_MuNum['data'].SetTitle('With VV subtraction')
hists_MuDen['data'].SetTitle('With VV subtraction')
if (options.region == 'dijet'):
hists_EleNum['data_bws'] = hists_EleNum['data'].Clone()
hists_EleNum['data_bws'].SetName(
hists_EleNum['data_bws'].GetName() + '_bws')
hists_EleDen['data_bws'] = hists_EleDen['data'].Clone()
hists_EleDen['data_bws'].SetName(
hists_EleDen['data_bws'].GetName() + '_bws')
hists_MuNum['data_bws'] = hists_MuNum['data'].Clone()
hists_MuNum['data_bws'].SetName(hists_MuNum['data_bws'].GetName() +
'_bws')
hists_MuDen['data_bws'] = hists_MuDen['data'].Clone()
hists_MuDen['data_bws'].SetName(hists_MuDen['data_bws'].GetName() +
'_bws')
hists_EleNum['data_bws'].SetTitle('No EW subtraction')
hists_EleDen['data_bws'].SetTitle('No EW subtraction')
hists_MuNum['data_bws'].SetTitle('No EW subtraction')
hists_MuDen['data_bws'].SetTitle('No EW subtraction')
hists_EleNum['data_bzs'] = hists_EleNum['data_bws'].Clone()
hists_EleNum['data_bzs'].SetName(
hists_EleNum['data_bzs'].GetName() + '_bzs')
hists_EleDen['data_bzs'] = hists_EleDen['data_bws'].Clone()
hists_EleDen['data_bzs'].SetName(
hists_EleDen['data_bzs'].GetName() + '_bzs')
hists_MuNum['data_bzs'] = hists_MuNum['data_bws'].Clone()
hists_MuNum['data_bzs'].SetName(hists_MuNum['data_bzs'].GetName() +
'_bzs')
hists_MuDen['data_bzs'] = hists_MuDen['data_bws'].Clone()
hists_MuDen['data_bzs'].SetName(hists_MuDen['data_bzs'].GetName() +
'_bzs')
hists_EleNum['data_bzs'].SetTitle('With W subtraction')
hists_EleDen['data_bzs'].SetTitle('With W subtraction')
hists_MuNum['data_bzs'].SetTitle('With W subtraction')
hists_MuDen['data_bzs'].SetTitle('With W subtraction')
for i in ['wje', 'wjm', 'wjt', 'zjee', 'zjmm', 'zjtt']:
if i in hists_EleNum.keys():
print 'Subtracting', i
hists_EleNum['data'].Add(hists_EleNum[i], -1)
hists_EleDen['data'].Add(hists_EleDen[i], -1)
hists_MuNum['data'].Add(hists_MuNum[i], -1)
hists_MuDen['data'].Add(hists_MuDen[i], -1)
if i not in ['zjee', 'zjmm', 'zjtt']:
hists_EleNum['data_bzs'].Add(hists_EleNum[i], -1)
hists_EleDen['data_bzs'].Add(hists_EleDen[i], -1)
hists_MuNum['data_bzs'].Add(hists_MuNum[i], -1)
hists_MuDen['data_bzs'].Add(hists_MuDen[i], -1)
hists_MuNum['data_bws'].Divide(hists_MuDen['data_bws'])
hists_EleNum['data_bws'].Divide(hists_EleDen['data_bws'])
hists_MuNum['data_bzs'].Divide(hists_MuDen['data_bzs'])
hists_EleNum['data_bzs'].Divide(hists_EleDen['data_bzs'])
if (options.region == 'zjet'):
hists_EleNum['data_bvvs'] = hists_EleNum['data'].Clone()
hists_EleNum['data_bvvs'].SetName(
hists_EleNum['data_bvvs'].GetName() + '_bvvs')
hists_EleDen['data_bvvs'] = hists_EleDen['data'].Clone()
hists_EleDen['data_bvvs'].SetName(
hists_EleDen['data_bvvs'].GetName() + '_bvvs')
hists_MuNum['data_bvvs'] = hists_MuNum['data'].Clone()
hists_MuNum['data_bvvs'].SetName(
hists_MuNum['data_bvvs'].GetName() + '_bvvs')
hists_MuDen['data_bvvs'] = hists_MuDen['data'].Clone()
hists_MuDen['data_bvvs'].SetName(
hists_MuDen['data_bvvs'].GetName() + '_bvvs')
hists_EleNum['data_bvvs'].SetTitle('No VV subtraction')
hists_EleDen['data_bvvs'].SetTitle('No VV subtraction')
hists_MuNum['data_bvvs'].SetTitle('No VV subtraction')
hists_MuDen['data_bvvs'].SetTitle('No VV subtraction')
# 15% systematic on vv subtraction
hists_EleNum['data_vv15sys'] = hists_EleNum['data'].Clone()
hists_EleNum['data_vv15sys'].SetName(
hists_EleNum['data_vv15sys'].GetName() + '_vv15sys')
hists_EleDen['data_vv15sys'] = hists_EleDen['data'].Clone()
hists_EleDen['data_vv15sys'].SetName(
hists_EleDen['data_vv15sys'].GetName() + '_vv15sys')
hists_MuNum['data_vv15sys'] = hists_MuNum['data'].Clone()
hists_MuNum['data_vv15sys'].SetName(
hists_MuNum['data_vv15sys'].GetName() + '_vv15sys')
hists_MuDen['data_vv15sys'] = hists_MuDen['data'].Clone()
hists_MuDen['data_vv15sys'].SetName(
hists_MuDen['data_vv15sys'].GetName() + '_vv15sys')
hists_EleNum['data_vv15sys'].SetTitle(
'15% systematic on subtraction')
hists_EleDen['data_vv15sys'].SetTitle(
'15% systematic on subtraction')
hists_MuNum['data_vv15sys'].SetTitle(
'15% systematic on subtraction')
hists_MuDen['data_vv15sys'].SetTitle(
'15% systematic on subtraction')
for i in ['wz', 'zz']:
if i in hists_EleNum.keys():
print 'Subtracting', i
hists_EleNum['data'].Add(hists_EleNum[i], -1)
hists_EleDen['data'].Add(hists_EleDen[i], -1)
hists_MuNum['data'].Add(hists_MuNum[i], -1)
hists_MuDen['data'].Add(hists_MuDen[i], -1)
hists_EleNum['data_vv15sys'].Add(hists_EleNum[i],
-1 + 0.15)
hists_EleDen['data_vv15sys'].Add(hists_EleDen[i],
-1 + 0.15)
hists_MuNum['data_vv15sys'].Add(hists_MuNum[i], -1 + 0.15)
hists_MuDen['data_vv15sys'].Add(hists_MuDen[i], -1 + 0.15)
hists_MuNum['data_bvvs'].Divide(hists_MuDen['data_bvvs'])
hists_EleNum['data_bvvs'].Divide(hists_EleDen['data_bvvs'])
hists_MuNum['data_vv15sys'].Divide(hists_MuDen['data_vv15sys'])
hists_EleNum['data_vv15sys'].Divide(hists_EleDen['data_vv15sys'])
hists_MuNum['data'].Divide(hists_MuDen['data'])
hists_EleNum['data'].Divide(hists_EleDen['data'])
f = ROOT.TFile('FakeFactors.root', 'recreate')
f.cd()
if 'data' in hists_EleNum.keys():
if not options.e: hists_MuNum['data'].Write("Muons")
if not options.mu: hists_EleNum['data'].Write("Electrons")
if not options.e: hists_MuNum['data_vv15sys'].Write("Muons_wzsyst")
if not options.mu:
hists_EleNum['data_vv15sys'].Write("Electrons_wzsyst")
f.Close()
g = ROOT.TFile('FakeFactors_mcClosure.root', 'recreate')
g.cd()
if (options.region == 'zjet'):
if not options.e: hists_MuNum['zjet'].Write('Muons')
if not options.mu: hists_EleNum['zjet'].Write('Electrons')
if (options.region == 'dijet'):
if not options.e: hists_MuNum['dijet'].Write('Muons')
if not options.mu: hists_EleNum['dijet'].Write('Electrons')
g.Close()
#
# systematic band histogram
#
from array import array
band = ROOT.TH1F('band', 'band', 5, array('d', [0, 15, 20, 30, 50, 100]))
def SetSysts(h_band, systs):
for i, sys in enumerate(systs):
h_band.SetBinContent(i + 1, 1)
h_band.SetBinError(i + 1, sys)
band.SetFillColor(ROOT.kOrange - 0)
band.SetMarkerSize(0)
band.SetMarkerColor(ROOT.kOrange - 0)
#
# Muon fake factor plots
#
if not options.e:
if 'zjet_sr' in hists_MuNum.keys():
cans.append(
plotfunc.RatioCanvas('lepPt_Mu_ff_systematic',
'%s_Mu_ff_systematic' % (v), 500, 500))
else:
cans.append(ROOT.TCanvas('lepPt_Mu_ff', '%s_Mu_ff' % (v), 500,
500))
if 'data' in hists_EleNum.keys():
if (options.region == 'dijet'):
plotfunc.AddHistogram(cans[-1], hists_MuNum['data_bws'])
plotfunc.AddHistogram(cans[-1], hists_MuNum['data_bzs'])
if 'dijet' in hists_EleNum.keys():
plotfunc.AddHistogram(cans[-1], hists_MuNum['dijet'])
if (options.region == 'zjet'):
if not options.syst:
plotfunc.AddHistogram(cans[-1], hists_MuNum['data_bvvs'])
#plotfunc.AddHistogram(cans[-1],hists_MuNum['data_vv15sys'])
pass
if not options.syst:
plotfunc.AddHistogram(cans[-1], hists_MuNum['data'])
if (options.region == 'zjet'):
if 'zjet' in hists_MuNum.keys():
plotfunc.AddHistogram(cans[-1], hists_MuNum['zjet'])
if 'zjet_sr' in hists_MuNum.keys():
if z_w == 'zid':
SetSysts(band, [0.0, 0.25, 0.2, 0.25, 0.25])
else:
SetSysts(band, [0.0, 0.0, 0.2, 0.30, 0.30])
plotfunc.AddHistogram(cans[-1].GetPrimitive('pad_bot'),
band, 'E2')
plotfunc.AddRatio(cans[-1], hists_MuNum['zjet_sr'],
hists_MuNum['zjet'])
#plotfunc.AddRatio(cans[-1],hists_MuNum['ttbar_sr'],hists_MuNum['zjet'])
if not plotfunc.CanvasEmpty(cans[-1]):
plotfunc.FormatCanvasAxes(cans[-1])
#taxisfunc.SetYaxisRanges(cans[-1],0,0.5)
plotfunc.MakeLegend(cans[-1])
additionaltext = ('supporting triggers'
if options.region == 'dijet' else None)
plotfunc.FullFormatCanvasDefault(cans[-1],
sqrts=13,
lumi=options.fb,
additionaltext=additionaltext)
if 'zjet_sr' in hists_MuNum.keys():
taxisfunc.SetYaxisRanges(cans[-1].GetPrimitive('pad_bot'), -1,
3)
plotfunc.SetAxisLabels(cans[-1], 'p_{T} [GeV]', 'fake factor')
#
# electron fake factor plots
#
if not options.mu:
if 'zjet_sr' in hists_EleNum.keys():
cans.append(
plotfunc.RatioCanvas('lepPt_Ele_ff_systematic',
'%s_Ele_ff_systematic' % (v), 500, 500))
else:
cans.append(
ROOT.TCanvas('lepPt_Ele_ff', '%s_Ele_ff' % (v), 500, 500))
if 'data' in hists_EleNum.keys():
if (options.region == 'dijet'):
plotfunc.AddHistogram(cans[-1], hists_EleNum['data_bws'])
plotfunc.AddHistogram(cans[-1], hists_EleNum['data_bzs'])
if 'dijet' in hists_EleNum.keys():
plotfunc.AddHistogram(cans[-1], hists_EleNum['dijet'])
if (options.region == 'zjet'):
if not options.syst:
plotfunc.AddHistogram(cans[-1], hists_EleNum['data_bvvs'])
#plotfunc.AddHistogram(cans[-1],hists_EleNum['data_vv15sys'])
if not options.syst:
plotfunc.AddHistogram(cans[-1], hists_EleNum['data'])
if (options.region == 'zjet'):
if 'zjet' in hists_EleNum.keys():
plotfunc.AddHistogram(cans[-1], hists_EleNum['zjet'])
if 'zjet_sr' in hists_EleNum.keys():
if z_w == 'zid':
SetSysts(band, [0.0, 0.55, 0.30, 0.40, 0.60])
else:
SetSysts(band, [0.0, 0.0, 0.25, 0.25, 0.65])
plotfunc.AddHistogram(cans[-1].GetPrimitive('pad_bot'),
band, 'E2')
plotfunc.AddRatio(cans[-1], hists_EleNum['zjet_sr'],
hists_EleNum['zjet'])
#plotfunc.AddRatio(cans[-1],hists_EleNum['ttbar_sr'],hists_EleNum['zjet'])
if not plotfunc.CanvasEmpty(cans[-1]):
plotfunc.FormatCanvasAxes(cans[-1])
#taxisfunc.SetYaxisRanges(cans[-1],0,0.5)
plotfunc.MakeLegend(cans[-1])
additionaltext = ('supporting triggers'
if options.region == 'dijet' else None)
plotfunc.FullFormatCanvasDefault(cans[-1],
sqrts=13,
lumi=options.fb,
additionaltext=additionaltext)
if 'zjet_sr' in hists_EleNum.keys():
taxisfunc.SetYaxisRanges(cans[-1].GetPrimitive('pad_bot'), -1,
3)
plotfunc.SetAxisLabels(cans[-1], 'p_{T} [GeV]', 'fake factor')
raw_input('Pausing. Press enter to exit.')
if options.save:
for can in cans:
can.Print(can.GetName() + '.pdf')
can.Print(can.GetName() + '.eps')
print 'done.'
return
def main(options, args):
plotfunc.SetupStyle()
for i in options.histformat.keys():
print '\'%s\':' % (i), options.histformat[i]
anaplot.LoadRootCore()
files_b, trees_b, keys_b, cf_b = anaplot.GetTreesFromFiles(options.bkgs)
files_s, trees_s, keys_s, cf_s = anaplot.GetTreesFromFiles(options.susy)
file_d, tree_d, key_d, cf_d = anaplot.GetTreesFromFiles(options.data)
options.fb, lumi_scale_factor = helpers.GetTTreeLumiScaleFactor(
files_b + files_s, options.fb)
dweight = ''
weight = 'TotalWeightNoSF'
if ''.join(options.cuts):
weight = weight + '*(%s)' % (' && '.join(options.cuts))
dweight = '(' + ' && '.join(options.cuts) + ')'
if hasattr(options.usermodule, 'weight'):
weight += '*(%s)' % (options.usermodule.weight)
if hasattr(options.usermodule, 'dataweight'):
dweight += '*(%s)' % (options.usermodule.dataweight)
cans = []
# get the histograms from the files
for v in options.variables.split(','):
n, low, high = options.histformat[v][:3]
xlabel = options.histformat[v][3]
bkg_hists = []
sig_hists = []
data_hist = None
rebin = []
if hasattr(options.usermodule,
'rebin') and v in options.usermodule.rebin.keys():
rebin = options.usermodule.rebin[v]
if options.bkgs:
bkg_hists = anaplot.GetVariableHistsFromTrees(
trees_b,
keys_b,
v,
weight,
n,
low,
high,
normalize=options.normalize,
rebin=rebin,
scale=lumi_scale_factor)
anaplot.PrepareBkgHistosForStack(bkg_hists)
if options.susy:
sig_hists = anaplot.GetVariableHistsFromTrees(
trees_s,
keys_s,
v,
weight,
n,
low,
high,
normalize=options.normalize,
rebin=rebin,
scale=lumi_scale_factor)
if options.data:
data_hist = anaplot.GetVariableHistsFromTrees(
tree_d,
key_d,
v,
dweight,
n,
low,
high,
normalize=options.normalize,
rebin=rebin,
scale=lumi_scale_factor)[0]
data_hist.SetLineWidth(2)
data_hist.SetLineColor(1)
data_hist.SetMarkerColor(1)
nsignal = 0
for si, s in enumerate(keys_s):
mass_map = GetMassesMap()
for i in mass_map.keys():
if str(i) in sig_hists[si].GetName():
title = '%s,%s' % (mass_map[i]['mc1'], mass_map[i]['mn1'])
sig_hists[si].SetTitle(title)
sig_hists[si].SetLineWidth(2)
sig_hists[si].SetLineColor(signal_colors[nsignal])
sig_hists[si].SetMarkerColor(signal_colors[nsignal])
nsignal += 1
cans.append(
anaplot.DrawHistos(v,
v,
xlabel,
bkg_hists,
sig_hists,
data_hist,
dostack=options.stack,
log=options.log,
ratio=options.ratio,
fb=options.fb))
if not options.batch:
raw_input('Press enter to exit')
if options.save:
for can in cans:
can.Print(can.GetName() + '.pdf')
print 'done.'
return
def main(options, args):
plotfunc.SetupStyle()
for i in options.histformat.keys():
print '\'%s\':' % (i), options.histformat[i]
anaplot.LoadRootCore()
files_mc1, trees_mc1, keys_mc1, cf_mc1 = anaplot.GetTreesFromFiles(
options.mc1)
files_mc2, trees_mc2, keys_mc2, cf_mc2 = anaplot.GetTreesFromFiles(
options.mc2)
weight = 'TotalWeightNoSF'
if ''.join(options.cuts):
weight = weight + '*(%s)' % (' && '.join(options.cuts))
if hasattr(options.usermodule, 'weight'):
weight += '*(%s)' % (options.usermodule.weight)
cans = []
# get the histograms from the files
for v in options.variables.split(','):
n, low, high = options.histformat[v][:3]
xlabel = options.histformat[v][3]
mc_hists = []
rebin = []
if hasattr(options.usermodule,
'rebin') and v in options.usermodule.rebin.keys():
rebin = options.usermodule.rebin[v]
if options.mc1:
mc_hists.append(
anaplot.GetVariableHistsFromTrees(trees_mc1,
keys_mc1,
v,
weight,
n,
low,
high,
normalize=options.normalize,
rebin=rebin)[0])
mc_hists[-1].SetTitle(options.label1)
mc_hists[-1].SetLineWidth(2)
mc_hists[-1].SetLineColor(1)
mc_hists[-1].SetMarkerColor(1)
if options.mc2:
mc_hists.append(
anaplot.GetVariableHistsFromTrees(trees_mc2,
keys_mc2,
v,
weight,
n,
low,
high,
normalize=options.normalize,
rebin=rebin)[0])
mc_hists[-1].SetTitle(options.label2)
mc_hists[-1].SetLineWidth(ROOT.kRed + 1)
mc_hists[-1].SetLineColor(ROOT.kRed + 1)
mc_hists[-1].SetMarkerColor(ROOT.kRed + 1)
cans.append(
anaplot.DrawHistos(v,
v,
xlabel,
mc_hists,
dostack=False,
log=options.log,
ratio=options.ratio,
fb=options.fb))
if not options.batch:
raw_input('Press enter to exit')
if options.save:
for can in cans:
can.Print(can.GetName() + '.pdf')
print 'done.'
return