print 'High MT W+jets estimated yield', yield_estimation
print 'High MT W+jets MC yield', yield_w_highmt_os
w_sf = yield_estimation / yield_w_highmt_os
print 'W+jets scale factor:', w_sf, '\n'
wjets.total_scale = w_sf
wjets_ss.total_scale = -w_sf
import pdb
pdb.set_trace()
for variable in variables:
cfg_main.var = variable
if qcd_from_same_sign:
qcd.var = variable # Can put into function but we will not want it by default if we take normalisations from e.g. high MT
if w_qcd_mssm_method:
wjets.var = variable # Can put into function but we will not want it by default if we take normalisations from e.g. high MT
qcd.var = variable
wjets_ss.var = variable
if variable.name in ['svfit_mass', 'svfit_transverse_mass']:
if cut.name in ['inclusive', 'nobtag']:
variable.binning = binning_mssm
elif cut.name in ['btag']:
variable.binning = binning_mssm_btag
plot = createHistogram(cfg_main, verbose=False)
createDefaultGroups(plot)
if sample.name != 'Data':
# Subtract background from data
sample.scale = -1.
qcd = HistogramCfg(name='QCD', var=None, cfgs=samples_ss, cut=inc_cut, lumi=40.0)
samples.append(qcd)
# Taken from Variables.py, can get subset with e.g. getVars(['mt', 'mvis'])
variables = all_vars
cfg_example = HistogramCfg(name='example', var=None, cfgs=samples, cut=inc_cut, lumi=40.0)
for cut_name in cuts:
cfg_example.cut = cuts[cut_name]
if qcd_from_same_sign and 'OS' in cut_name:
qcd.cut = cuts[cut_name].replace('l1_charge != l2_charge', 'l1_charge == l2_charge')
for variable in variables:
cfg_example.var = variable
if qcd_from_same_sign:
qcd.var = variable # Can put into function but we will not want it by default if we take normalisations from e.g. high MT
plot = createHistogram(cfg_example, verbose=True)
plot.Group('Diboson', ['ZZ', 'WZ', 'WW'])
plot.Group('Single t', ['T_tWch', 'TBar_tWch', 'TToLeptons_sch', 'TToLeptons_tch'])
plot.Group('ZLL', ['Ztt_ZL', 'Ztt_ZJ'], style=plot.Hist('Ztt_ZL').style)
HistDrawer.draw(plot, plot_dir='plots/'+cut_name)
name='loose_data',
var=None,
cfgs=samples,
cut=inc_cut,
lumi=int_lumi,
weight=total_weight + ' * ((genmet_pt < 0.) - (l2_gen_match == 5))')
cfg_tight.cut = cuts[cut_name]
cfg_loose.cut = cuts[cut_name].replace(
'l2_byCombinedIsolationDeltaBetaCorrRaw3Hits<1.5', '1.')
cfg_data_tight.cut = cuts[cut_name]
cfg_data_loose.cut = cuts[cut_name].replace(
'l2_byCombinedIsolationDeltaBetaCorrRaw3Hits<1.5', '1.')
for variable in variables:
cfg_tight.var = variable
cfg_loose.var = variable
cfg_data_tight.var = variable
cfg_data_loose.var = variable
plot_tight = createHistogram(cfg_tight, verbose=False)
plot_loose = createHistogram(cfg_loose, verbose=False)
plot_data_tight = createHistogram(cfg_data_tight,
verbose=False,
all_stack=True)
plot_data_loose = createHistogram(cfg_data_loose,
verbose=False,
all_stack=True)
for plot in [plot_tight, plot_loose, plot_data_tight, plot_data_loose]:
plot.Group('VV', ['ZZ', 'WZ', 'WW', 'T_tWch', 'TBar_tWch'])
out_dir = 'fakeplots/' + cut_name if plot is plot_tight else 'fakeplots/loose' + cut_name
var=None,
cfgs=samples_qcdfromss,
cut=inc_cut,
lumi=int_lumi,
weight=total_weight)
else:
cfg_example = HistogramCfg(name='example',
var=None,
cfgs=samples,
cut=inc_cut,
lumi=int_lumi,
weight=total_weight)
cfg_example.cut = cuts[cut_name]
if qcd_from_same_sign and not 'SS' in cut_name:
qcd.cut = cuts[cut_name].replace('l1_charge != l2_charge',
'l1_charge == l2_charge')
for variable in variables:
cfg_example.var = variable
if qcd_from_same_sign:
qcd.var = variable # Can put into function but we will not want it by default if we take normalisations from e.g. high MT
plot = createHistogram(cfg_example, verbose=True)
plot.Group('VV', ['ZZ', 'WZ', 'WW', 'T_tWch', 'TBar_tWch'])
# plot.Group('Single t', ['T_tWch', 'TBar_tWch', 'TToLeptons_sch', 'TToLeptons_tch'])
# plot.Group('ZLL', ['Ztt_ZL', 'Ztt_ZJ'], style=plot.Hist('Ztt_ZL').style)
HistDrawer.draw(plot, plot_dir='plots/RemoveLowMET_' + cut_name)
plot.WriteDataCard(filename='datacard_mvis.root', dir='mt_' + cut_name)
SampleCfg(name='WJetsToLNu', ana_dir=analysis_dir, tree_prod_name=tree_prod_name, xsec=WJetsToLNu.xSection, sumweights=WJetsToLNu.nGenEvents),
SampleCfg(name='TTJets', dir_name='TTLep_pow', ana_dir=analysis_dir, tree_prod_name=tree_prod_name, xsec=TT_pow.xSection, sumweights=TT_pow.nGenEvents),
SampleCfg(name='T_tWch', dir_name='T_tWch', ana_dir=analysis_dir, tree_prod_name=tree_prod_name, xsec=T_tWch.xSection, sumweights=T_tWch.nGenEvents),
SampleCfg(name='TBar_tWch', dir_name='TBar_tWch', ana_dir=analysis_dir, tree_prod_name=tree_prod_name, xsec=TBar_tWch.xSection, sumweights=TBar_tWch.nGenEvents),
SampleCfg(name='TToLeptons_tch', dir_name='TToLeptons_tch', ana_dir=analysis_dir, tree_prod_name=tree_prod_name, xsec=TToLeptons_tch.xSection, sumweights=TBar_tWch.nGenEvents),
SampleCfg(name='TToLeptons_sch', dir_name='TToLeptons_sch', ana_dir=analysis_dir, tree_prod_name=tree_prod_name, xsec=TToLeptons_sch.xSection, sumweights=TToLeptons_sch.nGenEvents),
SampleCfg(name='ZZ', dir_name='ZZp8', ana_dir=analysis_dir, tree_prod_name=tree_prod_name, xsec=ZZp8.xSection, sumweights=ZZp8.nGenEvents),
SampleCfg(name='WZ', dir_name='WZp8', ana_dir=analysis_dir, tree_prod_name=tree_prod_name, xsec=WZp8.xSection, sumweights=WZp8.nGenEvents),
SampleCfg(name='WW', dir_name='WWTo2L2Nu', ana_dir=analysis_dir, tree_prod_name=tree_prod_name, xsec=WWTo2L2Nu.xSection, sumweights=WWTo2L2Nu.nGenEvents),
SampleCfg(name='QCD', dir_name='QCD_Mu15', ana_dir=analysis_dir, tree_prod_name=tree_prod_name, xsec=QCD_Mu15.xSection),
SampleCfg(name='Data', dir_name='SingleMuon_Run2015B', ana_dir=data_dir, tree_prod_name=tree_prod_name, is_data=True),
]
# -> Can add cross sections for samples either explicitly, or from file, or from cfg
for sample in samples:
setSumWeights(sample)
# Taken from Variables.py, can get subset with e.g. getVars(['mt', 'mvis'])
variables = all_vars
cfg_example = HistogramCfg(name='example', var=None, cfgs=samples, cut=example_cut, lumi=40.0)
for variable in variables:
cfg_example.var = variable
plot = createHistogram(cfg_example)
plot.Group('Diboson', ['ZZ', 'WZ', 'WW'])
plot.Group('Single t', ['T_tWch', 'TBar_tWch', 'TToLeptons_sch', 'TToLeptons_tch'])
HistDrawer.draw(plot)
# HistDrawer.drawRatio(plot)
cut=inc_cut,
lumi=int_lumi,
weight='1.')
for var_set in var_sets:
print 'Variable set', var_set.name
cfg_signal.cut += var_set.cut_s
cfg_bg.cut += var_set.cut_b
rocs = []
sig_eff = None
bg_eff = None
for i_var, var in enumerate(var_set.vars):
print ' variable:', var
cfg_signal.var = var
cfg_bg.var = var
plot_signal = createHistogram(cfg_signal, verbose=False)
plot_bg = createHistogram(cfg_bg, verbose=False)
h_signal = plot_signal.GetStack().totalHist.weighted
h_bg = plot_bg.GetStack().totalHist.weighted
print 'Working point at cut 1.5:'
if not sig_eff and not bg_eff:
sig_eff = h_signal.Integral(
0, h_signal.FindBin(1.5)) / h_signal.Integral(
0,
h_signal.GetNbinsX() + 1)