for cut in cuts:
if qcd_from_same_sign and not 'SS' in cut.name and not w_qcd_mssm_method:
cfg_main = HistogramCfg(name=cut.name,
var=None,
cfgs=samples_qcdfromss,
cut=cut.cut,
lumi=int_lumi,
weight=total_weight)
elif w_qcd_mssm_method:
cfg_main = HistogramCfg(name=cut.name,
var=None,
cfgs=samples_mssm_method,
cut=cut.cut,
lumi=int_lumi,
weight=total_weight)
wjets.cut = cut.cut # since wjets is a sub-HistogramCfg
else:
cfg_main = HistogramCfg(name=cut.name,
var=None,
cfgs=all_samples,
cut=cut.cut,
lumi=int_lumi,
weight=total_weight)
if qcd_from_same_sign and not 'SS' in cut.name:
qcd.cut = cut.cut.replace('l1_charge != l2_charge',
'l1_charge == l2_charge')
if w_qcd_mssm_method:
stacknow_highmt_os.name = 'HighMTOS' + cut.name
stacknow_highmt_ss.name = 'HighMTSS' + cut.name
# variables = [lnujj_vars[0]]
# variables = getVars(['l1_reliso05', 'l2_reliso05'])
# variables = [
# VariableCfg(name='mvis', binning={'nbinsx':35, 'xmin':0, 'xmax':350}, unit='GeV', xtitle='m_{vis}')
# ]
for cut_name in cuts:
cfg_example = HistogramCfg(name='example',
var=None,
cfgs=samples,
cut='',
lumi=int_lumi,
weight=total_weight)
cfg_example.cut = cuts[cut_name]
cfg_example.vars = variables
channel = "l#nujj"
if cut_name.find("_mu") >= 0:
channel = "#mu#nujj"
elif cut_name.find("_e") >= 0:
channel = "e#nujj"
if cut_name.find("HP") >= 0:
channel += " HP"
elif cut_name.find("LP") >= 0:
channel += " LP"
plots = createHistograms(cfg_example, verbose=False)
for variable in variables:
plot = plots[variable.name]
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)
# Taken from Variables.py, can get subset with e.g. getVars(['mt', 'mvis'])
variables = emu_vars
# variables = getVars(['n_vertices'])
# variables = getVars(['l1_reliso05', 'l2_reliso05'])
# variables = [
# VariableCfg(name='mvis', binning={'nbinsx':35, 'xmin':0, 'xmax':350}, unit='GeV', xtitle='m_{vis}')
# ]
for cut_name in cuts:
if qcd_from_same_sign and not 'SS' in cut_name :
cfg_example = HistogramCfg(name='example', var=None, cfgs=samples_qcdfromss, cut=inc_cut, lumi=lumi, weight=total_weight)
else:
cfg_example = HistogramCfg(name='example', var=None, cfgs=samples, cut=inc_cut, lumi=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')
cfg_example.vars = variables
if qcd_from_same_sign:
qcd.vars = variables # Can put into function but we will not want it by default if we take normalisations from e.g. high MT
plots = createHistograms(cfg_example, verbose=True)
for variable in variables:
plot = plots[variable.name]
plot.Group('VV', ['WWTo1L1Nu2Q', 'WZTo1L1Nu2Q', 'WZTo1L3Nu', 'WZTo2L2Q', 'VVTo2L2Nu', 'ZZTo2L2Q', 'ZZTo4L'])
plot.Group('Single t', ['T_tWch', 'TBar_tWch', 'TBarToLeptons_tch_powheg', 'TToLeptons_tch_powheg'])
plot.Group('ZLL', ['ZL', 'ZJ'], style=plot.Hist('ZL').style)
plot.Group('W', ['W1Jets', 'W2Jets', 'W3Jets', 'W4Jets'])
samples_mc, samples_data, samples, all_samples, sampleDict = createSampleLists(analysis_dir, channel='WV', weight=weight_MC)
# Taken from Variables.py, can get subset with e.g. getVars(['mt', 'mvis'])
variables = generic_vars + lnujj_vars + lnujj_vbf_vars
# variables = [lnujj_vars[0]]
# variables = getVars(['l1_reliso05', 'l2_reliso05'])
# variables = [
# VariableCfg(name='mvis', binning={'nbinsx':35, 'xmin':0, 'xmax':350}, unit='GeV', xtitle='m_{vis}')
# ]
for cut_name in cuts:
cfg_example = HistogramCfg(name='example', var=None, cfgs=samples, cut='', lumi=int_lumi, weight=total_weight)
cfg_example.cut = cuts[cut_name].replace("||HLT_MET120", "")
cfg_example.vars = variables
channel = "l#nujj"
if cut_name.find("_mu") >= 0:
channel = "#mu#nujj"
elif cut_name.find("_e") >= 0:
channel = "e#nujj"
if cut_name.find("HP") >= 0:
channel += " HP"
elif cut_name.find("LP") >= 0:
channel += " LP"
plots = createHistograms(cfg_example, verbose=False)
for variable in variables:
plot = plots[variable.name]
cfg_data_tight = HistogramCfg(
name='tight_data',
var=None,
cfgs=samples,
cut=inc_cut,
lumi=int_lumi,
weight=total_weight + ' * ((genmet_pt < 0.) - (l2_gen_match == 5))')
cfg_data_loose = HistogramCfg(
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,
cut=inc_cut,
lumi=int_lumi,
weight=total_weight +
' * ((l2_gen_match == 6))')
tight_cut = inc_cut + cuts[cut_name] + cut_extra
loose_cut = tight_cut.replace(
'l2_byIsolationMVArun2v1DBoldDMwLT>2.5', '1.')
loose_cut = tight_cut.replace(
'l2_byIsolationMVArun2v1DBoldDMwLT>2.5',
'l2_byIsolationMVArun2v1DBoldDMwLT>0.5')
print 'Tight cut:', tight_cut
print 'Loose cut:', loose_cut
cfg_tight.cut = tight_cut
cfg_loose.cut = loose_cut
cfg_tight.var = variable
cfg_loose.var = variable
plot_tight = createHistogram(cfg_tight, verbose=False)
plot_loose = createHistogram(cfg_loose, verbose=False)
tight_hist = plot_tight.GetStack().totalHist.weighted
loose_hist = plot_loose.GetStack().totalHist.weighted
plot_inputs.append((tight_hist, loose_hist, sample_def['name'],
sample_def['colour'], sample_def['style']))
plotMCEffs(
cfg_tight_data = HistogramCfg(
name='tight_data',
var=None,
cfgs=samples,
cut=inc_cut,
lumi=int_lumi,
weight=total_weight + '*( (is_data>0.5) - (abs(tau1_gen_pdgId)==15))')
cfg_loose_data = HistogramCfg(
name='loose_data',
var=None,
cfgs=samples,
cut=inc_cut,
lumi=int_lumi,
weight=total_weight + '*( (is_data>0.5) - (abs(tau1_gen_pdgId)==15))')
cfg_tight.cut = cuts[cut_name][0]
cfg_loose.cut = cuts[cut_name][1]
cfg_tight_data.cut = cuts[cut_name][0]
cfg_loose_data.cut = cuts[cut_name][1]
for cfg in [cfg_tight, cfg_loose, cfg_tight_data, cfg_loose_data]:
cfg.vars = variables
plots_tight = createHistograms(cfg_tight, verbose=True)
plots_loose = createHistograms(cfg_loose, verbose=True)
plots_tight_data = createHistograms(cfg_tight_data,
verbose=True,
all_stack=True)
plots_loose_data = createHistograms(cfg_loose_data,
verbose=True,
all_stack=True)
cfg_data_tight = HistogramCfg(
name='tight_data',
var=None,
cfgs=samples,
cut=inc_cut,
lumi=int_lumi,
weight=total_weight + ' * ((genmet_pt < 0.) - (l2_gen_match == 5))')
cfg_data_loose = HistogramCfg(
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('tau1_decayModeFinding>0.', '1.')
cfg_data_tight.cut = cuts[cut_name]
cfg_data_loose.cut = cuts[cut_name].replace('tau1_decayModeFinding>0.',
'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,
if qcd_from_same_sign and not 'SS' in cut.name:
cfg_example = HistogramCfg(name=cut.name,
var=None,
cfgs=samples_qcdfromss,
cut=inc_cut,
lumi=int_lumi,
weight=total_weight)
else:
cfg_example = HistogramCfg(name=cut.name,
var=None,
cfgs=all_samples,
cut=inc_cut,
lumi=int_lumi,
weight=total_weight)
cfg_example.cut = cut.cut
if qcd_from_same_sign and not 'SS' in cut.name:
qcd.cut = cut.cut.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=False)
plot.Group('VV', [
'ZZTo2L2Q', 'WWTo1L1Nu2Q', 'WZTo1L3Nu', 'ZZTo4L', 'WZTo3L',
'WZTo2L2Q', 'WZTo1L1Nu2Q', 'T_tWch', 'TBar_tWch',
'TToLeptons_tch_powheg', 'TBarToLeptons_tch_powheg'
])
signal_cut_name,
var=None,
cfgs=samples,
cut=inc_cut,
lumi=int_lumi,
weight=total_weight)
cfg_stack_loose = HistogramCfg(name='loose_stack' + cut_name +
signal_cut_name,
var=None,
cfgs=samples,
cut=inc_cut,
lumi=int_lumi,
weight=total_weight)
for variable in variables:
cfg_tight.cut = cuts[cut_name] + signal_cut
cfg_loose.cut = cuts[cut_name]
cfg_data_tight.cut = cuts[cut_name] + signal_cut
cfg_data_loose.cut = cuts[cut_name]
cfg_stack_tight.cut = cuts[cut_name] + signal_cut
cfg_stack_loose.cut = cuts[cut_name]
if variable.name in ['jet_pt_up', 'jet_pt_down']:
for cfg in [
cfg_tight, cfg_loose, cfg_data_tight, cfg_data_loose,
cfg_stack_tight, cfg_stack_loose
]:
if variable.name == 'jet_pt_up':
cfg.cut = cfg.cut.replace(
'jet_pt',
'(jet_pt*(is_data + (1. - is_data)*jet_corrJECUp))'
