def createSampleLists(analysis_dir='samples/',
channel='VV',
weight='',
signalSample='',
vJetsKFac=1.,
reweightVJets=False,
reweightTop=False):
# settings and code to reweight V+jets samples (EW and QCD NLO corrections)
# the following two k-factors are from samples_13TeV_RunIISpring16MiniAODv2.py
wJetsKFac = 1.21
dyJetsKFac = 1.23
wJetsQCDCorrections = {}
dyJetsQCDCorrections = {}
# taken from http://cms.cern.ch/iCMS/jsp/db_notes/noteInfo.jsp?cmsnoteid=CMS%20AN-2015/186 (Table 4)
wJetsQCDCorrections["WJetsToLNu_HT100to200"] = 1.459 / wJetsKFac
wJetsQCDCorrections["WJetsToLNu_HT200to400"] = 1.434 / wJetsKFac
wJetsQCDCorrections["WJetsToLNu_HT400to600"] = 1.532 / wJetsKFac
wJetsQCDCorrections["WJetsToLNu_HT600to800"] = 1.004 / wJetsKFac
wJetsQCDCorrections["WJetsToLNu_HT800to1200"] = 1.004 / wJetsKFac
wJetsQCDCorrections["WJetsToLNu_HT1200to2500"] = 1.004 / wJetsKFac
wJetsQCDCorrections["WJetsToLNu_HT2500toInf"] = 1.004 / wJetsKFac
dyJetsQCDCorrections["DYJetsToLL_M50_HT100to200"] = 1.588 / dyJetsKFac
dyJetsQCDCorrections["DYJetsToLL_M50_HT200to400"] = 1.438 / dyJetsKFac
dyJetsQCDCorrections["DYJetsToLL_M50_HT400to600"] = 1.494 / dyJetsKFac
dyJetsQCDCorrections["DYJetsToLL_M50_HT600toInf"] = 1.139 / dyJetsKFac
# explicit list of samples:
wjetsSampleNames = [
"WJetsToLNu_HT1200to2500", "WJetsToLNu_HT2500toInf",
"WJetsToLNu_HT400to600", "WJetsToLNu_HT600to800",
"WJetsToLNu_HT800to1200", 'WJetsToLNu_HT100to200',
'WJetsToLNu_HT200to400'
]
dyjetsSampleNames = [
'DYJetsToLL_M50_HT100to200', 'DYJetsToLL_M50_HT200to400',
'DYJetsToLL_M50_HT400to600', 'DYJetsToLL_M50_HT600toInf'
]
ttjetsSampleNames = ["TT_pow_ext3"]
qcdSampleNames = [
"QCD_HT1000to1500", "QCD_HT1500to2000", "QCD_HT2000toInf",
"QCD_HT500to700", "QCD_HT700to1000"
]
vvSampleNames = ['WWTo1L1Nu2Q', 'WZTo1L1Nu2Q']
singleTopSampleNames = [
'TToLeptons_tch_powheg', 'TBarToLeptons_tch_powheg', 'TToLeptons_sch',
'TBar_tWch', 'T_tWch'
]
jj_SampleNames = qcdSampleNames
lnujj_SampleNames = ttjetsSampleNames + wjetsSampleNames + vvSampleNames + qcdSampleNames + dyjetsSampleNames + singleTopSampleNames
# cuts to split ttbar sample according to W decay
ttjetsWCut = '(lnujj_l2_mergedVTruth==1&&lnujj_l2_nearestBDRTruth>0.8)'
ttjetsNonWCut = '(!(lnujj_l2_mergedVTruth==1&&lnujj_l2_nearestBDRTruth>0.8))'
# add ttbar pT reweighting
if reweightTop:
ttjetsWCut += '*truth_genTop_weight'
ttjetsNonWCut += '*truth_genTop_weight'
tree_prod_name = ''
if (channel == "WV"):
channelSampleNames = lnujj_SampleNames
else:
channelSampleNames = jj_SampleNames
samples_essential = []
if "/sVJetsReweighting_cc.so" not in gSystem.GetLibraries():
ROOT.gROOT.ProcessLine(
".L %s/src/CMGTools/VVResonances/python/plotting/VJetsReweighting.cc+"
% os.environ['CMSSW_BASE'])
from ROOT import getDYWeight, getWWeight
# add QCD, DY+jets, W+jets, DiBosons and SingleTop samples, but not those with _ext, since they are merged with the others
for sample in QCDHT + DYJetsM50HT + WJetsToLNuHT + DiBosons + SingleTop:
vJetsWeight = str(vJetsKFac)
if sample.name in channelSampleNames:
if (sample in DYJetsM50HT) and reweightVJets:
vJetsWeight = 'getDYWeight(truth_genBoson_pt) * {}'.format(
dyJetsQCDCorrections[sample.name])
elif (sample in WJetsToLNuHT) and reweightVJets:
vJetsWeight = 'getWWeight(truth_genBoson_pt) * {}'.format(
wJetsQCDCorrections[sample.name])
samples_essential.append(
SampleCfg(name=sample.name,
dir_name=sample.name,
ana_dir=analysis_dir,
tree_prod_name=tree_prod_name,
xsec=sample.xSection,
sumweights=sample.nGenEvents,
weight_expr=('*'.join([weight, vJetsWeight]))))
# TTJets sample
for sample in [TT_pow]:
if sample.name in channelSampleNames:
# print "Adding", sample.name, sample.xSection, sample.nGenEvents, weight
samples_essential.append(
SampleCfg(name=sample.name + '_W',
dir_name=sample.name,
ana_dir=analysis_dir,
tree_prod_name=tree_prod_name,
xsec=sample.xSection,
sumweights=sample.nGenEvents,
weight_expr=('*'.join([weight, ttjetsWCut]))))
samples_essential.append(
SampleCfg(name=sample.name + '_nonW',
dir_name=sample.name,
ana_dir=analysis_dir,
tree_prod_name=tree_prod_name,
xsec=sample.xSection,
sumweights=sample.nGenEvents,
weight_expr=('*'.join([weight, ttjetsNonWCut]))))
# signal sample (set signal xsec to 5 pb)
samples_signal = []
if (signalSample):
for sample in signalSamples:
if sample.name == signalSample:
samples_signal.append(
SampleCfg(name=sample.name,
dir_name=sample.name,
ana_dir=analysis_dir,
tree_prod_name=tree_prod_name,
xsec=5.,
sumweights=sample.nGenEvents,
weight_expr=('*'.join([weight])),
is_signal=True))
samples_data = []
if channel == 'WV':
samples_data = [
SampleCfg(name='data_SingleMuon',
dir_name='SingleMuon_Run2016B_PromptReco_v2',
ana_dir=analysis_dir,
tree_prod_name=tree_prod_name,
is_data=True),
SampleCfg(name='data_SingleMuon',
dir_name='SingleMuon_Run2016C_PromptReco_v2',
ana_dir=analysis_dir,
tree_prod_name=tree_prod_name,
is_data=True),
SampleCfg(name='data_SingleMuon',
dir_name='SingleMuon_Run2016D_PromptReco_v2',
ana_dir=analysis_dir,
tree_prod_name=tree_prod_name,
is_data=True),
SampleCfg(name='data_SingleElectron',
dir_name='SingleElectron_Run2016B_PromptReco_v2',
ana_dir=analysis_dir,
tree_prod_name=tree_prod_name,
is_data=True),
SampleCfg(name='data_SingleElectron',
dir_name='SingleElectron_Run2016C_PromptReco_v2',
ana_dir=analysis_dir,
tree_prod_name=tree_prod_name,
is_data=True),
SampleCfg(name='data_SingleElectron',
dir_name='SingleElectron_Run2016D_PromptReco_v2',
ana_dir=analysis_dir,
tree_prod_name=tree_prod_name,
is_data=True),
SampleCfg(name='data_MET',
dir_name='MET_Run2016B_PromptReco_v2',
ana_dir=analysis_dir,
tree_prod_name=tree_prod_name,
is_data=True),
SampleCfg(name='data_MET',
dir_name='MET_Run2016C_PromptReco_v2',
ana_dir=analysis_dir,
tree_prod_name=tree_prod_name,
is_data=True),
SampleCfg(name='data_MET',
dir_name='MET_Run2016D_PromptReco_v2',
ana_dir=analysis_dir,
tree_prod_name=tree_prod_name,
is_data=True),
]
else:
samples_data = [
SampleCfg(name='data_JetHT',
dir_name='JetHT_Run2016B_PromptReco_v2',
ana_dir=analysis_dir,
tree_prod_name=tree_prod_name,
is_data=True),
SampleCfg(name='data_JetHT',
dir_name='JetHT_Run2016C_PromptReco_v2',
ana_dir=analysis_dir,
tree_prod_name=tree_prod_name,
is_data=True),
SampleCfg(name='data_JetHT',
dir_name='JetHT_Run2016D_PromptReco_v2',
ana_dir=analysis_dir,
tree_prod_name=tree_prod_name,
is_data=True),
]
# samples_WH = []
# mssm_names = ['HiggsSUSYBB80', 'HiggsSUSYBB90', 'HiggsSUSYBB100', 'HiggsSUSYBB110', 'HiggsSUSYBB120', 'HiggsSUSYBB130', 'HiggsSUSYBB140', 'HiggsSUSYBB160', 'HiggsSUSYBB180', 'HiggsSUSYBB200', 'HiggsSUSYBB250', 'HiggsSUSYBB300', 'HiggsSUSYBB350', 'HiggsSUSYBB400', 'HiggsSUSYBB450', 'HiggsSUSYBB500', 'HiggsSUSYBB600', 'HiggsSUSYBB700', 'HiggsSUSYBB900', 'HiggsSUSYBB1000', 'HiggsSUSYBB1200', 'HiggsSUSYBB1500', 'HiggsSUSYBB1600', 'HiggsSUSYBB1800', 'HiggsSUSYBB2000', 'HiggsSUSYBB2300', 'HiggsSUSYBB2600', 'HiggsSUSYBB2900', 'HiggsSUSYBB3200', 'HiggsSUSYGG80', 'HiggsSUSYGG90',
# 'HiggsSUSYGG100', 'HiggsSUSYGG110', 'HiggsSUSYGG120', 'HiggsSUSYGG130', 'HiggsSUSYGG140', 'HiggsSUSYGG160', 'HiggsSUSYGG180', 'HiggsSUSYGG200', 'HiggsSUSYGG250', 'HiggsSUSYGG300', 'HiggsSUSYGG400', 'HiggsSUSYGG450', 'HiggsSUSYGG500', 'HiggsSUSYGG600', 'HiggsSUSYGG700', 'HiggsSUSYGG800', 'HiggsSUSYGG900', 'HiggsSUSYGG1000', 'HiggsSUSYGG1200', 'HiggsSUSYGG1400', 'HiggsSUSYGG1500', 'HiggsSUSYGG1600', 'HiggsSUSYGG1800', 'HiggsSUSYGG2000', 'HiggsSUSYGG2300', 'HiggsSUSYGG2600', 'HiggsSUSYGG2900', 'HiggsSUSYGG3200'] # HiggsSUSYBB800, HiggsSUSYBB1400, HiggsSUSYGG350
# for name in mssm_names:
# samples_WH.append(SampleCfg(name=name.replace('HiggsSUSYBB', 'bbH').replace('HiggsSUSYGG', 'ggH'), dir_name=name,
# ana_dir=analysis_dir, tree_prod_name=tree_prod_name, xsec=1., sumweights=1., is_signal=True),)
samples_mc = samples_essential + samples_signal
samples = samples_essential + samples_data + samples_signal
all_samples = samples_mc + samples_data
# -> Can add cross sections for samples either explicitly, or from file, or from cfg
# (currently taken from htt_common)
weighted_list = []
for sample in samples_mc:
if sample.name not in weighted_list:
setSumWeights(sample)
# sampleDict = {s.name: s for s in all_samples}
sampleDict = {}
for s in all_samples:
sampleDict[s.name] = s
return samples_mc, samples_data, samples, all_samples, sampleDict
def createSampleLists(analysis_dir='samples/',
channel='VV',
weight='',
signalSample='',
vJetsKFac=1.,
qcdKFac=1.,
useQCDPt=False):
# settings and code to reweight V+jets samples (EW and QCD NLO corrections)
# the following two k-factors are from samples_13TeV_RunIISpring16MiniAODv2.py
# if reweightVJets and reweightVJets2015:
# raise AssertionError
# wJetsKFac = 1.21
# dyJetsKFac = 1.23
# wJetsQCDCorrections2015 = {}
# dyJetsQCDCorrections2015 = {}
# wJetsQCDCorrections = {}
# dyJetsQCDCorrections = {}
# # taken from http://cms.cern.ch/iCMS/jsp/db_notes/noteInfo.jsp?cmsnoteid=CMS%20AN-2015/186 (Table 4)
# wJetsQCDCorrections2015["WJetsToLNu_HT100to200"] = 1.459/wJetsKFac
# wJetsQCDCorrections2015["WJetsToLNu_HT200to400"] = 1.434/wJetsKFac
# wJetsQCDCorrections2015["WJetsToLNu_HT400to600"] = 1.532/wJetsKFac
# wJetsQCDCorrections2015["WJetsToLNu_HT600to800"] = 1.004/wJetsKFac
# wJetsQCDCorrections2015["WJetsToLNu_HT800to1200"] = 1.004/wJetsKFac
# wJetsQCDCorrections2015["WJetsToLNu_HT1200to2500"] = 1.004/wJetsKFac
# wJetsQCDCorrections2015["WJetsToLNu_HT2500toInf"] = 1.004/wJetsKFac
# dyJetsQCDCorrections2015["DYJetsToLL_M50_HT100to200"] = 1.588/dyJetsKFac
# dyJetsQCDCorrections2015["DYJetsToLL_M50_HT200to400"] = 1.438/dyJetsKFac
# dyJetsQCDCorrections2015["DYJetsToLL_M50_HT400to600"] = 1.494/dyJetsKFac
# dyJetsQCDCorrections2015["DYJetsToLL_M50_HT600to800"] = 1.139/dyJetsKFac
# dyJetsQCDCorrections2015["DYJetsToLL_M50_HT800to1200"] = 1.139/dyJetsKFac
# dyJetsQCDCorrections2015["DYJetsToLL_M50_HT1200to2500"] = 1.139/dyJetsKFac
# dyJetsQCDCorrections2015["DYJetsToLL_M50_HT2500toInf"] = 1.139/dyJetsKFac
# # new for Summer16 W+jets (see https://github.com/jmhogan/GenHTweight)
# wJetsQCDCorrections["WJetsToLNu_HT100to200"] = 0.998056
# wJetsQCDCorrections["WJetsToLNu_HT200to400"] = 0.978569
# wJetsQCDCorrections["WJetsToLNu_HT400to600"] = 0.928054
# wJetsQCDCorrections["WJetsToLNu_HT600to800"] = 0.856705
# wJetsQCDCorrections["WJetsToLNu_HT800to1200"] = 0.757463
# wJetsQCDCorrections["WJetsToLNu_HT1200to2500"] = 0.608292
# wJetsQCDCorrections["WJetsToLNu_HT2500toInf"] = 0.454246
# dyJetsQCDCorrections["DYJetsToLL_M50_HT100to200"] = 1.007516
# dyJetsQCDCorrections["DYJetsToLL_M50_HT200to400"] = 0.992853
# dyJetsQCDCorrections["DYJetsToLL_M50_HT400to600"] = 0.974071
# dyJetsQCDCorrections["DYJetsToLL_M50_HT600to800"] = 0.948367
# dyJetsQCDCorrections["DYJetsToLL_M50_HT800to1200"] = 0.883340
# dyJetsQCDCorrections["DYJetsToLL_M50_HT1200to2500"] = 0.749894
# dyJetsQCDCorrections["DYJetsToLL_M50_HT2500toInf"] = 0.617254
# explicit list of samples:
wjetsSampleNames = ["WJetsToQQ_HT800toInf"]
dyjetsSampleNames = ['ZJetsToQQ_HT800toInf']
ttjetsSampleNames = ["TTHad_pow"]
qcdSampleNames = [
'QCD_HT100to200', 'QCD_HT200to300', 'QCD_HT300to500', 'QCD_HT500to700',
'QCD_HT700to1000', 'QCD_HT1000to1500', 'QCD_HT1500to2000',
'QCD_HT2000toInf'
]
# vvSampleNames = ['WWTo1L1Nu2Q', 'WWTo1L1Nu2Q', 'WZTo1L1Nu2Q']
# singleTopSampleNames = ['Ttch_powheg', 'TBar_tch_powheg', 'TToLeptons_sch', 'TBar_tWch', 'T_tWch']
# topSamples = [TT_pow]
# if useTopMcatnlo:
# topSamples = [TTJets]
# ttjetsSampleNames = ["TTJets"]
# if useWJetsPt:
# wjetsSampleNames = ["WJetsToLNu_Pt_100To250", "WJetsToLNu_Pt_250To400", "WJetsToLNu_Pt_400To600", "WJetsToLNu_Pt_600ToInf"]
jj_SampleNames = qcdSampleNames + wjetsSampleNames + dyjetsSampleNames + ttjetsSampleNames
# cuts to split ttbar sample according to W decay
# ttjetsWCut = '(lnujj_l2_mergedVTruth==1&&lnujj_l2_nearestBDRTruth>0.8)'
# ttjetsNonWCut = '(!(lnujj_l2_mergedVTruth==1&&lnujj_l2_nearestBDRTruth>0.8))'
# add ttbar pT reweighting
# if reweightTop:
# ttjetsWCut += '*truth_genTop_weight'
# ttjetsNonWCut += '*truth_genTop_weight'
tree_prod_name = ''
# if (channel == "WV"):
# channelSampleNames = lnujj_SampleNames
# else:
channelSampleNames = jj_SampleNames
samples_essential = []
# if "/sVJetsReweighting_cc.so" not in gSystem.GetLibraries():
# ROOT.gROOT.ProcessLine(".L %s/src/CMGTools/VVResonances/python/plotting/VJetsReweighting.cc+" % os.environ['CMSSW_BASE'])
# from ROOT import getDYWeight, getWWeight
# add samples
for sample in QCDHT + QCDPt + VJetsQQHT + [TTHad_pow]:
vJetsWeight = "1." # str(vJetsKFac)
if sample.name in channelSampleNames:
if sample.name in qcdSampleNames:
vJetsWeight = str(qcdKFac)
if sample.name in (wjetsSampleNames + dyjetsSampleNames):
vJetsWeight = str(0.3)
# if (sample in DYJetsM50HT) and reweightVJets:
# vJetsWeight = '{} * {}'.format(vJetsKFac, dyJetsQCDCorrections[sample.name])
# elif (sample in WJetsToLNuHT) and reweightVJets:
# vJetsWeight = '{} * {}'.format(vJetsKFac, wJetsQCDCorrections[sample.name])
# if (sample in DYJetsM50HT) and reweightVJets2015:
# vJetsWeight = 'getDYWeight(truth_genBoson_pt) * {} * {}'.format(vJetsKFac, dyJetsQCDCorrections2015[sample.name])
# elif (sample in WJetsToLNuHT) and reweightVJets2015:
# vJetsWeight = 'getWWeight(truth_genBoson_pt) * {} * {}'.format(vJetsKFac, wJetsQCDCorrections2015[sample.name])
samples_essential.append(
SampleCfg(name=sample.name,
dir_name=sample.name,
ana_dir=analysis_dir,
tree_prod_name=tree_prod_name,
xsec=sample.xSection,
sumweights=sample.nGenEvents,
weight_expr=('*'.join([weight, vJetsWeight]))))
# # TTJets sample
# for sample in topSamples:
# if sample.name in channelSampleNames:
# # print "Adding", sample.name, sample.xSection, sample.nGenEvents, weight
# samples_essential.append(
# SampleCfg(name=sample.name+'_W', dir_name=sample.name, ana_dir=analysis_dir, tree_prod_name=tree_prod_name,
# xsec=sample.xSection, sumweights=sample.nGenEvents, weight_expr=('*'.join([weight, ttjetsWCut]))))
# samples_essential.append(
# SampleCfg(name=sample.name+'_nonW', dir_name=sample.name, ana_dir=analysis_dir, tree_prod_name=tree_prod_name,
# xsec=sample.xSection, sumweights=sample.nGenEvents, weight_expr=('*'.join([weight, ttjetsNonWCut]))))
# signal sample (set signal xsec to 5 pb)
samples_signal = []
if (signalSample):
for sample in signalSamples:
if sample.name == signalSample:
samples_signal.append(
SampleCfg(name=sample.name,
dir_name=sample.name,
ana_dir=analysis_dir,
tree_prod_name=tree_prod_name,
xsec=5.,
sumweights=sample.nGenEvents,
weight_expr=('*'.join([weight])),
is_signal=True))
samples_data = []
if channel == 'WV':
samples_data = [
SampleCfg(name='data_SingleMuon',
dir_name='SingleMuon_Run2016B_17Nov2017',
ana_dir=analysis_dir,
tree_prod_name=tree_prod_name,
is_data=True),
SampleCfg(name='data_SingleMuon',
dir_name='SingleMuon_Run2016C_17Nov2017',
ana_dir=analysis_dir,
tree_prod_name=tree_prod_name,
is_data=True),
SampleCfg(name='data_SingleMuon',
dir_name='SingleMuon_Run2016D_17Nov2017',
ana_dir=analysis_dir,
tree_prod_name=tree_prod_name,
is_data=True),
SampleCfg(name='data_SingleMuon',
dir_name='SingleMuon_Run2016E_17Nov2017',
ana_dir=analysis_dir,
tree_prod_name=tree_prod_name,
is_data=True),
SampleCfg(name='data_SingleMuon',
dir_name='SingleMuon_Run2016F_17Nov2017',
ana_dir=analysis_dir,
tree_prod_name=tree_prod_name,
is_data=True),
SampleCfg(name='data_SingleMuon',
dir_name='SingleMuon_Run2016G_17Nov2017',
ana_dir=analysis_dir,
tree_prod_name=tree_prod_name,
is_data=True),
SampleCfg(name='data_SingleMuon',
dir_name='SingleMuon_Run2016H_17Nov2017',
ana_dir=analysis_dir,
tree_prod_name=tree_prod_name,
is_data=True),
SampleCfg(name='data_SingleMuon',
dir_name='SingleMuon_Run2016H_17Nov2017',
ana_dir=analysis_dir,
tree_prod_name=tree_prod_name,
is_data=True),
SampleCfg(name='data_SingleElectron',
dir_name='SingleElectron_Run2016B_17Nov2017',
ana_dir=analysis_dir,
tree_prod_name=tree_prod_name,
is_data=True),
SampleCfg(name='data_SingleElectron',
dir_name='SingleElectron_Run2016C_17Nov2017',
ana_dir=analysis_dir,
tree_prod_name=tree_prod_name,
is_data=True),
SampleCfg(name='data_SingleElectron',
dir_name='SingleElectron_Run2016D_17Nov2017',
ana_dir=analysis_dir,
tree_prod_name=tree_prod_name,
is_data=True),
SampleCfg(name='data_SingleElectron',
dir_name='SingleElectron_Run2016E_17Nov2017',
ana_dir=analysis_dir,
tree_prod_name=tree_prod_name,
is_data=True),
SampleCfg(name='data_SingleElectron',
dir_name='SingleElectron_Run2016F_17Nov2017',
ana_dir=analysis_dir,
tree_prod_name=tree_prod_name,
is_data=True),
SampleCfg(name='data_SingleElectron',
dir_name='SingleElectron_Run2016G_17Nov2017',
ana_dir=analysis_dir,
tree_prod_name=tree_prod_name,
is_data=True),
SampleCfg(name='data_SingleElectron',
dir_name='SingleElectron_Run2016H_17Nov2017',
ana_dir=analysis_dir,
tree_prod_name=tree_prod_name,
is_data=True),
SampleCfg(name='data_SingleElectron',
dir_name='SingleElectron_Run2016H_17Nov2017',
ana_dir=analysis_dir,
tree_prod_name=tree_prod_name,
is_data=True),
SampleCfg(name='data_MET',
dir_name='MET_Run2016B_17Nov2017',
ana_dir=analysis_dir,
tree_prod_name=tree_prod_name,
is_data=True),
SampleCfg(name='data_MET',
dir_name='MET_Run2016C_17Nov2017',
ana_dir=analysis_dir,
tree_prod_name=tree_prod_name,
is_data=True),
SampleCfg(name='data_MET',
dir_name='MET_Run2016D_17Nov2017',
ana_dir=analysis_dir,
tree_prod_name=tree_prod_name,
is_data=True),
SampleCfg(name='data_MET',
dir_name='MET_Run2016E_17Nov2017',
ana_dir=analysis_dir,
tree_prod_name=tree_prod_name,
is_data=True),
SampleCfg(name='data_MET',
dir_name='MET_Run2016F_17Nov2017',
ana_dir=analysis_dir,
tree_prod_name=tree_prod_name,
is_data=True),
SampleCfg(name='data_MET',
dir_name='MET_Run2016G_17Nov2017',
ana_dir=analysis_dir,
tree_prod_name=tree_prod_name,
is_data=True),
SampleCfg(name='data_MET',
dir_name='MET_Run2016H_17Nov2017',
ana_dir=analysis_dir,
tree_prod_name=tree_prod_name,
is_data=True),
SampleCfg(name='data_MET',
dir_name='MET_Run2016H_17Nov2017',
ana_dir=analysis_dir,
tree_prod_name=tree_prod_name,
is_data=True),
]
else:
samples_data = [
SampleCfg(name='data_JetHT',
dir_name='JetHT_Run2017B_17Nov2017',
ana_dir=analysis_dir,
tree_prod_name=tree_prod_name,
is_data=True),
SampleCfg(name='data_JetHT',
dir_name='JetHT_Run2017C_17Nov2017',
ana_dir=analysis_dir,
tree_prod_name=tree_prod_name,
is_data=True),
SampleCfg(name='data_JetHT',
dir_name='JetHT_Run2017D_17Nov2017',
ana_dir=analysis_dir,
tree_prod_name=tree_prod_name,
is_data=True),
SampleCfg(name='data_JetHT',
dir_name='JetHT_Run2017E_17Nov2017',
ana_dir=analysis_dir,
tree_prod_name=tree_prod_name,
is_data=True),
SampleCfg(name='data_JetHT',
dir_name='JetHT_Run2017F_17Nov2017',
ana_dir=analysis_dir,
tree_prod_name=tree_prod_name,
is_data=True),
]
# samples_WH = []
# mssm_names = ['HiggsSUSYBB80', 'HiggsSUSYBB90', 'HiggsSUSYBB100', 'HiggsSUSYBB110', 'HiggsSUSYBB120', 'HiggsSUSYBB130', 'HiggsSUSYBB140', 'HiggsSUSYBB160', 'HiggsSUSYBB180', 'HiggsSUSYBB200', 'HiggsSUSYBB250', 'HiggsSUSYBB300', 'HiggsSUSYBB350', 'HiggsSUSYBB400', 'HiggsSUSYBB450', 'HiggsSUSYBB500', 'HiggsSUSYBB600', 'HiggsSUSYBB700', 'HiggsSUSYBB900', 'HiggsSUSYBB1000', 'HiggsSUSYBB1200', 'HiggsSUSYBB1500', 'HiggsSUSYBB1600', 'HiggsSUSYBB1800', 'HiggsSUSYBB2000', 'HiggsSUSYBB2300', 'HiggsSUSYBB2600', 'HiggsSUSYBB2900', 'HiggsSUSYBB3200', 'HiggsSUSYGG80', 'HiggsSUSYGG90',
# 'HiggsSUSYGG100', 'HiggsSUSYGG110', 'HiggsSUSYGG120', 'HiggsSUSYGG130', 'HiggsSUSYGG140', 'HiggsSUSYGG160', 'HiggsSUSYGG180', 'HiggsSUSYGG200', 'HiggsSUSYGG250', 'HiggsSUSYGG300', 'HiggsSUSYGG400', 'HiggsSUSYGG450', 'HiggsSUSYGG500', 'HiggsSUSYGG600', 'HiggsSUSYGG700', 'HiggsSUSYGG800', 'HiggsSUSYGG900', 'HiggsSUSYGG1000', 'HiggsSUSYGG1200', 'HiggsSUSYGG1400', 'HiggsSUSYGG1500', 'HiggsSUSYGG1600', 'HiggsSUSYGG1800', 'HiggsSUSYGG2000', 'HiggsSUSYGG2300', 'HiggsSUSYGG2600', 'HiggsSUSYGG2900', 'HiggsSUSYGG3200'] # HiggsSUSYBB800, HiggsSUSYBB1400, HiggsSUSYGG350
# for name in mssm_names:
# samples_WH.append(SampleCfg(name=name.replace('HiggsSUSYBB', 'bbH').replace('HiggsSUSYGG', 'ggH'), dir_name=name,
# ana_dir=analysis_dir, tree_prod_name=tree_prod_name, xsec=1., sumweights=1., is_signal=True),)
samples_mc = samples_essential + samples_signal
samples = samples_essential + samples_data + samples_signal
all_samples = samples_mc + samples_data
# -> Can add cross sections for samples either explicitly, or from file, or from cfg
# (currently taken from htt_common)
weighted_list = []
for sample in samples_mc:
if sample.name not in weighted_list:
setSumWeights(sample)
# sampleDict = {s.name: s for s in all_samples}
sampleDict = {}
for s in all_samples:
sampleDict[s.name] = s
return samples_mc, samples_data, samples, all_samples, sampleDict
def createSampleLists(analysis_dir='samples/', channel='VV', weight=''):
# -> Possibly from cfg like in the past, but may also make sense to enter directly
tree_prod_name = ''
samples_essential = []
# add QCD samples, but not those with _ext, since they are not produced
for sample in QCDHT:
if not (sample.name.find("_ext") >= 0):
samples_essential.append(
SampleCfg(name=sample.name,
dir_name=sample.name,
ana_dir=analysis_dir,
tree_prod_name=tree_prod_name,
xsec=sample.xSection,
sumweights=sample.nGenEvents,
weight_expr=weight))
# TTJets sample
samples_essential.append(
SampleCfg(name=TTJets.name,
dir_name=TTJets.name,
ana_dir=analysis_dir,
tree_prod_name=tree_prod_name,
xsec=TTJets.xSection,
sumweights=TTJets.nGenEvents,
weight_expr=weight))
# DY+jets samples, but not those with _ext, since they are not produced
for dySample in DYJetsM50HT:
if not (sample.name.find("_ext") >= 0):
samples_essential.append(
SampleCfg(name=dySample.name,
dir_name=dySample.name,
ana_dir=analysis_dir,
tree_prod_name=tree_prod_name,
xsec=dySample.xSection,
sumweights=dySample.nGenEvents,
weight_expr=weight))
# W+jets samples, but not those with _ext, since they are not produced
for sample in WJetsToLNuHT:
if not (sample.name.find("_ext") >= 0):
samples_essential.append(
SampleCfg(name=sample.name,
dir_name=sample.name,
ana_dir=analysis_dir,
tree_prod_name=tree_prod_name,
xsec=sample.xSection,
sumweights=sample.nGenEvents,
weight_expr=weight))
# DiBosons samples
for sample in DiBosons:
if not (sample.name.find("NuNu") >= 0):
samples_essential.append(
SampleCfg(name=sample.name,
dir_name=sample.name,
ana_dir=analysis_dir,
tree_prod_name=tree_prod_name,
xsec=sample.xSection,
sumweights=sample.nGenEvents,
weight_expr=weight))
# SingleTop samples
for sample in SingleTop:
if not (sample.name.find("tZq_ll") >= 0):
samples_essential.append(
SampleCfg(name=sample.name,
dir_name=sample.name,
ana_dir=analysis_dir,
tree_prod_name=tree_prod_name,
xsec=sample.xSection,
sumweights=sample.nGenEvents,
weight_expr=weight))
samples_data = []
# if channel in ['VV']:
samples_data = [
SampleCfg(name='data_obs',
dir_name='JetHT_Run2016B_PromptReco_v2',
ana_dir=analysis_dir,
tree_prod_name=tree_prod_name,
is_data=True),
SampleCfg(name='data_obs',
dir_name='JetHT_Run2016C_PromptReco_v2',
ana_dir=analysis_dir,
tree_prod_name=tree_prod_name,
is_data=True),
SampleCfg(name='data_obs',
dir_name='JetHT_Run2016D_PromptReco_v2',
ana_dir=analysis_dir,
tree_prod_name=tree_prod_name,
is_data=True),
SampleCfg(name='data_obs',
dir_name='SingleMuon_Run2016B_PromptReco_v2',
ana_dir=analysis_dir,
tree_prod_name=tree_prod_name,
is_data=True),
SampleCfg(name='data_obs',
dir_name='SingleMuon_Run2016C_PromptReco_v2',
ana_dir=analysis_dir,
tree_prod_name=tree_prod_name,
is_data=True),
SampleCfg(name='data_obs',
dir_name='SingleMuon_Run2016D_PromptReco_v2',
ana_dir=analysis_dir,
tree_prod_name=tree_prod_name,
is_data=True),
SampleCfg(name='data_obs',
dir_name='SingleElectron_Run2016B_PromptReco_v2',
ana_dir=analysis_dir,
tree_prod_name=tree_prod_name,
is_data=True),
SampleCfg(name='data_obs',
dir_name='SingleElectron_Run2016C_PromptReco_v2',
ana_dir=analysis_dir,
tree_prod_name=tree_prod_name,
is_data=True),
SampleCfg(name='data_obs',
dir_name='SingleElectron_Run2016D_PromptReco_v2',
ana_dir=analysis_dir,
tree_prod_name=tree_prod_name,
is_data=True),
]
# samples_WH = []
# mssm_names = ['HiggsSUSYBB80', 'HiggsSUSYBB90', 'HiggsSUSYBB100', 'HiggsSUSYBB110', 'HiggsSUSYBB120', 'HiggsSUSYBB130', 'HiggsSUSYBB140', 'HiggsSUSYBB160', 'HiggsSUSYBB180', 'HiggsSUSYBB200', 'HiggsSUSYBB250', 'HiggsSUSYBB300', 'HiggsSUSYBB350', 'HiggsSUSYBB400', 'HiggsSUSYBB450', 'HiggsSUSYBB500', 'HiggsSUSYBB600', 'HiggsSUSYBB700', 'HiggsSUSYBB900', 'HiggsSUSYBB1000', 'HiggsSUSYBB1200', 'HiggsSUSYBB1500', 'HiggsSUSYBB1600', 'HiggsSUSYBB1800', 'HiggsSUSYBB2000', 'HiggsSUSYBB2300', 'HiggsSUSYBB2600', 'HiggsSUSYBB2900', 'HiggsSUSYBB3200', 'HiggsSUSYGG80', 'HiggsSUSYGG90',
# 'HiggsSUSYGG100', 'HiggsSUSYGG110', 'HiggsSUSYGG120', 'HiggsSUSYGG130', 'HiggsSUSYGG140', 'HiggsSUSYGG160', 'HiggsSUSYGG180', 'HiggsSUSYGG200', 'HiggsSUSYGG250', 'HiggsSUSYGG300', 'HiggsSUSYGG400', 'HiggsSUSYGG450', 'HiggsSUSYGG500', 'HiggsSUSYGG600', 'HiggsSUSYGG700', 'HiggsSUSYGG800', 'HiggsSUSYGG900', 'HiggsSUSYGG1000', 'HiggsSUSYGG1200', 'HiggsSUSYGG1400', 'HiggsSUSYGG1500', 'HiggsSUSYGG1600', 'HiggsSUSYGG1800', 'HiggsSUSYGG2000', 'HiggsSUSYGG2300', 'HiggsSUSYGG2600', 'HiggsSUSYGG2900', 'HiggsSUSYGG3200'] # HiggsSUSYBB800, HiggsSUSYBB1400, HiggsSUSYGG350
# for name in mssm_names:
# samples_WH.append(SampleCfg(name=name.replace('HiggsSUSYBB', 'bbH').replace('HiggsSUSYGG', 'ggH'), dir_name=name,
# ana_dir=analysis_dir, tree_prod_name=tree_prod_name, xsec=1., sumweights=1., is_signal=True),)
samples_mc = samples_essential # + samples_WH
samples = samples_essential + samples_data
all_samples = samples_mc + samples_data
# -> Can add cross sections for samples either explicitly, or from file, or from cfg
# (currently taken from htt_common)
weighted_list = []
for sample in samples_mc:
if sample.name not in weighted_list:
setSumWeights(sample)
# sampleDict = {s.name: s for s in all_samples}
sampleDict = {}
for s in all_samples:
sampleDict[s.name] = s
return samples_mc, samples_data, samples, all_samples, sampleDict
def createSampleLists(analysis_dir='/data/clange/ntuples/2015_76X_Pruning/',
channel='VV',
weight=''):
# -> Possibly from cfg like in the past, but may also make sense to enter directly
tree_prod_name = ''
samples_essential = []
for qcdSample in QCDHT:
if not ((qcdSample.name.find("_ext") >= 0) or
(qcdSample.name.find("100to200") >= 0)):
print qcdSample.name
samples_essential.append(
SampleCfg(name=qcdSample.name,
dir_name=qcdSample.name,
ana_dir=analysis_dir,
tree_prod_name=tree_prod_name,
xsec=qcdSample.xSection,
sumweights=qcdSample.nGenEvents,
weight_expr=weight))
samples_essential.append(
SampleCfg(name=TTJets.name,
dir_name=TTJets.name,
ana_dir=analysis_dir,
tree_prod_name=tree_prod_name,
xsec=TTJets.xSection,
sumweights=TTJets.nGenEvents,
weight_expr=weight))
samples_data = []
# if channel in ['VV']:
samples_data = [
# SampleCfg(name='data_obs', dir_name='JetHT_Run2015C_25ns_16Dec', ana_dir=analysis_dir, tree_prod_name=tree_prod_name, is_data=True),
SampleCfg(name='data_obs',
dir_name='JetHT_Run2015D_16Dec',
ana_dir=analysis_dir,
tree_prod_name=tree_prod_name,
is_data=True),
]
# samples_WH = []
# mssm_names = ['HiggsSUSYBB80', 'HiggsSUSYBB90', 'HiggsSUSYBB100', 'HiggsSUSYBB110', 'HiggsSUSYBB120', 'HiggsSUSYBB130', 'HiggsSUSYBB140', 'HiggsSUSYBB160', 'HiggsSUSYBB180', 'HiggsSUSYBB200', 'HiggsSUSYBB250', 'HiggsSUSYBB300', 'HiggsSUSYBB350', 'HiggsSUSYBB400', 'HiggsSUSYBB450', 'HiggsSUSYBB500', 'HiggsSUSYBB600', 'HiggsSUSYBB700', 'HiggsSUSYBB900', 'HiggsSUSYBB1000', 'HiggsSUSYBB1200', 'HiggsSUSYBB1500', 'HiggsSUSYBB1600', 'HiggsSUSYBB1800', 'HiggsSUSYBB2000', 'HiggsSUSYBB2300', 'HiggsSUSYBB2600', 'HiggsSUSYBB2900', 'HiggsSUSYBB3200', 'HiggsSUSYGG80', 'HiggsSUSYGG90',
# 'HiggsSUSYGG100', 'HiggsSUSYGG110', 'HiggsSUSYGG120', 'HiggsSUSYGG130', 'HiggsSUSYGG140', 'HiggsSUSYGG160', 'HiggsSUSYGG180', 'HiggsSUSYGG200', 'HiggsSUSYGG250', 'HiggsSUSYGG300', 'HiggsSUSYGG400', 'HiggsSUSYGG450', 'HiggsSUSYGG500', 'HiggsSUSYGG600', 'HiggsSUSYGG700', 'HiggsSUSYGG800', 'HiggsSUSYGG900', 'HiggsSUSYGG1000', 'HiggsSUSYGG1200', 'HiggsSUSYGG1400', 'HiggsSUSYGG1500', 'HiggsSUSYGG1600', 'HiggsSUSYGG1800', 'HiggsSUSYGG2000', 'HiggsSUSYGG2300', 'HiggsSUSYGG2600', 'HiggsSUSYGG2900', 'HiggsSUSYGG3200'] # HiggsSUSYBB800, HiggsSUSYBB1400, HiggsSUSYGG350
# for name in mssm_names:
# samples_WH.append(SampleCfg(name=name.replace('HiggsSUSYBB', 'bbH').replace('HiggsSUSYGG', 'ggH'), dir_name=name,
# ana_dir=analysis_dir, tree_prod_name=tree_prod_name, xsec=1., sumweights=1., is_signal=True),)
samples_mc = samples_essential # + samples_WH
samples = samples_essential + samples_data
all_samples = samples_mc + samples_data
# -> Can add cross sections for samples either explicitly, or from file, or from cfg
# (currently taken from htt_common)
weighted_list = ['W', 'W1Jets', 'W2Jets', 'W3Jets', 'W4Jets']
for sample in samples_mc:
if sample.name not in weighted_list:
setSumWeights(sample)
# sampleDict = {s.name: s for s in all_samples}
sampleDict = {}
for s in all_samples:
sampleDict[s.name] = s
return samples_mc, samples_data, samples, all_samples, sampleDict