for i in [0,1,2]:
tags[i] = CutNode(Cuts.n_tags(i), graph, "%dt"%i, [tag], [])
#The primary MET/MTW cut node
met = Node(graph, "met", tag.children(), [])
mets = dict()
#No MET cut requirement
mets['off'] = CutNode(Cuts.no_cut, graph, "met__off", [met], [],
)
for met_syst in ["nominal", "up", "down"]:
mets['met_' + met_syst] = CutNode(
Cuts.met(met_syst),
graph, "met__met_" + met_syst,
[met], [],
filter_funcs=[lambda x: is_chan(x, 'ele')]
)
mets['mtw_' + met_syst] = CutNode(
Cuts.mt_mu(met_syst),
graph, "met__mtw_" + met_syst, [met], [],
filter_funcs=[lambda x: is_chan(x, 'mu')]
)
# purifications ---> cutbased, MVA
purification = Node(graph, "signalenr", met.children(), [])
purifications = dict()
purifications['cutbased'] = Node(graph, "cutbased", [purification], [])
purifications['mva'] = Node(graph, "mva", [purification], [])
cutlist['2j0t']=Cuts.n_jets(2)*Cuts.n_tags(0)
cutlist['3j0t']=Cuts.n_jets(3)*Cuts.n_tags(0)
cutlist['3j1t']=Cuts.n_jets(3)*Cuts.n_tags(1)
cutlist['3j2t']=Cuts.n_jets(3)*Cuts.n_tags(2)
#Needed for RMS cut validation
cutlist['presel_ele_no_rms']=Cuts.hlt_isoele*Cuts.lepton_veto*Cuts.pt_jet*Cuts.one_electron
cutlist['presel_mu_no_rms']=Cuts.hlt_isomu*Cuts.lepton_veto*Cuts.pt_jet*Cuts.one_muon
cutlist['presel_ele'] = cutlist['presel_ele_no_rms']*Cuts.rms_lj
cutlist['presel_mu'] = cutlist['presel_mu_no_rms']*Cuts.rms_lj
cutlist['nomet_ele']=cutlist['presel_ele']*Cuts.top_mass_sig*Cuts.eta_lj
cutlist['nomt_mu']=cutlist['presel_mu']*Cuts.top_mass_sig*Cuts.eta_lj
cutlist['noeta_ele']=cutlist['presel_ele']*Cuts.top_mass_sig*Cuts.met()
cutlist['noeta_mu']=cutlist['presel_mu']*Cuts.top_mass_sig*Cuts.mt_mu()
cutlist['final_ele']=cutlist['nomet_ele']*Cuts.met()
cutlist['final_mu']=cutlist['nomt_mu']*Cuts.mt_mu()
mva_var = Cuts.mva_vars
mva_var_qcd = Cuts.mva_vars_qcd
bdt = Cuts.mva_wps['bdt']
cutlist['bdt_mu_loose'] = Cuts.mt_mu()*Cut('%s>%f' % (mva_var['mu'],bdt['mu']['loose']))
cutlist['bdt_ele_loose'] = Cuts.met()*Cut('%s>%f' % (mva_var['ele'],bdt['ele']['loose']))
cutlist['bdt_mu_tight'] = Cuts.mt_mu()*Cut('%s>%f' % (mva_var['mu'],bdt['mu']['tight']))
cutlist['bdt_ele_tight'] = Cuts.met()*Cut('%s>%f' % (mva_var['ele'],bdt['ele']['tight']))
# Using MVA based QCD removal
mvaFileList['sig']['eval']= [
'T_t_ToLeptons',
'Tbar_t_ToLeptons'
]
mvaFileList['bg']['train']= [
'TTJets_MassiveBinDECAY',
'WJets_inclusive'
]
mvaFileList['bg']['eval']= [
'TTJets_FullLept',
'TTJets_SemiLept',
'W1Jets_exclusive',
'W2Jets_exclusive',
'W3Jets_exclusive',
'W4Jets_exclusive'
]
varList={}
varList['ele'] = [ 'top_mass','eta_lj','C','met','mt_el','mass_bj','mass_lj','el_pt','pt_bj' ]
varList['mu'] = [ 'top_mass','eta_lj','C','met','mt_mu','mass_bj','mass_lj','mu_pt','pt_bj' ]
varRank={}
varRank['ele'] = ['top_mass', 'C', 'eta_lj', 'el_pt', 'mt_el', 'pt_bj', 'mass_bj', 'met', 'mass_lj']
varRank['mu'] = ['top_mass', 'eta_lj', 'C', 'mu_pt', 'mt_mu', 'met', 'mass_bj', 'pt_bj', 'mass_lj']
from plots.common.cuts import Cut,Cuts
cuts = {}
cuts['ele'] = Cuts.n_jets(2)*Cuts.n_tags(1)*Cuts.hlt_isoele*Cuts.lepton_veto*Cuts.pt_jet*Cuts.one_electron*Cuts.rms_lj*Cuts.met()
cuts['mu'] = Cuts.n_jets(2)*Cuts.n_tags(1)*Cuts.hlt_isomu*Cuts.lepton_veto*Cuts.pt_jet*Cuts.one_muon*Cuts.rms_lj*Cuts.mt_mu()
