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TransferFunctionNanoAOD.py
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TransferFunctionNanoAOD.py
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import os.path
import sys
from bamboo.analysismodules import NanoAODModule, NanoAODHistoModule, DataDrivenBackgroundHistogramsModule
from bamboo import treefunctions as op
from bamboo.analysisutils import makeMultiPrimaryDatasetTriggerSelection
from bamboo.plots import Plot, EquidistantBinning, SummedPlot
sys.path.append(os.path.dirname(os.path.abspath(__file__))) # Add scripts in this directory
from BaseHHtobbWW import BaseNanoHHtobbWW
def plotNumber(contName,cont,sel,Nmax,xTitle):
return [Plot.make1D(contName,
op.rng_len(cont),
sel,
EquidistantBinning(Nmax,0.,Nmax),
xTitle=xTitle)]
def plotMatching(contName,cont,sel,partName):
plots = []
# plots.append(Plot.make1D(contName+"_deltaR",
# op.map(cont,lambda m : op.deltaR(m[0].p4,m[1].p4)),
# sel,
# EquidistantBinning(1000,0.,0.2),
# xTitle="#Delta R(%s_{gen},%s_{reco})"%(partName,partName)))
# plots.append(Plot.make1D(contName+"_deltaPtRel",
# op.map(cont,lambda m : (m[1].pt-m[0].pt)/(m[0].pt+m[1].pt)),
# sel,
# EquidistantBinning(1000,-1.,1.),
# xTitle="P_{T}(%s_{reco})-P_{T}(%s_{gen})/P_{T}(%s_{reco})+P_{T}(%s_{gen})"%(partName,partName,partName,partName)))
# plots.append(Plot.make2D(contName+"_Pt2D",
# [op.map(cont,lambda m : m[0].pt),op.map(cont,lambda m : m[1].pt)],
# sel,
# [EquidistantBinning(1000,0,1000),EquidistantBinning(1000,0,1000)],
# xTitle="P_{T}(gen)",
# yTitle="P_{T}(reco)"))
plots.append(Plot.make2D(contName+"_TF",
(op.map(cont,lambda m : m[0].p4.E()),op.map(cont,lambda m : m[1].p4.E()-m[0].p4.E())),
sel,
[EquidistantBinning(3000,0.,3000.),EquidistantBinning(8000,-1000.,1000.)],
xTitle="E^{parton}(e^{-})",
yTitle="#Delta E = E^{reco}(%s)-E^{parton}(%s)"%(partName,partName)))
return plots
def plotRecoForGen(sel,gen,reco,lambda_match,name):
n_reco = [op.select(reco, lambda r: op.switch(op.rng_len(gen)>i, lambda_match(gen[i],r), op.c_bool(False))) for i in range(10)]
plots = SummedPlot("n_reco_{}_per_gen".format(name),
[Plot.make1D("n_reco_{}_per_gen_{}".format(name,i),
op.rng_len(nre),
sel,
EquidistantBinning(10,0,10),
xTitle="N reco {} for gen {}".format(name,i))
for i,nre in enumerate(n_reco)],
xTitle = "N reco {} for each gen".format(name))
return plots
def plotFatjetMatching(cont,sel,sub1,sub2):
plots = []
plots.append(Plot.make1D(f"fatjet{sub1}{sub2}_sub1_dE",
op.map(cont,lambda m : m[2].subJet1.p4.E()-m[0].p4.E()),
sel,
EquidistantBinning(1000,-1000.,1000.),
xTitle=f"subJet1 {sub1} E - gen {sub1} E"))
plots.append(Plot.make2D(f"fatjet{sub1}{sub2}_sub1_TF",
[op.map(cont,lambda m : m[0].p4.E()),op.map(cont,lambda m : m[2].subJet1.p4.E()-m[0].p4.E())],
sel,
[EquidistantBinning(3000,0.,3000.),EquidistantBinning(8000,-1000.,1000.)],
xTitle="E^{{parton}}({sub1})",
yTitle=f"#Delta E = E^{{reco}}({sub1})-E^{{parton}}({sub1})"))
plots.append(Plot.make1D(f"fatjet{sub1}{sub2}_sub2_dE",
op.map(cont,lambda m : m[2].subJet2.p4.E()-m[1].p4.E()),
sel,
EquidistantBinning(1000,-1000.,1000.),
xTitle=f"subJet2 {sub2} E - gen {sub2} E"))
plots.append(Plot.make2D(f"fatjet{sub1}{sub2}_sub2_TF",
[op.map(cont,lambda m : m[1].p4.E()),op.map(cont,lambda m : m[2].subJet1.p4.E()-m[1].p4.E())],
sel,
[EquidistantBinning(3000,0.,3000.),EquidistantBinning(8000,-1000.,1000.)],
xTitle="E^{{parton}}({sub2})",
yTitle=f"#Delta E = E^{{reco}}({sub2})-E^{{parton}}({sub2})"))
plots.append(Plot.make2D(f"fatjet{sub1}{sub2}_dE2D",
[op.map(cont,lambda m : m[2].subJet1.p4.E()-m[0].p4.E()),op.map(cont,lambda m : m[2].subJet2.p4.E()-m[1].p4.E())],
sel,
[EquidistantBinning(1000,-1000.,1000.),EquidistantBinning(1000,-1000.,1000.)],
xTitle=f"subJet1 {sub1} E - gen {sub1} E",
yTitle=f"subJet2 {sub2} E - gen {sub2} E"))
return plots
def fatjetPlots(sel,fatjets,name):
plots = []
# plots.append(Plot.make2D(name+'_Pt2D',
# [op.map(fatjets, lambda fatjet : fatjet.subJet1.pt),op.map(fatjets, lambda fatjet : fatjet.subJet2.pt)],
# sel,
# [EquidistantBinning(1000,0.,1000.),EquidistantBinning(1000,0.,1000.)],
# xTitle = "subjet 1 P_{T}",
# yTitle = "subjet 2 P_{T}"))
plots.append(Plot.make2D(name+'_E2D',
[op.map(fatjets, lambda fatjet : fatjet.subJet1.p4.E()),op.map(fatjets, lambda fatjet : fatjet.subJet2.p4.E())],
sel,
[EquidistantBinning(1000,0.,1000.),EquidistantBinning(1000,0.,1000.)],
xTitle = "subjet 1 E",
yTitle = "subjet 2 E"))
# plots.append(Plot.make2D(name+'_partonflavour2D',
# [op.map(fatjets, lambda fatjet : fatjet.subJet1.partonFlavour),op.map(fatjets, lambda fatjet : fatjet.subJet2.partonFlavour)],
# sel,
# [EquidistantBinning(7,0.,6.),EquidistantBinning(7,0.,6.)],
# xTitle = "subjet 1 P_{T}",
# yTitle = "subjet 2 P_{T}"))
# plots.append(Plot.make2D(name+'_subjet1VSFatjet_E2D',
# [op.map(fatjets, lambda fatjet : fatjet.subJet1.p4.E()),op.map(fatjets, lambda fatjet : fatjet.p4.E())],
# sel,
# [EquidistantBinning(1000,0.,1000.),EquidistantBinning(1000,0.,1000.)],
# xTitle = "subjet 1 E",
# yTitle = "fatjet E"))
# plots.append(Plot.make2D(name+'_subjet2VSFatjet_E2D',
# [op.map(fatjets, lambda fatjet : fatjet.subJet2.p4.E()),op.map(fatjets, lambda fatjet : fatjet.p4.E())],
# sel,
# [EquidistantBinning(1000,0.,1000.),EquidistantBinning(1000,0.,1000.)],
# xTitle = "subjet 2 E",
# yTitle = "fatjet E"))
#
# plots.append(Plot.make2D(name+'_Eta2D',
# [op.map(fatjets, lambda fatjet : fatjet.subJet1.p4.eta()),op.map(fatjets, lambda fatjet : fatjet.subJet2.p4.eta())],
# sel,
# [EquidistantBinning(500,-2.5,2.5),EquidistantBinning(500,-2.5,2.5)],
# xTitle = "subjet 1 #eta",
# yTitle = "subjet 2 #eta"))
# plots.append(Plot.make2D(name+'_Phi2D',
# [op.map(fatjets, lambda fatjet : fatjet.subJet1.p4.phi()),op.map(fatjets, lambda fatjet : fatjet.subJet2.p4.phi())],
# sel,
# [EquidistantBinning(320,-3.2,3.2),EquidistantBinning(320,-3.2,3.2)],
# xTitle = "subjet 1 #phi",
# yTitle = "subjet 2 #phi"))
return plots
class TransferFunction(BaseNanoHHtobbWW,DataDrivenBackgroundHistogramsModule):
def definePlots(self, t, noSel, sample=None, sampleCfg=None):
noSel = super(TransferFunction,self).prepareObjects(t, noSel, sample, sampleCfg, 'DL')
noSel = self.beforeJetselection(noSel)
era = sampleCfg['era']
plots = []
if not self.is_MC:
return plots
lambda_is_matched = lambda lep : op.OR(lep.genPartFlav==1, # Prompt muon or electron
lep.genPartFlav==15) # From tau decay
#lep.genPartFlav==22) # From photon conversion (only available for electrons)
plots.append(Plot.make1D("totalWeight",
noSel.weight,
noSel,
EquidistantBinning(100,-int(10**5),int(10**5)),
xTitle="total weight"))
plots.append(Plot.make1D("genWeight",
t.genWeight,
noSel,
EquidistantBinning(100,-int(10**5),int(10**5)),
xTitle="gen weight"))
##########################################################
# Leptons #
##########################################################
#----- Gen particles -----#
gen_e = op.select(t.GenPart,lambda g : op.AND(op.abs(g.pdgId) == 11 ,
g.statusFlags & ( 0x1 << 13),
g.pt >= 10,
op.abs(g.eta)<2.5 ))
gen_m = op.select(t.GenPart,lambda g : op.AND(op.abs(g.pdgId) == 13 ,
g.statusFlags & ( 0x1 << 13),
g.pt >= 10,
op.abs(g.eta)<2.4 ))
#----- Reco particles -----#
lambda_reco_e = lambda el : op.AND(op.abs(el.pdgId) == 11 ,
el.pt >= 10 ,
op.abs(el.eta) <2.5,
lambda_is_matched(el))
lambda_reco_m = lambda mu : op.AND(op.abs(mu.pdgId) == 13 ,
mu.pt >= 10 ,
op.abs(mu.eta) < 2.4,
lambda_is_matched(mu))
reco_e = op.select(self.electronsFakeSel, lambda_reco_e)
reco_m = op.select(self.muonsFakeSel, lambda_reco_m)
#---- Matching -----#
lambda_lepton_match = lambda gen,reco : op.AND(op.deltaR(gen.p4,reco.p4) < 0.1 , (op.abs(gen.pt-reco.pt)/(gen.pt+reco.pt)) < 0.2 )
# reco_e_matched = op.select(reco_e, lambda re : op.rng_any(gen_e, lambda ge: lambda_lepton_match(ge,re)))
# reco_m_matched = op.select(reco_m, lambda rm : op.rng_any(gen_m, lambda gm: lambda_lepton_match(gm,rm)))
#match_e = op.combine((gen_e,reco_e), pred = lambda ge,re : re.idx == op.rng_min_element_by(reco_e_matched,lambda re_matched : op.deltaR(ge.p4,re_matched.p4)).idx)
#match_m = op.combine((gen_m,reco_m), pred = lambda gm,rm : rm.idx == op.rng_min_element_by(reco_m_matched,lambda rm_matched : op.deltaR(gm.p4,rm_matched.p4)).idx)
match_e = op.combine((gen_e,reco_e), pred=lambda_lepton_match)
match_m = op.combine((gen_m,reco_m), pred=lambda_lepton_match)
plots.extend(plotMatching("e",match_e,noSel,"e^{#pm}"))
plots.extend(plotMatching("m",match_m,noSel,"#mu^{#pm}"))
# plots.append(plotRecoForGen(noSel,gen_e,tight_e,lambda_lepton_match,"e_tight"))
# plots.append(plotRecoForGen(noSel,gen_e,tight_m,lambda_lepton_match,"m_tight"))
##########################################################
# Ak4 B jets #
##########################################################
#----- RecoJets -----#
recoJet_b = op.select(t.Jet, lambda j : op.AND(op.abs(j.partonFlavour) == 5,
j.pt>=20,
op.abs(j.eta)<2.4,
j.genJet.isValid))
#----- Parton -----#
gen_b = op.select(t.GenPart,lambda g : op.AND(op.abs(g.pdgId) == 5 ,
g.statusFlags & ( 0x1 << 13) ,
g.pt>=20,
op.abs(g.eta)<2.4))
#----- Matching -----#
lambda_jet_match = lambda gen,reco : op.AND(op.deltaR(gen.p4,reco.p4)<0.2)
reco_b_matched = op.select(recoJet_b, lambda jetb: op.rng_any(gen_b, lambda gb: lambda_jet_match(gb,jetb)))
match_b = op.combine((gen_b,recoJet_b), pred = lambda gb,jetb : jetb.idx == op.rng_min_element_by(reco_b_matched,lambda rb_matched : op.deltaR(gb.p4,rb_matched.p4)).idx)
plots.extend(plotMatching("ak4b",match_b,noSel,"b"))
##########################################################
# Ak4 C jets #
##########################################################
#----- RecoJets -----#
recoJet_c = op.select(t.Jet, lambda j : op.AND(op.abs(j.partonFlavour) == 4,
j.pt>=20,
op.abs(j.eta)<2.4,
j.genJet.isValid))
#----- Parton -----#
gen_c = op.select(t.GenPart,lambda g : op.AND(op.abs(g.pdgId) == 4 ,
g.statusFlags & ( 0x1 << 13) ,
g.pt>=20,
op.abs(g.eta)<2.4))
#----- Matching -----#
reco_c_matched = op.select(recoJet_c, lambda jetc: op.rng_any(gen_c, lambda gc: lambda_jet_match(gc,jetc)))
match_c = op.combine((gen_c,recoJet_c), pred = lambda gc,jetc : jetc.idx == op.rng_min_element_by(reco_c_matched,lambda rc_matched : op.deltaR(gc.p4,rc_matched.p4)).idx)
plots.extend(plotMatching("ak4c",match_c,noSel,"c"))
##########################################################
# Ak4 lightjets #
##########################################################
#----- RecoJets -----#
recoJet_l = op.select(t.Jet, lambda j : op.AND(op.OR(op.abs(j.partonFlavour) == 1,
op.abs(j.partonFlavour) == 2,
op.abs(j.partonFlavour) == 3),
j.pt>=20,
op.abs(j.eta)<2.4,
j.genJet.isValid))
#----- Parton -----#
gen_l = op.select(t.GenPart,lambda g : op.AND(op.OR(op.abs(g.pdgId) == 1,
op.abs(g.pdgId) == 2,
op.abs(g.pdgId) == 3),
g.statusFlags & ( 0x1 << 13) ,
g.pt>=20,
op.abs(g.eta)<2.4))
#----- Matching -----#
reco_l_matched = op.select(recoJet_l, lambda jetl: op.rng_any(gen_l, lambda gl: lambda_jet_match(gl,jetl)))
match_l = op.combine((gen_l,recoJet_l), pred = lambda gl,jetl : jetl.idx == op.rng_min_element_by(reco_l_matched,lambda rl_matched : op.deltaR(gl.p4,rl_matched.p4)).idx)
plots.extend(plotMatching("ak4l",match_l,noSel,"l"))
##########################################################
# Ak8 jets #
##########################################################
#----- RecoJets -----#
recoFatJet = op.select(t.FatJet, lambda j : op.AND(j.pt>=100,
op.abs(j.eta)<2.4,
op.AND(j.subJet1.isValid, j.subJet1.pt >= 20. , op.abs(j.subJet1.eta)<=2.4,
j.subJet2.isValid, j.subJet2.pt >= 20. , op.abs(j.subJet2.eta)<=2.4),
op.AND(j.msoftdrop >= 30, j.msoftdrop <= 210),
j.tau2/j.tau1 <= 0.75))
#plots.extend(fatjetPlots(noSel,recoFatJet,"fatjet"))
reco_subJet1_b_matched = op.select(recoFatJet, lambda fat: op.rng_any(gen_b, lambda gb: lambda_jet_match(gb,fat.subJet1)))
reco_subJet2_b_matched = op.select(recoFatJet, lambda fat: op.rng_any(gen_b, lambda gb: lambda_jet_match(gb,fat.subJet2)))
reco_subJet1_c_matched = op.select(recoFatJet, lambda fat: op.rng_any(gen_c, lambda gc: lambda_jet_match(gc,fat.subJet1)))
reco_subJet2_c_matched = op.select(recoFatJet, lambda fat: op.rng_any(gen_c, lambda gc: lambda_jet_match(gc,fat.subJet2)))
reco_subJet1_l_matched = op.select(recoFatJet, lambda fat: op.rng_any(gen_l, lambda gl: lambda_jet_match(gl,fat.subJet1)))
reco_subJet2_l_matched = op.select(recoFatJet, lambda fat: op.rng_any(gen_l, lambda gl: lambda_jet_match(gl,fat.subJet2)))
def makeFatjetMatch(gen1,gen2,recoFatJet):
return op.combine((gen1,gen2,recoFatJet), pred = lambda g1,g2,fat : op.AND(
fat.subJet1.idx == op.rng_min_element_by(reco_subJet1_b_matched,
lambda sub1_matched : op.deltaR(g1.p4,sub1_matched.p4)).idx,
fat.subJet2.idx == op.rng_min_element_by(reco_subJet2_b_matched,
lambda sub2_matched : op.deltaR(g2.p4,sub2_matched.p4)).idx))
match_fat_bb = makeFatjetMatch(gen_b,gen_b,recoFatJet)
match_fat_bc = makeFatjetMatch(gen_b,gen_c,recoFatJet)
match_fat_bl = makeFatjetMatch(gen_b,gen_l,recoFatJet)
match_fat_cb = makeFatjetMatch(gen_c,gen_b,recoFatJet)
match_fat_cc = makeFatjetMatch(gen_c,gen_c,recoFatJet)
match_fat_cl = makeFatjetMatch(gen_c,gen_l,recoFatJet)
match_fat_lb = makeFatjetMatch(gen_l,gen_b,recoFatJet)
match_fat_lc = makeFatjetMatch(gen_l,gen_c,recoFatJet)
match_fat_ll = makeFatjetMatch(gen_l,gen_l,recoFatJet)
# match_fat_bb = op.combine((gen_b,gen_b,recoFatJet), pred = lambda g1,g2,fat : op.AND(
# fat.subJet1.idx == op.rng_min_element_by(reco_subJet1_b_matched,
# lambda sub1_matched : op.deltaR(gb1.p4,sub1_matched.p4)).idx,
# fat.subJet2.idx == op.rng_min_element_by(reco_subJet2_b_matched,
# lambda sub2_matched : op.deltaR(gb2.p4,sub2_matched.p4)).idx))
# match_fat_bc = op.combine((gen_b,gen_b,recoFatJet), pred = lambda gb1,gb2,fat : op.AND(
# fat.subJet1.idx == op.rng_min_element_by(reco_subJet1_b_matched,
# lambda sub1_matched : op.deltaR(gb1.p4,sub1_matched.p4)).idx,
# fat.subJet2.idx == op.rng_min_element_by(reco_subJet2_b_matched,
# lambda sub2_matched : op.deltaR(gb2.p4,sub2_matched.p4)).idx))
plots.extend(plotFatjetMatching(match_fat_bb,noSel,'b','b'))
plots.extend(plotFatjetMatching(match_fat_bc,noSel,'b','c'))
plots.extend(plotFatjetMatching(match_fat_bl,noSel,'b','l'))
plots.extend(plotFatjetMatching(match_fat_cb,noSel,'c','b'))
plots.extend(plotFatjetMatching(match_fat_cc,noSel,'c','c'))
plots.extend(plotFatjetMatching(match_fat_cl,noSel,'c','l'))
plots.extend(plotFatjetMatching(match_fat_bb,noSel,'l','b'))
plots.extend(plotFatjetMatching(match_fat_bc,noSel,'l','c'))
plots.extend(plotFatjetMatching(match_fat_bl,noSel,'l','l'))
return plots