def rcPre2Loose(t,cuts):
ops = config.logicOperators()
rcjets = []
for b,pt in enumerate(t.reclusteredW_pt):
rcjet = Py4Vector()
rcjet.SetPtEtaPhiE(pt,t.reclusteredW_eta[b],t.reclusteredW_phi[b],t.reclusteredW_e[b])
rcPt = cuts['reclustered']['whad_pt']['value']
rcPt_cond = cuts['reclustered']['whad_pt']['cond']
Ms = cuts['reclustered']['whad_mwin']['value'][0] #only 1 bin
if ops[rcPt_cond](rcjet.Pt,rcPt) and Ms[0] <= rcjet.M <= Ms[1]:
subpt = []; subeta = []
subphi = []; sube = []
subm = []
nsub = t.reclusteredW_nsub[b]
# for n in range(nsub):
# subpt.append(t.reclusteredWsub_pt[b][n])
# subeta.append(t.reclusteredWsub_eta[b][n])
# subphi.append(t.reclusteredWsub_phi[b][n])
# sube.append(t.reclusteredWsub_e[b][n])
# subm.append(t.reclusteredWsub_m[b][n])
rcjet.SetRTSubJet(nsub,subpt,subeta,subphi,sube,subm)
rcjets.append(rcjet)
logging.info(" Setup Re-clustered Jets.")
return rcjets
def getWcandidate(candidates,num,cond):
"""
:: DEPRECATED :: No longer used -- now use W-tagging information
Choose the highest pT (no b-tagging stuff) jet(s)
@param candidates = List of hadronic W candidates
num = Number of hadronic W's required (1,2,3,etc.)
cond = Conditional for number of hadronic W's (==,>,<,>=,<=,etc.)
"""
import pyMiniSL.config as config
ops = config.logicOperators()
wcandidates = []
if ops[cond](len(candidates),num):
wcandidates = candidates
return wcandidates
if cond == '==':
if len(candidates) > num:
for n in range(num):
wcandidates.append(candidates[n])
elif len(boostedWcands) < num:
logging.error(" Too few W candidates.")
wcandidates = []
else:
logging.error(" No other condidtionals supported")
logging.error(" Please try '=='")
wcandidates = []
return wcandidates
return wcandidates
def __init__(self,cfg_filename):
"""
Init
@param cfg_filename Filename of the config file ("PyUser.ini")
"""
self.p_settings = info.getConfigSettings(cfg_filename)
self.p_cfg_name = 'configuration'
self.ops = config.logicOperators()
self.key2attr = info.key2attr()
self.obj2ttree = info.obj2ttree()
self.truthObj = info.truthObject()
self.nonGeVvars = info.nonGeVvariables() # variables that aren't in GeV (for scaling plots)
self.GeV = 1000.
def __init__(self,parser,cuts):
"""Initialize the class by loading the config file."""
self.cuts = cuts # same for all events
self.parser = parser # same for all events
self.lvl = ''
self.ops = config.logicOperators()
self.name2attr = {'dr':'DeltaR',\
'dp':'DeltaPhi',\
'dm':'DeltaM'}
self.op_keys = self.name2attr.keys()+['min','max']
self.key2attr = info.key2attr() # dictionary of object attributes and text file keys
self.vector_objects = info.listed_objects() # list of objects that are stored as lists in event
self.unique_objects = ['ht','met+mtw','nbtags','mass_lb','vlq_evtype',\
'A_mass','A_dr','A_distance'] # simple definitions
return
def fjPre2Loose(t,cuts):
ops = config.logicOperators()
boostedWcands = []
whad_n_cond = cuts['inclusive']['whad_n']['cond']
whad_n = cuts['inclusive']['whad_n']['value']
## Check for boosted W first
logging.debug(' Boosted Event')
for b,pt in enumerate(t.boostedW_pt):
fatjet = Py4Vector()
fatjet.SetPtEtaPhiE(pt,t.boostedW_eta[b],t.boostedW_phi[b],t.boostedW_e[b])
skipThisFatJet=False
for jj,smalljet in enumerate(t.jet_pt):
smalljet = Py4Vector()
smalljet.SetPtEtaPhiE(t.jet_pt[jj],t.jet_eta[jj],t.jet_phi[jj],t.jet_e[jj])
if skipThisFatJet: continue
setattr(fatjet,'isSmoothTop50',t.boostedW_isSmoothTop50[b])
setattr(fatjet,'isSmoothTop80',t.boostedW_isSmoothTop80[b])
setattr(fatjet,'isPtLowTop50',t.boostedW_isPtLowTop50[b])
setattr(fatjet,'isPtHighTop50',t.boostedW_isPtHighTop50[b])
setattr(fatjet,'isPtLowTop80',t.boostedW_isPtLowTop80[b])
setattr(fatjet,'isPtHighTop80',t.boostedW_isPtHighTop80[b])
setattr(fatjet,'isWmed',t.boostedW_isWmed[b])
setattr(fatjet,'isWtight',t.boostedW_isWtight[b])
setattr(fatjet,'isZmed',t.boostedW_isZmed[b])
setattr(fatjet,'isZtight',t.boostedW_isZtight[b])
setattr(fatjet,'isGood',t.boostedW_isGood[b])
# Energy Correlations
setattr(fatjet,'C2',t.boostedW_C2[b])
setattr(fatjet,'D2',t.boostedW_D2[b])
# Splitting Scales
setattr(fatjet,'d12',t.boostedW_d12[b])
setattr(fatjet,'d23',t.boostedW_d23[b])
# N-subjettiness
setattr(fatjet,'tau1',t.boostedW_tau1[b])
setattr(fatjet,'tau2',t.boostedW_tau2[b])
setattr(fatjet,'tau3',t.boostedW_tau3[b])
setattr(fatjet,'tau21',t.boostedW_tau21[b])
setattr(fatjet,'tau32',t.boostedW_tau32[b])
setattr(fatjet,'tau1_wta',t.boostedW_tau1_wta[b])
setattr(fatjet,'tau2_wta',t.boostedW_tau2_wta[b])
setattr(fatjet,'tau3_wta',t.boostedW_tau3_wta[b])
setattr(fatjet,'tau21_wta',t.boostedW_tau21_wta[b])
setattr(fatjet,'tau32_wta',t.boostedW_tau32_wta[b])
## Re-structure the cuts to be easier to access
Pts = cuts['boosted']['whad_pt']['value'] # bin edges
Ms = cuts['boosted']['whad_mwin']['value'] # mass windows/bin
D2s = cuts['boosted']['whad_d2']['value'] # single values/bin
D2s_cond = cuts['boosted']['whad_d2']['cond']
nbins = len(Pts)-1
logging.debug(' Fat Jet pT,M,d2 = {0},{1},{2}'.format(fatjet.Pt(),fatjet.M(), fatjet.D2))
logging.debug(' pT bin edges: {0}'.format(Pts))
logging.debug(' D2 cut values: {0}'.format(D2s))
logging.debug(' Mass Window: {0}'.format(Ms))
if fatjet.Pt() < Pts[0]:
continue
for bin in range(nbins):
if Pts[bin] < fatjet.Pt() < Pts[bin+1]:
WmassMin = Ms[bin][0]
WmassMax = Ms[bin][1]
if WmassMin <= fatjet.M() <= WmassMax and ops[D2s_cond](fatjet.D2,D2s[bin]):
boostedWcands.append(fatjet)
break
logging.debug(' Fat Jet Loop')
logging.debug(' Number of Fat Jets: {0}'.format(len(boostedWcands)))
if boostedWcands:
boostedWcands = vlq.getWcandidate(boostedWcands,whad_n,whad_n_cond)
logging.info(" Fat Jet Whad Candidate. ")
return boostedWcands
