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TWanalyzer.py~
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TWanalyzer.py~
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#! /usr/bin/env python
###################################################################
## ##
## Name: TWkinematics.py ##
## Author: Kevin Nash ##
## Date: 6/5/2012 ##
## Purpose: This program performs the main analysis. ##
## It takes the tagrates created by ##
## TWrate_Maker.py stored in fitdata, and uses ##
## them to weigh pre b tagged samples to create a ##
## QCD background estimate along with the full event ##
## selection to product Mtw inputs to Theta ##
## ##
###################################################################
import os
import glob
import math
from math import sqrt
#import quickroot
#from quickroot import *
import ROOT
from ROOT import *
import sys
#from DataFormats.FWLite import Events, Handle
from optparse import OptionParser
parser = OptionParser()
parser.add_option('-s', '--set', metavar='F', type='string', action='store',
default = 'data',
dest = 'set',
help = 'data or ttbar')
parser.add_option('-x', '--pileup', metavar='F', type='string', action='store',
default = 'on',
dest = 'pileup',
help = 'If not data do pileup reweighting?')
parser.add_option('-n', '--num', metavar='F', type='string', action='store',
default = 'all',
dest = 'num',
help = 'job number')
parser.add_option('-y', '--modmass', metavar='F', type='string', action='store',
default = 'nominal',
dest = 'modmass',
help = 'nominal up or down')
parser.add_option('-j', '--jobs', metavar='F', type='string', action='store',
default = '1',
dest = 'jobs',
help = 'number of jobs')
parser.add_option('-t', '--tname', metavar='F', type='string', action='store',
default = 'HLT_PFHT900,HLT_AK8PFJet450',
dest = 'tname',
help = 'trigger name')
parser.add_option('-J', '--JES', metavar='F', type='string', action='store',
default = 'nominal',
dest = 'JES',
help = 'nominal, up, or down')
parser.add_option('-R', '--JER', metavar='F', type='string', action='store',
default = 'nominal',
dest = 'JER',
help = 'nominal, up, or down')
parser.add_option('-m', '--modulesuffix', metavar='F', type='string', action='store',
default = 'none',
dest = 'modulesuffix',
help = 'ex. PtSmearUp')
parser.add_option('-g', '--grid', metavar='F', type='string', action='store',
default = 'off',
dest = 'grid',
help = 'running on grid off or on')
parser.add_option('-u', '--ptreweight', metavar='F', type='string', action='store',
default = 'none',
dest = 'ptreweight',
help = 'on or off')
parser.add_option('-p', '--pdfweights', metavar='F', type='string', action='store',
default = 'nominal',
dest = 'pdfweights',
help = 'nominal, up, or down')
parser.add_option('-z', '--pdfset', metavar='F', type='string', action='store',
default = 'cteq66',
dest = 'pdfset',
help = 'pdf set')
parser.add_option('--printEvents', metavar='F', action='store_true',
default=False,
dest='printEvents',
help='Print events that pass selection (run:lumi:event)')
parser.add_option('-c', '--cuts', metavar='F', type='string', action='store',
default = 'default',
dest = 'cuts',
help = 'Cuts type (ie default, rate, etc)')
parser.add_option('-v', '--var', metavar='F', type='string', action='store',
default = 'analyzer',
dest = 'var',
help = 'anaylzer or kinematics')
parser.add_option('-S', '--split', metavar='F', type='string', action='store',
default = 'event',
dest = 'split',
help = 'split by event of file') # file splitting doesn't work with ttrees
parser.add_option('-A', '--Alphabet', metavar='F', type='string', action='store',
default = 'off',
dest = 'Alphabet',
help = 'turn alphabet on or off')
parser.add_option('-r', '--rate', metavar='F', type='string', action='store',
default = 'tpt',
dest = 'rate',
help = 'tpt, Mt, Mtw')
(options, args) = parser.parse_args()
if (options.set.find('QCD') != -1):
setstr = 'QCD'
else:
setstr = 'data'
print "Options summary"
print "=================="
for opt,value in options.__dict__.items():
#print str(option)+ ": " + str(options[option])
print str(opt) +': '+ str(value)
print "=================="
print ""
di = ""
if options.grid == 'on':
di = "tardir/"
sys.path.insert(0, 'tardir/')
gROOT.Macro(di+"rootlogon.C")
import Bstar_Functions
from Bstar_Functions import *
tname = options.tname.split(',')
tnamestr = ''
for iname in range(0,len(tname)):
tnamestr+=tname[iname]
if iname!=len(tname)-1:
tnamestr+='OR'
#trig='none'
#if options.set!= 'data' and options.tname!='none':
# if options.tname=='HLT_PFHT800_v2ORHLT_AK8DiPFJet280_200_TrimMass30_BTagCSV0p45_v3':
# trig = 'nominal'
# elif options.tname!= []:
# trig = 'tnamestr'
if tnamestr=='HLT_PFHT900ORHLT_AK8PFJet450':
tnameformat='nominal'
elif tnamestr=='':
tnameformat='none'
else:
tnameformat=tnamestr
pie = math.pi
#Load up cut values based on what selection we want to run
Cuts = LoadCuts(options.cuts)
wpt = Cuts['wpt']
tpt = Cuts['tpt']
dy = Cuts['dy']
tmass = Cuts['tmass']
tau32 = Cuts['tau32']
tau21 = Cuts['tau21']
sjbtag = Cuts['sjbtag']
wmass = Cuts['wmass']
eta1 = Cuts['eta1']
eta2 = Cuts['eta2']
eta = Cuts['eta']
Cons = LoadConstants()
lumi = Cons['lumi']
Lumi = str(lumi/1000)+'fb'
#For large datasets we need to parallelize the processing
jobs=int(options.jobs)
if jobs != 1:
num=int(options.num)
jobs=int(options.jobs)
print "Running over " +str(jobs)+ " jobs"
print "This will process job " +str(num)
else:
print "Running over all events"
#This section defines some strings that are used in naming the output files
mod = ''
post = ''
if options.JES!='nominal':
mod = mod + 'JES_' + options.JES
post='jes'+options.JES
if options.JER!='nominal':
mod = mod + 'JER_' + options.JER
post='jer'+options.JER
pstr = ""
if options.pdfweights!="nominal":
print "using pdf uncertainty"
pstr = "_pdf_"+options.pdfset+"_"+options.pdfweights
pustr = ""
if options.pileup=='off':
pustr = "pileup_unweighted"
if options.pileup=='up':
pustr = "pileup_up"
if options.pileup=='down':
pustr = "pileup_down"
mod = mod+pustr
if mod == '':
mod = options.modulesuffix
print "mod = " + mod
mmstr = ""
if options.modmass!="nominal":
print "using modm uncertainty"
mmstr = "_modm_"+options.modmass
#------------------------------------------------------------------------
#Based on what set we want to analyze, we find all Ntuple root files
if options.grid == "on":
mainDir = "/uscms_data/d3/lcorcodi/BStar13TeV/CMSSW_7_4_1/src/BStar13TeV/TTrees/"
else:
mainDir='TTrees/'
file = TFile(mainDir + "TWtreefile_"+options.set+"_Trigger_"+tnameformat+"_"+mod+pstr+".root")
tree = file.Get("Tree")
if (options.set.find('ttbar') != -1) or (options.set.find('singletop') != -1):
settype = 'ttbar'
elif (options.set.find('QCD') != -1):
settype ='ttbar'
run_b_SF = False
else :
settype = options.set
print 'The type of set is ' + settype
#---------------Modmass file if you dont want alphabet-----------------------
if options.Alphabet != "on":
ModFile = ROOT.TFile(di+"ModMassFile_rate_"+options.cuts+".root")
ModPlot = ModFile.Get("rtmass")
ModFitParams = open(di+'fitdata/ModMass_pol3_PSET_rate_'+options.cuts+'.txt')
ModFitParams.seek(0)
ModFit = TF1("ModFit",'pol3',tmass[0],tmass[1])
ModFitParams2 = ModFitParams.read()
for i in range(0,4):
ModFit.SetParameter(i,float(ModFitParams2.split('\n')[i]) )
# ModFile = ROOT.TFile(di+"ModMassFile_"+options.cuts+".root")
# ModPlot = ModFile.Get("rtmass")
if options.set != 'data':
#Load up scale factors (to be used for MC only)
TrigFile = TFile(di+"Triggerweight_data80X.root")
TrigPlot = TrigFile.Get("TriggerWeight_"+tnamestr+"_pre_HLT_PFHT475_v3")
PileFile = TFile(di+"PileUp_Ratio_"+settype+".root")
if options.pileup=='up':
PilePlot = PileFile.Get("Pileup_Ratio_up")
elif options.pileup=='down':
PilePlot = PileFile.Get("Pileup_Ratio_down")
else:
PilePlot = PileFile.Get("Pileup_Ratio")
nevHisto = file.Get("nev")
B2Gnev = nevHisto.Integral()/jobs
# For some reason, the above line makes python forget what `tpt` is so redifining
tpt = Cuts['tpt']
#---------------------------------------------------------------------------------------------------------------------#
var = ""
if options.var == "kinematics":
var = "_kin"
if jobs != 1:
f = TFile( "TWanalyzer"+options.set+"_Trigger_"+tnameformat+"_"+mod+pstr+mmstr+"_job"+options.num+"of"+options.jobs+"_PSET_"+options.cuts+var+".root", "recreate" )
else:
f = TFile( "TWanalyzer"+options.set+"_Trigger_"+tnameformat+"_"+mod+pstr+mmstr+"_PSET_"+options.cuts+var+".root", "recreate" )
#Load up the average t-tagging rates -- Takes parameters from text file and makes a function
#CHANGE BACK
if options.Alphabet == "on":
TTR = TTR_Init('QUAD',options.cuts,setstr,options.rate,di)
TTR_errUp = TTR_Init('QUAD_errUp',options.cuts,setstr,options.rate,di)
TTR_errDown = TTR_Init('QUAD_errDown',options.cuts,setstr,options.rate,di)
fittitles = ["QUAD"]
fits = []
for fittitle in fittitles:
fits.append(TTR_Init(fittitle,options.cuts,setstr,options.rate,di))
elif options.Alphabet == "off":
TTR = TTR_Init('Bifpoly','rate_'+options.cuts,setstr,options.rate,di)
TTR_err = TTR_Init('Bifpoly_err','rate_'+options.cuts,setstr,options.rate,di)
#TTR = TTR_Init('Bifpoly',options.cuts,setstr,options.rate,di)
#TTR_err = TTR_Init('Bifpoly_err',options.cuts,setstr,options.rate,di)
fittitles = ["pol0","pol2","pol3","FIT","Bifpoly","expofit"]
fits = []
for fittitle in fittitles:
fits.append(TTR_Init(fittitle,'rate_'+options.cuts,setstr,options.rate,di))
#fits.append(TTR_Init(fittitle,options.cuts,setstr,options.rate,di))
TagFile1 = TFile(di+"Tagrate"+setstr+"2D_rate_"+options.cuts+".root")
#TagFile1 = TFile(di+"Tagrate"+setstr+"2D_"+options.cuts+".root")
TagPlot2de1= TagFile1.Get("tagrateeta1")
TagPlot2de2= TagFile1.Get("tagrateeta2")
print "Creating histograms"
f.cd()
#---------------------------------------------------------------------------------------------------------------------#
Mtw = TH1F("Mtw", "mass of tw", 140, 500, 4000 )
nev = TH1F("nev", "nev", 1, 0, 1 )
Mtwtrigup = TH1F("Mtwtrigup", "mass of tw trig up", 140, 500, 4000 )
Mtwtrigdown = TH1F("Mtwtrigdown", "mass of tw trig up", 140, 500, 4000 )
MtwTup = TH1F("MtwTup", "mass of tw top tag SF up", 140, 500, 4000 )
MtwTdown = TH1F("MtwTdown", "mass of tw top tag SF down", 140, 500, 4000 )
Nevents = TH1F("Nevents", "mass of tb", 5, 0., 5. )
QCDbkg= TH1F("QCDbkg", "QCD background estimate", 140, 500, 4000 )
QCDbkgh= TH1F("QCDbkgh", "QCD background estimate up error", 140, 500, 4000 )
QCDbkgl= TH1F("QCDbkgl", "QCD background estimate down error", 140, 500, 4000 )
if options.Alphabet == "off":
QCDbkg2D= TH1F("QCDbkg2D", "QCD background estimate 2d error", 140, 500, 4000 )
QCDbkg2Dup= TH1F("QCDbkg2Dup", "QCD background estimate 2d error", 140, 500, 4000 )
QCDbkg2Ddown= TH1F("QCDbkg2Ddown", "QCD background estimate 2d error", 140, 500, 4000 )
MtStack = TH1F("MtStack", "top candidate mass for stack", 100, 0, 500 )
QCDbkgMtStack = TH1F("QCDbkgMtStack", "QCD background for top mass", 100, 0, 500 )
masswHist = TH1F("Massw", "Massw", 25, 0, 5 )
masswHist.Sumw2()
Mtw.Sumw2()
Mtwtrigup.Sumw2()
Mtwtrigdown.Sumw2()
MtwTup.Sumw2()
MtwTdown.Sumw2()
QCDbkg.Sumw2()
QCDbkgh.Sumw2()
QCDbkgl.Sumw2()
MtStack.Sumw2()
QCDbkgMtStack.Sumw2()
Mtw_cut1 = TH1F("Mtw_cut1", "mass of tw after wpt cut", 140, 500, 4000)
Mtw_cut2 = TH1F("Mtw_cut2", "mass of tw after tpt cut", 140, 500, 4000)
Mtw_cut3 = TH1F("Mtw_cut3", "mass of tw after dy cut", 140, 500, 4000)
Mtw_cut4 = TH1F("Mtw_cut4", "mass of tw after tmass cut", 140, 500, 4000)
Mtw_cut5 = TH1F("Mtw_cut5", "mass of tw after wmass cut", 140, 500, 4000)
Mtw_cut6 = TH1F("Mtw_cut6", "mass of tw after tau21 cut", 140, 500, 4000)
Mtw_cut7 = TH1F("Mtw_cut7", "mass of tw after eta1 cut", 140, 500, 4000)
Mtw_cut8 = TH1F("Mtw_cut8", "mass of tw after eta2 cut", 140, 500, 4000)
Mtw_cut9 = TH1F("Mtw_cut9", "mass of tw after sjbtag cut", 140, 500, 4000)
Mtw_cut10 = TH1F("Mtw_cut10", "mass of tw after tau32 cut", 140, 500, 4000)
EtaTop = TH1F("EtaTop", "Top Candidate eta", 12, -2.4, 2.4 )
EtaW = TH1F("EtaW", "W Candidate eta", 12, -2.4, 2.4 )
PtTop = TH1F("PtTop", "Top Candidate pt (GeV)", 50, 450, 1500 )
PtW = TH1F("PtW", "W Candidate pt (GeV)", 50, 370, 1430 )
PtTopW = TH1F("PtTopW", "pt of tw system", 35, 0, 700 )
PhiTop = TH1F("PhiTop", "Top Candidate Phi (rad)", 12, -pie, pie )
PhiW = TH1F("PhiW", "Top Candidate Phi (rad)", 12, -pie, pie )
dPhi = TH1F("dPhi", "delta theat between Top and W Candidates", 12, 2.2, pie )
TopMass = TH1F("TopMass", "Top mass", 10,0,500)
Nsubjetiness32 = TH1F("Nsubjetiness32", "Nsubjetiness", 8,0,1.6)
Nsubjetiness21 = TH1F("Nsubjetiness21", "Nsubjetiness", 8,0,1.6)
deltaY = TH1F("deltaY", "delta y between Top and b candidates", 10,0,5)
CSV = TH1F("CSV", "CSV", 10,0,1)
CSVMax = TH1F("CSVMax", "CSV maximum", 10,0,1)
Btag = TH1F("Btag", "Tagged bs", 4,0,4)
Btagmax = TH1F("Btagmax", "Max value of b disc", 30,0,1)
Btruth = TH1F("Btruth", "MC Truth for bs", 4,0,4)
JetsVsBtag = TH2F("JetsVsBtag", "Jets vs Btag", 4,0,4, 30,0,30)
QCDbkgET = TH1F("QCDbkgET", "QCD background estimate eta top", 12, -2.4, 2.4 )
QCDbkgETh= TH1F("QCDbkgETh", "QCD background estimate up error", 12, -2.4, 2.4 )
QCDbkgETl= TH1F("QCDbkgETl", "QCD background estimate down error", 12, -2.4, 2.4 )
if options.Alphabet == "off":
QCDbkgET2D= TH1F("QCDbkgET2D", "QCD background estimate 2d error", 12, -2.4, 2.4 )
QCDbkgET2Dup= TH1F("QCDbkgET2Dup", "QCD background estimate 2d error", 12, -2.4, 2.4 )
QCDbkgET2Ddown= TH1F("QCDbkgET2Ddown", "QCD background estimate 2d error", 12, -2.4, 2.4 )
QCDbkgEW = TH1F("QCDbkgEW", "QCD background estimate eta w", 12, -2.4, 2.4 )
QCDbkgEWh= TH1F("QCDbkgEWh", "QCD background estimate up error", 12, -2.4, 2.4 )
QCDbkgEWl= TH1F("QCDbkgEWl", "QCD background estimate down error", 12, -2.4, 2.4 )
if options.Alphabet == "off":
QCDbkgEW2D= TH1F("QCDbkgEW2D", "QCD background estimate 2d error", 12, -2.4, 2.4 )
QCDbkgEW2Dup= TH1F("QCDbkgEW2Dup", "QCD background estimate 2d error", 12, -2.4, 2.4 )
QCDbkgEW2Ddown= TH1F("QCDbkgEW2Ddown", "QCD background estimate 2d error", 12, -2.4, 2.4 )
QCDbkgPT = TH1F("QCDbkgPT", "QCD background estimate pt top", 50, 450, 1500 )
QCDbkgPTh= TH1F("QCDbkgPTh", "QCD background estimate up error", 50, 450, 1500 )
QCDbkgPTl= TH1F("QCDbkgPTl", "QCD background estimate down error", 50, 450, 1500 )
if options.Alphabet == "off":
QCDbkgPT2D= TH1F("QCDbkgPT2D", "QCD background estimate 2d error", 50, 450, 1500 )
QCDbkgPT2Dup= TH1F("QCDbkgPT2Dup", "QCD background estimate 2d error", 50, 450, 1500 )
QCDbkgPT2Ddown= TH1F("QCDbkgPT2Ddown", "QCD background estimate 2d error", 50, 450, 1500 )
QCDbkgPW = TH1F("QCDbkgPW", "QCD background estimate pt W", 50, 370, 1430 )
QCDbkgPWh= TH1F("QCDbkgPWh", "QCD background estimate up error", 50, 370, 1430 )
QCDbkgPWl= TH1F("QCDbkgPWl", "QCD background estimate down error", 50, 370, 1430 )
if options.Alphabet == "off":
QCDbkgPW2D= TH1F("QCDbkgPW2D", "QCD background estimate 2d error", 50, 370, 1430 )
QCDbkgPW2Dup= TH1F("QCDbkgPW2Dup", "QCD background estimate 2d error", 50, 370, 1430 )
QCDbkgPW2Ddown= TH1F("QCDbkgPW2Ddown", "QCD background estimate 2d error", 50, 370, 1430 )
QCDbkgPTW = TH1F("QCDbkgPTW", "QCD background estimate pt top+w", 35, 0, 700 )
QCDbkgPTWh= TH1F("QCDbkgPTWh", "QCD background estimate up error", 35, 0, 700 )
QCDbkgPTWl= TH1F("QCDbkgPTWl", "QCD background estimate down error", 35, 0, 700 )
if options.Alphabet == "off":
QCDbkgPTW2D= TH1F("QCDbkgPTW2D", "QCD background estimate 2d error", 35, 0, 700 )
QCDbkgPTW2Dup= TH1F("QCDbkgPTW2Dup", "QCD background estimate 2d error", 35, 0, 700 )
QCDbkgPTW2Ddown= TH1F("QCDbkgPTW2Ddown", "QCD background estimate 2d error", 35, 0, 700 )
QCDbkgPhT = TH1F("QCDbkgPhT", "QCD background estimate phi top", 12, -pie, pie )
QCDbkgPhTh= TH1F("QCDbkgPhTh", "QCD background estimate up error", 12, -pie, pie )
QCDbkgPhTl= TH1F("QCDbkgPhTl", "QCD background estimate down error", 12, -pie, pie )
if options.Alphabet == "off":
QCDbkgPhT2D= TH1F("QCDbkgPhT2D", "QCD background estimate 2d error", 12, -pie, pie )
QCDbkgPhT2Dup= TH1F("QCDbkgPhT2Dup", "QCD background estimate 2d error", 12, -pie, pie )
QCDbkgPhT2Ddown= TH1F("QCDbkgPhT2Ddown", "QCD background estimate 2d error", 12, -pie, pie )
QCDbkgPhW = TH1F("QCDbkgPhW", "QCD background estimate phi w", 12, -pie, pie )
QCDbkgPhWh= TH1F("QCDbkgPhWh", "QCD background estimate up error", 12, -pie, pie )
QCDbkgPhWl= TH1F("QCDbkgPhWl", "QCD background estimate down error", 12, -pie, pie )
if options.Alphabet == "off":
QCDbkgPhW2D= TH1F("QCDbkgPhW2D", "QCD background estimate 2d error", 12, -pie, pie )
QCDbkgPhW2Dup= TH1F("QCDbkgPhW2Dup", "QCD background estimate 2d error", 12, -pie, pie )
QCDbkgPhW2Ddown= TH1F("QCDbkgPhW2Ddown", "QCD background estimate 2d error", 12, -pie, pie )
QCDbkgdPhi = TH1F("QCDbkgdPhi", "QCD background estimate delta phi", 12, 2.2, pie )
QCDbkgdPhih= TH1F("QCDbkgdPhih", "QCD background estimate up error", 12, 2.2, pie )
QCDbkgdPhil= TH1F("QCDbkgdPhil", "QCD background estimate down error", 12, 2.2, pie )
if options.Alphabet == "off":
QCDbkgdPhi2D= TH1F("QCDbkgdPhi2D", "QCD background estimate 2d error", 12, 2.2, pie )
QCDbkgdPhi2Dup= TH1F("QCDbkgdPhi2Dup", "QCD background estimate 2d error", 12, 2.2, pie )
QCDbkgdPhi2Ddown= TH1F("QCDbkgdPhi2Ddown", "QCD background estimate 2d error", 12, 2.2, pie )
Mtw_cut1.Sumw2()
Mtw_cut2.Sumw2()
Mtw_cut3.Sumw2()
Mtw_cut4.Sumw2()
Mtw_cut5.Sumw2()
Mtw_cut6.Sumw2()
Mtw_cut7.Sumw2()
Mtw_cut8.Sumw2()
Mtw_cut9.Sumw2()
Mtw_cut10.Sumw2()
EtaTop.Sumw2()
EtaW.Sumw2()
PtTop.Sumw2()
PtW.Sumw2()
PtTopW.Sumw2()
PhiTop.Sumw2()
PhiW.Sumw2()
dPhi.Sumw2()
TopMass.Sumw2()
Nsubjetiness32.Sumw2()
Nsubjetiness21.Sumw2()
deltaY.Sumw2()
CSV.Sumw2()
CSVMax.Sumw2()
Btag.Sumw2()
Btagmax.Sumw2()
Btruth.Sumw2()
JetsVsBtag.Sumw2()
QCDbkgET.Sumw2()
QCDbkgETh.Sumw2()
QCDbkgETl.Sumw2()
QCDbkgEW.Sumw2()
QCDbkgEWh.Sumw2()
QCDbkgEWl.Sumw2()
QCDbkgPT.Sumw2()
QCDbkgPTh.Sumw2()
QCDbkgPTl.Sumw2()
QCDbkgPW.Sumw2()
QCDbkgPWh.Sumw2()
QCDbkgPWl.Sumw2()
QCDbkgPTW.Sumw2()
QCDbkgPTWh.Sumw2()
QCDbkgPTWl.Sumw2()
QCDbkgPhT.Sumw2()
QCDbkgPhTh.Sumw2()
QCDbkgPhTl.Sumw2()
QCDbkgPhW.Sumw2()
QCDbkgPhWh.Sumw2()
QCDbkgPhWl.Sumw2()
QCDbkgdPhi.Sumw2()
QCDbkgdPhih.Sumw2()
QCDbkgdPhil.Sumw2()
QCDbkg_ARR = []
kinVars = ['', 'ET', 'EW', 'PT', 'PW', 'PTW', 'PhT', 'PhW', 'dPhi' ]
kinBin = [140, 12, 12, 50, 50, 35, 12, 12, 12 ]
kinLow = [500, -2.4, -2.4, 450, 370, 0, -pie, -pie, 2.2 ]
kinHigh = [4000, 2.4, 2.4, 1500, 1430, 700, pie, pie, pie ]
# if options.var == 'analyzer':
# iterations = 1
# elif options.var == 'kinematics':
# iterations = len(kinVars)
# else:
# print "You messed up the var options bozo"
# quit()
iterations = len(kinVars)
arr_count = 0
for iVar in range(0,iterations):
for ihist in fittitles:
QCDbkg_ARR.append(TH1F("QCDbkg"+kinVars[iVar]+ihist, str(kinVars[iVar]) + "in b+1 pt est etabin", kinBin[iVar], kinLow[iVar], kinHigh[iVar]))
QCDbkg_ARR[arr_count].Sumw2()
arr_count += 1
#---------------------------------------------------------------------------------------------------------------------#
# loop over events
#---------------------------------------------------------------------------------------------------------------------#
count = 0
jobiter = 0
print "Start looping"
#initialize the ttree variables
tree_vars = { "wpt":array('d',[0.]),
"wmass":array('d',[0.]),
"tpt":array('d',[0.]),
"tmass":array('d',[0.]),
"tau32":array('d',[0.]),
"tau21":array('d',[0.]),
"sjbtag":array('d',[0.]),
"weight":array('d',[0.])}
NewTree = Make_Trees(tree_vars)
treeEntries = tree.GetEntries()
goodEvents = []
# Design the splitting if necessary
if jobs != 1:
evInJob = int(treeEntries/jobs)
lowBinEdge = evInJob*(num-1)
highBinEdge = evInJob*num
if num == jobs:
highBinEdge = treeEntries
else:
lowBinEdge = 0
highBinEdge = treeEntries
nev.SetBinContent(1,B2Gnev)
print "Range of events: (" + str(lowBinEdge) + ", " + str(highBinEdge) + ")"
for entry in range(lowBinEdge,highBinEdge):
# Have to grab tree entry first
tree.GetEntry(entry)
count = count + 1
if count % 100000 == 0 :
print '--------- Processing Event ' + str(count) +' -- percent complete ' + str(100*count/(highBinEdge-lowBinEdge)) + '% -- '
doneAlready = False
for hemis in ['hemis0','hemis1']:
if hemis == 'hemis0':
# Load up the ttree values
tVals = {
"tau1":tree.tau1_leading,
"tau2":tree.tau2_leading,
"tau3":tree.tau3_leading,
"phi":tree.phi_leading,
"mass":tree.mass_leading,
"pt":tree.pt_leading,
"eta":tree.eta_leading,
"sjbtag":tree.sjbtag_leading,
"SDmass":tree.SDmass_leading
}
wVals = {
"tau1":tree.tau1_subleading,
"tau2":tree.tau2_subleading,
"tau3":tree.tau3_subleading,
"phi":tree.phi_subleading,
"mass":tree.mass_subleading,
"pt":tree.pt_subleading,
"eta":tree.eta_subleading,
"sjbtag":tree.sjbtag_subleading,
"SDmass":tree.SDmass_subleading
}
if hemis == 'hemis1' and doneAlready == False :
wVals = {
"tau1":tree.tau1_leading,
"tau2":tree.tau2_leading,
"tau3":tree.tau3_leading,
"phi":tree.phi_leading,
"mass":tree.mass_leading,
"pt":tree.pt_leading,
"eta":tree.eta_leading,
"sjbtag":tree.sjbtag_leading,
"SDmass":tree.SDmass_leading
}
tVals = {
"tau1":tree.tau1_subleading,
"tau2":tree.tau2_subleading,
"tau3":tree.tau3_subleading,
"phi":tree.phi_subleading,
"mass":tree.mass_subleading,
"pt":tree.pt_subleading,
"eta":tree.eta_subleading,
"sjbtag":tree.sjbtag_subleading,
"SDmass":tree.SDmass_subleading
}
elif hemis == 'hemis1' and doneAlready == True:
continue
# Remake the lorentz vectors
tjet = TLorentzVector()
tjet.SetPtEtaPhiM(tVals["pt"],tVals["eta"],tVals["phi"],tVals["mass"])
wjet = TLorentzVector()
wjet.SetPtEtaPhiM(wVals["pt"],wVals["eta"],wVals["phi"],wVals["mass"])
weight = 1.0
dy_val = abs(tjet.Rapidity()-wjet.Rapidity())
MtopW = (tjet+wjet).M()
Mtw_cut1.Fill(MtopW,weight)
wpt_cut = wpt[0]<wjet.Perp()<wpt[1]
tpt_cut = tpt[0]<tjet.Perp()<tpt[1]
dy_cut = dy[0]<=dy_val<dy[1]
if wpt_cut and tpt_cut:
Mtw_cut2.Fill(MtopW,weight)
deltaY.Fill(dy_val,weight)
if dy_cut:
Mtw_cut3.Fill(MtopW,weight)
# Have never used this so ignoring for now (pdfLabel/Handle also not defined)
# if options.pdfweights != "nominal" :
# tree.getByLabel( pdfLabel, pdfHandle )
# pdfs = pdfHandle.product()
# iweight = PDF_Lookup( pdfs , options.pdfweights )
# weight *= iweight
weightSFt = 1.0
weightSFtdown = 1.0
weightSFtup = 1.0
if options.set!="data":
bin1 = tree.pileBin
if False:#options.pileup != 'off':
weight *= PilePlot.GetBinContent(bin1)
# CHANGE BACK - When you have the correct top scale factors
# if options.cuts=="default" and options.set!="QCD":
# #top scale factor reweighting done here
# SFT = SFT_Lookup( tjet.Perp() )
# weightSFt = SFT[0]
# weightSFtdown = SFT[1]
# weightSFtup = SFT[2]
# For top mass
tmass_cut = tmass[0]<tVals["SDmass"]<tmass[1]
TopMass.Fill(tVals["SDmass"],weight)
if tmass_cut :
Mtw_cut4.Fill(MtopW,weight)
ht = tjet.Perp() + wjet.Perp()
if ht < 1100.0:
continue
weighttrigup=1.0
weighttrigdown=1.0
# CHANGE BACK - When triggers aren't wonky any more
# if tname != 'none' and options.set!='data' :
# #Trigger reweighting done here
# TRW = Trigger_Lookup( ht , TrigPlot )[0]
# TRWup = Trigger_Lookup( ht , TrigPlot )[1]
# TRWdown = Trigger_Lookup( ht , TrigPlot )[2]
# weighttrigup=weight*TRWup
# weighttrigdown=weight*TRWdown
# weight*=TRW
# Like pdfweights, have never turned this on and GenLabel/Handle don't exist so ignoring for now
# if options.ptreweight == "on":
# #ttbar pt reweighting done here
# tree.getByLabel( GenLabel, GenHandle )
# GenParticles = GenHandle.product()
# PTW = PTW_Lookup( GenParticles )
# weight*=PTW
# weightSFptup=max(0.0,weight*(2*PTW-1))
# weightSFptdown=weight
weightSFtup=weight*weightSFtup
weightSFtdown=weight*weightSFtdown
weight*=weightSFt
weighttrigup*=weightSFt
weighttrigdown*=weightSFt
try:
tau32val = tVals["tau3"]/tVals["tau2"]
tau21val = wVals["tau2"]/wVals["tau1"]
except:
continue
tau21_cut = tau21[0]<=tau21val<tau21[1]
tau32_cut = tau32[0]<=tau32val<tau32[1]
SJ_csvval = tVals["sjbtag"]
sjbtag_cut = sjbtag[0]<SJ_csvval<=sjbtag[1]
CSVMax.Fill(SJ_csvval,weight)
Nsubjetiness32.Fill(tau32val,weight)
Nsubjetiness21.Fill(tau21val,weight)
if type(wmass[0]) is float:
wmass_cut = wmass[0]<=wVals["SDmass"]<wmass[1]
elif type(wmass[0]) is list:
wmass_cut = wmass[0][0]<=wVals["SDmass"]<wmass[0][1] or wmass[1][0]<=wVals["SDmass"]<wmass[1][1]
else:
print "wmass type error"
continue
FullTop = sjbtag_cut and tau32_cut
if wmass_cut:
Mtw_cut5.Fill(MtopW,weight)
if tau21_cut:
Mtw_cut6.Fill(MtopW,weight)
# ------------------- Now going to split into alphabet and tagrate parts -----------------
if options.Alphabet == "off":
eta_regions = [eta1,eta2]
eta1_cut = eta1[0]<=abs(tjet.Eta())<eta1[1]
eta2_cut = eta2[0]<=abs(tjet.Eta())<eta2[1]
TTRweight = bkg_weight_pt(tjet,TTR,eta_regions)
TTRweightsigsq = bkg_weight_pt(tjet,TTR_err,eta_regions)
TTRweighterrup = TTRweight+sqrt(TTRweightsigsq)
TTRweighterrdown = TTRweight-sqrt(TTRweightsigsq)
modm = tVals["SDmass"]
if options.modmass=='nominal':
massw = ModFit.Eval(modm) #ModPlot.Interpolate(modm)
if options.modmass=='up':
massw = 1 + 0.5*(ModFit.Eval(modm) -1)
if options.modmass=='down':
massw = max(0.0,1 + 1.5*(ModFit.Eval(modm) -1))
if options.modmass=='none':
massw = 1
masswHist.Fill(massw)
if (eta1_cut) and not FullTop:
xbin = TagPlot2de2.GetXaxis().FindBin(tjet.Perp())
ybin = TagPlot2de2.GetYaxis().FindBin(MtopW)
tagrate2d = TagPlot2de2.GetBinContent(xbin,ybin)
tagrate2derr = TagPlot2de2.GetBinError(xbin,ybin)
QCDbkg2D.Fill(MtopW,tagrate2d*weight*massw)
QCDbkg2Dup.Fill(MtopW,(tagrate2d+tagrate2derr)*weight*massw)
QCDbkg2Ddown.Fill(MtopW,(tagrate2d-tagrate2derr)*weight*massw)
Mtw_cut8.Fill(MtopW,weight)
QCDbkgET2D.Fill(tjet.Eta(),tagrate2d*weight*massw)
QCDbkgET2Dup.Fill(tjet.Eta(),(tagrate2d+tagrate2derr)*weight*massw)
QCDbkgET2Ddown.Fill(tjet.Eta(),(tagrate2d-tagrate2derr)*weight*massw)
QCDbkgEW2D.Fill(wjet.Eta(),tagrate2d*weight*massw)
QCDbkgEW2Dup.Fill(wjet.Eta(),(tagrate2d+tagrate2derr)*weight*massw)
QCDbkgEW2Ddown.Fill(wjet.Eta(),(tagrate2d-tagrate2derr)*weight*massw)
QCDbkgPT2D.Fill(tjet.Perp(),tagrate2d*weight*massw)
QCDbkgPT2Dup.Fill(tjet.Perp(),(tagrate2d+tagrate2derr)*weight*massw)
QCDbkgPT2Ddown.Fill(tjet.Perp(),(tagrate2d-tagrate2derr)*weight*massw)
QCDbkgPW2D.Fill(wjet.Perp(),tagrate2d*weight*massw)
QCDbkgPW2Dup.Fill(wjet.Perp(),(tagrate2d+tagrate2derr)*weight*massw)
QCDbkgPW2Ddown.Fill(wjet.Perp(),(tagrate2d-tagrate2derr)*weight*massw)
QCDbkgPTW2D.Fill((tjet+wjet).Perp(),tagrate2d*weight*massw)
QCDbkgPTW2Dup.Fill((tjet+wjet).Perp(),(tagrate2d+tagrate2derr)*weight*massw)
QCDbkgPTW2Ddown.Fill((tjet+wjet).Perp(),(tagrate2d-tagrate2derr)*weight*massw)
QCDbkgPhT2D.Fill(tjet.Phi(),tagrate2d*weight*massw)
QCDbkgPhT2Dup.Fill(tjet.Phi(),(tagrate2d+tagrate2derr)*weight*massw)
QCDbkgPT2Ddown.Fill(tjet.Phi(),(tagrate2d-tagrate2derr)*weight*massw)
QCDbkgPhW2D.Fill(wjet.Phi(),tagrate2d*weight*massw)
QCDbkgPhW2Dup.Fill(wjet.Phi(),(tagrate2d+tagrate2derr)*weight*massw)
QCDbkgPhW2Ddown.Fill(wjet.Phi(),(tagrate2d-tagrate2derr)*weight*massw)
QCDbkgdPhi2D.Fill(abs(tjet.Phi()-wjet.Phi()),tagrate2d*weight*massw)
QCDbkgdPhi2Dup.Fill(abs(tjet.Phi()-wjet.Phi()),(tagrate2d+tagrate2derr)*weight*massw)
QCDbkgdPhi2Ddown.Fill(abs(tjet.Phi()-wjet.Phi()),(tagrate2d-tagrate2derr)*weight*massw)
if (eta2_cut) and not FullTop:
xbin = TagPlot2de2.GetXaxis().FindBin(tjet.Perp())
ybin = TagPlot2de2.GetYaxis().FindBin(MtopW)
tagrate2d = TagPlot2de2.GetBinContent(xbin,ybin)
tagrate2derr = TagPlot2de2.GetBinError(xbin,ybin)
QCDbkg2D.Fill(MtopW,tagrate2d*weight*massw)
QCDbkg2Dup.Fill(MtopW,(tagrate2d+tagrate2derr)*weight*massw)
QCDbkg2Ddown.Fill(MtopW,(tagrate2d-tagrate2derr)*weight*massw)
Mtw_cut8.Fill(MtopW,weight)
QCDbkgET2D.Fill(tjet.Eta(),tagrate2d*weight*massw)
QCDbkgET2Dup.Fill(tjet.Eta(),(tagrate2d+tagrate2derr)*weight*massw)
QCDbkgET2Ddown.Fill(tjet.Eta(),(tagrate2d-tagrate2derr)*weight*massw)
QCDbkgEW2D.Fill(wjet.Eta(),tagrate2d*weight*massw)
QCDbkgEW2Dup.Fill(wjet.Eta(),(tagrate2d+tagrate2derr)*weight*massw)
QCDbkgEW2Ddown.Fill(wjet.Eta(),(tagrate2d-tagrate2derr)*weight*massw)
QCDbkgPT2D.Fill(tjet.Perp(),tagrate2d*weight*massw)
QCDbkgPT2Dup.Fill(tjet.Perp(),(tagrate2d+tagrate2derr)*weight*massw)
QCDbkgPT2Ddown.Fill(tjet.Perp(),(tagrate2d-tagrate2derr)*weight*massw)
QCDbkgPW2D.Fill(wjet.Perp(),tagrate2d*weight*massw)
QCDbkgPW2Dup.Fill(wjet.Perp(),(tagrate2d+tagrate2derr)*weight*massw)
QCDbkgPW2Ddown.Fill(wjet.Perp(),(tagrate2d-tagrate2derr)*weight*massw)
QCDbkgPTW2D.Fill((tjet+wjet).Perp(),tagrate2d*weight*massw)
QCDbkgPTW2Dup.Fill((tjet+wjet).Perp(),(tagrate2d+tagrate2derr)*weight*massw)
QCDbkgPTW2Ddown.Fill((tjet+wjet).Perp(),(tagrate2d-tagrate2derr)*weight*massw)
QCDbkgPhT2D.Fill(tjet.Phi(),tagrate2d*weight*massw)
QCDbkgPhT2Dup.Fill(tjet.Phi(),(tagrate2d+tagrate2derr)*weight*massw)
QCDbkgPT2Ddown.Fill(tjet.Phi(),(tagrate2d-tagrate2derr)*weight*massw)
QCDbkgPhW2D.Fill(wjet.Phi(),tagrate2d*weight*massw)
QCDbkgPhW2Dup.Fill(wjet.Phi(),(tagrate2d+tagrate2derr)*weight*massw)
QCDbkgPhW2Ddown.Fill(wjet.Phi(),(tagrate2d-tagrate2derr)*weight*massw)
QCDbkgdPhi2D.Fill(abs(tjet.Phi()-wjet.Phi()),tagrate2d*weight*massw)
QCDbkgdPhi2Dup.Fill(abs(tjet.Phi()-wjet.Phi()),(tagrate2d+tagrate2derr)*weight*massw)
QCDbkgdPhi2Ddown.Fill(abs(tjet.Phi()-wjet.Phi()),(tagrate2d-tagrate2derr)*weight*massw)
fillSpec = [MtopW, tjet.Eta(), wjet.Eta(), tjet.Perp(), wjet.Perp(), tjet.Perp()+wjet.Perp(), tjet.Phi(), wjet.Phi(), abs(tjet.Phi()-wjet.Phi())]
arr_count = 0
for spec in fillSpec:
for ifit in range(0,len(fittitles)):
tempweight = bkg_weight_pt(tjet,fits[ifit],eta_regions)
QCDbkg_ARR[arr_count].Fill(spec,tempweight*weight*massw)
arr_count+=1
if not FullTop:
QCDbkg.Fill(MtopW,TTRweight*weight*massw)
QCDbkgh.Fill(MtopW,TTRweighterrup*weight*massw)
QCDbkgl.Fill(MtopW,TTRweighterrdown*weight*massw)
QCDbkgMtStack.Fill(tVals["SDmass"],TTRweight*weight*massw)
QCDbkgET.Fill(tjet.Eta(),TTRweight*weight*massw)
QCDbkgETh.Fill(tjet.Eta(),TTRweighterrup*weight*massw)
QCDbkgETl.Fill(tjet.Eta(),TTRweighterrdown*weight*massw)
QCDbkgEW.Fill(wjet.Eta(),TTRweight*weight*massw)
QCDbkgEWh.Fill(wjet.Eta(),TTRweighterrup*weight*massw)
QCDbkgEWl.Fill(wjet.Eta(),TTRweighterrdown*weight*massw)
QCDbkgPT.Fill(tjet.Perp(),TTRweight*weight*massw)
QCDbkgPTh.Fill(tjet.Perp(),TTRweighterrup*weight*massw)
QCDbkgPTl.Fill(tjet.Perp(),TTRweighterrdown*weight*massw)
QCDbkgPW.Fill(wjet.Perp(),TTRweight*weight*massw)
QCDbkgPWh.Fill(wjet.Perp(),TTRweighterrup*weight*massw)
QCDbkgPWl.Fill(wjet.Perp(),TTRweighterrdown*weight*massw)
QCDbkgPTW.Fill((tjet+wjet).Perp(),TTRweight*weight*massw)
QCDbkgPTWh.Fill((tjet+wjet).Perp(),TTRweighterrup*weight*massw)
QCDbkgPTWl.Fill((tjet+wjet).Perp(),TTRweighterrdown*weight*massw)
QCDbkgPhT.Fill(tjet.Phi(),TTRweight*weight*massw)
QCDbkgPhTh.Fill(tjet.Phi(),TTRweighterrup*weight*massw)
QCDbkgPhTl.Fill(tjet.Phi(),TTRweighterrdown*weight*massw)
QCDbkgPhW.Fill(wjet.Phi(),TTRweight*weight*massw)
QCDbkgPhWh.Fill(wjet.Phi(),TTRweighterrup*weight*massw)
QCDbkgPhWl.Fill(wjet.Phi(),TTRweighterrdown*weight*massw)
QCDbkgdPhi.Fill(abs(tjet.Phi()-wjet.Phi()),TTRweight*weight*massw)
QCDbkgdPhih.Fill(abs(tjet.Phi()-wjet.Phi()),TTRweighterrup*weight*massw)
QCDbkgdPhil.Fill(abs(tjet.Phi()-wjet.Phi()),TTRweighterrdown*weight*massw)
if sjbtag_cut:
Mtw_cut9.Fill(MtopW,weight)
# Grab the pass/fail ratio at the last second for efficiency
if tau32_cut:
Mtw_cut10.Fill(MtopW,weight)
#if ((MtopW)>2400):
# goodEvents.append( [ tree.object().id().run(), tree.object().id().luminosityBlock(), tree.object().id().event(), ] )
Mtw.Fill(MtopW,weight)
MtStack.Fill(tVals["SDmass"],weight)
Mtwtrigup.Fill(MtopW,weighttrigup)
Mtwtrigdown.Fill(MtopW,weighttrigdown)
MtwTup.Fill(MtopW,weightSFtup)
MtwTdown.Fill(MtopW,weightSFtdown)
EtaTop.Fill(tjet.Eta(),weight)
EtaW.Fill(wjet.Eta(),weight)
PtTop.Fill(tjet.Perp(),weight)
PtW.Fill(wjet.Perp(),weight)
PtTopW.Fill((tjet+wjet).Perp(),weight)
PhiTop.Fill(tjet.Phi(),weight)
PhiW.Fill(wjet.Phi(),weight)
dPhi.Fill(abs(tjet.Phi()-wjet.Phi()),weight)
temp_variables = { "wpt":wjet.Perp(),
"wmass":wVals["SDmass"],
"tpt":tjet.Perp(),
"tmass":tVals["SDmass"],
"tau32":tau32val,
"tau21":tau21val,
"sjbtag":SJ_csvval,
"weight":weight}
for tv in tree_vars.keys():
tree_vars[tv][0] = temp_variables[tv]
NewTree.Fill()
doneAlready = True
# ---------------------- Now for Alphabet ----------------------------------------
elif options.Alphabet == "on":
eta_cut = eta[0]<=abs(tjet.Eta())<eta[1]
massw = 1