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MakePlots_Wlnu.py
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MakePlots_Wlnu.py
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from ast import parse
import ROOT
import os
import numpy as np
from collections import OrderedDict
from modules.SampleManager import DrawConfig, Sample, SampleManager
from modules.Binnings import Vptbins
from modules.theoryUncIndices import theoryUnc_13TeV_wjets, theoryUnc_5TeV_wjets
from CMSPLOTS.myFunction import DrawHistos
import argparse
ROOT.gROOT.SetBatch(True)
ROOT.ROOT.EnableImplicitMT(10)
def main():
print("Program start...")
parser = argparse.ArgumentParser(
description="Make plots for Wlnu analysis")
parser.add_argument("--doTest", action="store_true", dest="doTest",
help="Run on a subset of samples for debugging; false runs on all dataset.")
parser.add_argument("--doWpT", action="store_true", dest="doWpT",
help="Bin in different W pt bins; false runs inclusively")
parser.add_argument("--is5TeV", action="store_true", dest="is5TeV",
help="Analyze the 5TeV data; false runs on 13TeV data")
parser.add_argument("--doElectron", action="store_true", dest="doElectron",
help="Analyze the electron channel; false runs the muon channel")
parser.add_argument("--doTheoryNorm", action="store_true",
dest="doTheoryNorm", help="Normalize to theory; false runs on data")
parser.add_argument("--reweightZpt", action="store_true", dest="reweightZpt",
help="Reweight the V pt according to the dilepton data-MC distribution; false does not reweight")
args = parser.parse_args()
doMuon = not args.doElectron
doTest = args.doTest
doWpT = args.doWpT
is5TeV = args.is5TeV
doTheoryNorm = args.doTheoryNorm
doZptReweight = args.reweightZpt
#reweightZpt = True
print("doMuon: ", doMuon)
print("doTest:", doTest)
print("doWpT:", doWpT)
print("is5TeV:", is5TeV)
print("doTheoryNorm", doTheoryNorm)
print("doZptReweight", doZptReweight)
str_zpt = "default" if doZptReweight else "noZptReweight"
outdir = ""
outdir += "5TeV/" if is5TeV else "13TeV/"
outdir += "Wmunu/" if doMuon else "Wenu/"
outdir += str_zpt + "/"
# ROOT.gROOT.ProcessLine('TFile* f_zpt = TFile::Open("results/zpt_weight.root")')
# ROOT.gROOT.ProcessLine('TH1D* h_zpt_ratio = (TH1D*)f_zpt->Get("h_zpt_ratio")')
if not is5TeV:
if doMuon:
ROOT.gROOT.ProcessLine(
'TFile* f_zpt = TFile::Open("data/output_Zpt_mumu_13TeV.root")')
ROOT.gROOT.ProcessLine(
'TH1D* h_zpt_ratio = (TH1D*)f_zpt->Get("histo_zjets_zpt_mumu_Ratio")')
else:
ROOT.gROOT.ProcessLine(
'TFile* f_zpt = TFile::Open("data/output_Zpt_ee_13TeV.root")')
ROOT.gROOT.ProcessLine(
'TH1D* h_zpt_ratio = (TH1D*)f_zpt->Get("histo_zjets_zpt_ee_Ratio")')
else:
if doMuon:
ROOT.gROOT.ProcessLine(
'TFile* f_zpt = TFile::Open("data/output_Zpt_mumu_5TeV.root")')
ROOT.gROOT.ProcessLine(
'TH1D* h_zpt_ratio = (TH1D*)f_zpt->Get("histo_zjets_zpt_mumu_Ratio")')
else:
ROOT.gROOT.ProcessLine(
'TFile* f_zpt = TFile::Open("data/output_Zpt_ee_5TeV.root")')
ROOT.gROOT.ProcessLine(
'TH1D* h_zpt_ratio = (TH1D*)f_zpt->Get("histo_zjets_zpt_ee_Ratio")')
if not is5TeV:
if doMuon:
input_data = "inputs/wmunu/input_data.txt"
input_wl0 = "inputs/wmunu/input_wm0.txt"
input_wl1 = "inputs/wmunu/input_wm1.txt"
input_wl2 = "inputs/wmunu/input_wm2.txt"
input_ttbar = "inputs/wmunu/input_ttbar_dilepton.txt"
input_ttbar_1lep = "inputs/wmunu/input_ttbar_singlelepton.txt"
input_ttbar_0lep = "inputs/wmunu/input_ttbar_hadronic.txt"
input_ww = "inputs/wmunu/input_ww.txt"
input_wz = "inputs/wmunu/input_wz.txt"
input_zz = "inputs/wmunu/input_zz.txt"
input_zxx = "inputs/wmunu/input_zxx.txt"
input_wx0 = "inputs/wmunu/input_wx0.txt"
input_wx1 = "inputs/wmunu/input_wx1.txt"
input_wx2 = "inputs/wmunu/input_wx2.txt"
else:
input_data = "inputs/wenu/input_data.txt"
input_wl0 = "inputs/wenu/input_we0.txt"
input_wl1 = "inputs/wenu/input_we1.txt"
input_wl2 = "inputs/wenu/input_we2.txt"
input_ttbar = "inputs/wenu/input_ttbar_dilepton.txt"
input_ttbar_1lep = "inputs/wenu/input_ttbar_singlelepton.txt"
input_ttbar_0lep = "inputs/wenu/input_ttbar_hadronic.txt"
input_ww = "inputs/wenu/input_ww.txt"
input_wz = "inputs/wenu/input_wz.txt"
input_zz = "inputs/wenu/input_zz.txt"
input_zxx = "inputs/wenu/input_zxx.txt"
input_wx0 = "inputs/wenu/input_wx0.txt"
input_wx1 = "inputs/wenu/input_wx1.txt"
input_wx2 = "inputs/wenu/input_wx2.txt"
else:
if doMuon:
input_data = "inputs_5TeV/wmunu/input_data.txt"
input_wl = "inputs_5TeV/wmunu/input_wm.txt"
input_ttbar = "inputs_5TeV/wmunu/input_ttbar.txt"
input_ww = "inputs_5TeV/wmunu/input_ww.txt"
input_wz = "inputs_5TeV/wmunu/input_wz.txt"
input_zz2l = "inputs_5TeV/wmunu/input_zz2l.txt"
input_zz4l = "inputs_5TeV/wmunu/input_zz4l.txt"
input_zxx = "inputs_5TeV/wmunu/input_zxx.txt"
input_wx = "inputs_5TeV/wmunu/input_wx.txt"
else:
input_data = "inputs_5TeV/wenu/input_data.txt"
input_wl = "inputs_5TeV/wenu/input_we.txt"
input_ttbar = "inputs_5TeV/wenu/input_ttbar.txt"
input_ww = "inputs_5TeV/wenu/input_ww.txt"
input_wz = "inputs_5TeV/wenu/input_wz.txt"
input_zz2l = "inputs_5TeV/wenu/input_zz2l.txt"
input_zz4l = "inputs_5TeV/wenu/input_zz4l.txt"
input_zxx = "inputs_5TeV/wenu/input_zxx.txt"
input_wx = "inputs_5TeV/wenu/input_wx.txt"
DataSamp = Sample(input_data, isMC=False, legend="Data",
name="Data", isWSR=True, doTheoryVariation=False)
signame = "wlnu"
if not is5TeV:
# W -> munu
# wjetsnorm = 1.06
wjetsnorm = 1.0
Wl0Samp = Sample(input_wl0, isMC=True, name="wl0",
isWSR=True, additionalnorm=wjetsnorm, reweightZpt=doZptReweight)
Wl1Samp = Sample(input_wl1, isMC=True, name="wl1",
isWSR=True, additionalnorm=wjetsnorm, reweightZpt=doZptReweight)
Wl2Samp = Sample(input_wl2, isMC=True, name="wl2",
isWSR=True, additionalnorm=wjetsnorm, reweightZpt=doZptReweight)
# ttbar
TTbarSamp = Sample(input_ttbar, isMC=True,
name="ttbar_dilepton", isWSR=True)
TT1LepSamp = Sample(input_ttbar_1lep, isMC=True,
name="ttbar_1lepton", isWSR=True)
#TT0LepSamp = Sample(input_ttbar_0lep, isMC=True,
# name="ttbar_0lepton", isWSR=True)
# dibosons
WWSamp = Sample(input_ww, isMC=True, name="WW", isWSR=True)
WZSamp = Sample(input_wz, isMC=True, name="WZ", isWSR=True)
ZZSamp = Sample(input_zz, isMC=True, name="ZZ", isWSR=True)
# tau
ZXXSamp = Sample(input_zxx, isMC=True, name="ZXX",
isWSR=True, reweightZpt=doZptReweight)
Wx0Samp = Sample(input_wx0, isMC=True, name="wx0",
isWSR=True, reweightZpt=doZptReweight)
Wx1Samp = Sample(input_wx1, isMC=True, name="wx1",
isWSR=True, reweightZpt=doZptReweight)
Wx2Samp = Sample(input_wx2, isMC=True, name="wx2",
isWSR=True, reweightZpt=doZptReweight)
if not doTest:
#sampMan = SampleManager(DataSamp, [Wl0Samp, Wl1Samp, Wl2Samp, TTbarSamp, TT1LepSamp,
# TT0LepSamp, WWSamp, WZSamp, ZZSamp, ZXXSamp, Wx0Samp, Wx1Samp, Wx2Samp])
sampMan = SampleManager(DataSamp, [Wl0Samp, Wl1Samp, Wl2Samp, TTbarSamp, TT1LepSamp,
WWSamp, WZSamp, ZZSamp, ZXXSamp, Wx0Samp, Wx1Samp, Wx2Samp])
else:
sampMan = SampleManager(DataSamp, [Wl1Samp, Wl2Samp])
wxname = "wx"
sampMan.groupMCs(["wx0", "wx1", "wx2"], wxname, 216, 'wx')
sampMan.groupMCs(["WW", "WZ", "ZZ"], 'vv', 75, 'vv')
sampMan.groupMCs(['ZXX'], 'zxx', 84, 'zxx')
sampMan.groupMCs(["ttbar_dilepton", "ttbar_1lepton"], "ttbar", 96, "t#bar{t}")
label = "W#rightarrow#mu#nu" if doMuon else "W#rightarrow e#nu"
sampMan.groupMCs(['wl0', 'wl1', 'wl2'], signame,
92, label)
# for the signal samples
if not doTest:
signalSamps = [Wl0Samp, Wl1Samp, Wl2Samp]
else:
signalSamps = [Wl1Samp, Wl2Samp]
signalSampnames = [samp.name for samp in signalSamps]
else:
# for the 5TeV files
# W -> munu
wjetsnorm = 1.0
label = "W#rightarrow#mu#nu" if doMuon else "W#rightarrow e#nu"
WlSamp = Sample(input_wl, isMC=True, name=signame, color=92,
legend=label, isWSR=True, additionalnorm=wjetsnorm, is5TeV=True, reweightZpt=doZptReweight)
# ttbar
TTbarSamp = Sample(input_ttbar, isMC=True, name="ttbar",
color=86, legend="t#bar{t}", isWSR=True, is5TeV=True)
# dibosons
WWSamp = Sample(input_ww, isMC=True, name="WW",
isWSR=True, is5TeV=True)
WZSamp = Sample(input_wz, isMC=True, name="WZ",
isWSR=True, is5TeV=True)
ZZ2LSamp = Sample(input_zz2l, isMC=True, name="ZZ2L",
isWSR=True, is5TeV=True)
ZZ4LSamp = Sample(input_zz4l, isMC=True, name="ZZ4L",
isWSR=True, is5TeV=True)
# tau
ZXXSamp = Sample(input_zxx, isMC=True, name="ZXX",
isWSR=True, is5TeV=True, reweightZpt=doZptReweight)
WxSamp = Sample(input_wx, isMC=True, name="wx",
color=216, legend="wx", isWSR=True, is5TeV=True, reweightZpt=doZptReweight)
sampMan = SampleManager(DataSamp, [
WlSamp, TTbarSamp, WWSamp, WZSamp, ZZ2LSamp, ZZ4LSamp, ZXXSamp, WxSamp], is5TeV=True)
sampMan.groupMCs(["WW", "WZ", "ZZ2L", "ZZ4L"], 'vv', 75, 'vv')
sampMan.groupMCs(['ZXX'], 'zxx', 84, 'zxx')
label = "W#rightarrow#mu#nu" if doMuon else "W#rightarrow e#nu"
# for the signal samples
signalSamps = [WlSamp]
signalSampnames = [samp.name for samp in signalSamps]
print(("signal sample names: ", signalSampnames))
h_sigs = OrderedDict()
sampMan.outdir = "plots/"+outdir
#sampMan.ApplyCutAll("relIso > 0.05")
# define variables and weights
sampMan.DefineAll("Lep_pt", "lep.Pt()")
sampMan.DefineAll("Lep_eta", "lep.Eta()")
sampMan.DefineAll("Lep_phi", "lep.Phi()")
for i in [1, 2, 3, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16]:
# variations on the recoil correction
sampMan.DefineMC("met_{}_pt".format(str(i)),
"metVars[{}]".format(str(i)))
sampMan.DefineMC("met_{}_phi".format(str(i)),
"TVector2::Phi_mpi_pi(metVarsPhi[{}])".format(str(i)))
# for data, always use the uncorrected
DataSamp.Define("met_{}_pt".format(str(i)), "metVars[0]")
DataSamp.Define("met_{}_phi".format(str(i)), "TVector2::Phi_mpi_pi(metVarsPhi[0])")
# mT
sampMan.DefineAll("mT_{}".format(str(
i)), "TMath::Sqrt(2 * Lep_pt * met_{}_pt * (1- TMath::Cos(Lep_phi - met_{}_phi)))".format(str(i), str(i)))
# raw MET
sampMan.DefineAll("met_org_pt", "metVars[16]")
sampMan.DefineAll("met_org_phi", "TVector2::Phi_mpi_pi(metVarsPhi[16])")
# deltaPhi
sampMan.DefineAll("deltaPhi", "TVector2::Phi_0_2pi(lep.Phi() - met_1_phi)")
# recoil variables
sampMan.DefineAll("V2W", "UVec(lep.Pt(), lep.Phi(), met_1_pt, met_1_phi)")
sampMan.DefineAll("WpT", "V2W.Mod()")
sampMan.DefineAll("Wphi", "TVector2::Phi_mpi_pi(V2W.Phi())")
# charge
lepname = "mu" if doMuon else "e"
sampMan.DefineAll(lepname+"plus", "q > 0")
sampMan.DefineAll(lepname+"minus", "q < 0")
chgbins = [lepname+"plus", lepname + "minus"]
# WpT bins
# bin0 is the inclusive bin
sampMan.DefineAll("WpT_bin0", "WpT>=0.")
wptbins = ["WpT_bin0"]
if doWpT:
sampMan.DefineAll("WpT_bin1", "WpT>=0. && WpT<8.0")
sampMan.DefineAll("WpT_bin2", "WpT>=8.0 && WpT<16.0")
sampMan.DefineAll("WpT_bin3", "WpT>=16.0 && WpT<24.0")
sampMan.DefineAll("WpT_bin4", "WpT>=24.0 && WpT<32.0")
sampMan.DefineAll("WpT_bin5", "WpT>=32.0 && WpT<40.0")
sampMan.DefineAll("WpT_bin6", "WpT>=40.0 && WpT<50.0")
sampMan.DefineAll("WpT_bin7", "WpT>=50.0 && WpT<70.0")
sampMan.DefineAll("WpT_bin8", "WpT>=70.0 && WpT<100.0")
sampMan.DefineAll("WpT_bin9", "WpT>=100.0")
wptbins = ["WpT_bin0", "WpT_bin1", "WpT_bin2", "WpT_bin3", "WpT_bin4",
"WpT_bin5", "WpT_bin6", "WpT_bin7", "WpT_bin8", "WpT_bin9"]
if doTest:
wptbins = ["WpT_bin0", "WpT_bin1"]
# truth level
wpttruthbins = []
if doWpT:
sampMan.DefineSpecificMCs(
"WpT_truth", "genV.Pt()", sampnames=signalSampnames)
sampMan.DefineSpecificMCs(
"WpT_truth_bin1", "WpT_truth>=0. && WpT_truth<8.0", sampnames=signalSampnames)
sampMan.DefineSpecificMCs(
"WpT_truth_bin2", "WpT_truth>=8.0 && WpT_truth<16.0", sampnames=signalSampnames)
sampMan.DefineSpecificMCs(
"WpT_truth_bin3", "WpT_truth>=16.0 && WpT_truth<24.0", sampnames=signalSampnames)
sampMan.DefineSpecificMCs(
"WpT_truth_bin4", "WpT_truth>=24.0 && WpT_truth<32.0", sampnames=signalSampnames)
sampMan.DefineSpecificMCs(
"WpT_truth_bin5", "WpT_truth>=32.0 && WpT_truth<40.0", sampnames=signalSampnames)
sampMan.DefineSpecificMCs(
"WpT_truth_bin6", "WpT_truth>=40.0 && WpT_truth<50.0", sampnames=signalSampnames)
sampMan.DefineSpecificMCs(
"WpT_truth_bin7", "WpT_truth>=50.0 && WpT_truth<70.0", sampnames=signalSampnames)
sampMan.DefineSpecificMCs(
"WpT_truth_bin8", "WpT_truth>=70.0 && WpT_truth<100.0", sampnames=signalSampnames)
sampMan.DefineSpecificMCs(
"WpT_truth_bin9", "WpT_truth>=100.0", sampnames=signalSampnames)
wpttruthbins = ["WpT_truth_bin1", "WpT_truth_bin2", "WpT_truth_bin3", "WpT_truth_bin4",
"WpT_truth_bin5", "WpT_truth_bin6", "WpT_truth_bin7", "WpT_truth_bin8", "WpT_truth_bin9"]
if doTest:
wpttruthbins = ["WpT_truth_bin1", "WpT_truth_bin2"]
# eta bins for electrons: barral and endcap
sampMan.DefineAll("lepEta_bin0", "1.0")
sampMan.DefineAll("lepEta_bin1", "abs(lep.Eta()) <= 1.4442")
sampMan.DefineAll("lepEta_bin2", "abs(lep.Eta()) > 1.4442")
# if doMuon:
# etabins = ["lepEta_bin0"]
# else:
# etabins = ["lepEta_bin0", "lepEta_bin1", "lepEta_bin2"]
etabins = ["lepEta_bin0"]
# sample weight
# 0 is the central one with all corrections
for i in [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13]:
for wpt in wptbins:
for lepeta in etabins:
# if i!= 5:
# sampMan.DefineMC("weight_{}_{}_{}".format(str(i), wpt, lepeta), "evtWeight[{}] * self.fnorm * {} * {}".format(str(i), wpt, lepeta))
# else:
# sampMan.DefineMC("weight_{}_{}_{}".format(str(i), wpt, lepeta), "(evtWeight[0] + TMath::Sqrt(TMath::Abs(evtWeight[{}]))) * self.fnorm * {} * {}".format(str(i), wpt, lepeta))
sampMan.DefineMC("weight_{}_{}_{}".format(str(
i), wpt, lepeta), "(TMath::IsNaN(evtWeight[{}]) ? 0.: evtWeight[{}]) * ZptWeight * self.fnorm * {} * {}".format(str(i), str(i), wpt, lepeta))
DataSamp.Define("weight_{}_{}_{}".format(
str(i), wpt, lepeta), "1.0 * {} * {}".format(wpt, lepeta))
for chg in chgbins:
sampMan.DefineAll("weight_{}_{}_{}_{}".format(chg, str(
i), wpt, lepeta), "weight_{}_{}_{} * {}".format(str(i), wpt, lepeta, chg))
# for signal MC, define the truth WpT bins
for wpttruth in wpttruthbins:
for samp in signalSamps:
samp.Define("weight_{}_{}_{}_{}_{}".format(chg, str(
i), wpt, lepeta, wpttruth), "weight_{}_{}_{}_{} * {}".format(chg, str(i), wpt, lepeta, wpttruth))
# scale the theory variations back
# some theory variations are far from 1.0
# use this to scale them back
# this should be equavalent as using fnorm_varied
for i in range(111):
sampMan.DefineMC(
f"lheweightS_{i}", f"lheweight[{i}] * self.nmcevt / self.nmcevts_varied[{i}]")
vsamples = ["wl0", "wl1", "wl2", "wx0", "wx1", "wx2"]
if is5TeV:
vsamples = ["wlnu", "wx"]
sampMan.DefineSpecificMCs("VpT", "genV.Pt()", sampnames=vsamples)
theoryMaps = theoryUnc_13TeV_wjets if not is5TeV else theoryUnc_5TeV_wjets
theoryVariations = OrderedDict()
for var in ["MuRVPTUp", "MuRVPTDown", "MuFVPTUp", "MuFVPTDown", "MuFMuRVPTUp", "MuFMuRVPTDown"]:
idx = theoryMaps.getIndex(var.replace("VPT", ""))
for wpt in range(len(Vptbins)-1):
# pt breaked version of the qcd scale variations
ptmin = Vptbins[wpt]
ptmax = Vptbins[wpt+1]
sampMan.DefineSpecificMCs(f"{var}".replace("VPT", str(
wpt)), f"(VpT >= {ptmin} && VpT < {ptmax}) ? lheweightS_{idx}: 1.0", sampnames=vsamples)
sampMan.DefineAll(f"{var}".replace(
"VPT", str(wpt)), "1.0", excludes=vsamples)
theoryVariations[f"{var}".replace("VPT", str(
wpt))] = f"{var}".replace("VPT", str(wpt))
# MuRUp, MuRDown, MuFUp, MuFDown, MuFMuRUp, MuFMuRDown are inclusive QCD scale variations
sampMan.DefineSpecificMCs(f"{var}".replace("VPT", ""), f"lheweightS_{idx}", sampnames=vsamples)
sampMan.DefineAll(f"{var}".replace("VPT", ""), "1.0", excludes=vsamples)
theoryVariations[f"{var}".replace("VPT", "")] = f"{var}".replace("VPT", "")
# pdf
pdfStart = theoryMaps.getIndex("PDFStart")
for i in range(1, 101):
theoryVariations[f"PDF{i}Up"] = f"lheweightS_{i + pdfStart - 1}"
# alphaS
alphaSUp = theoryMaps.getIndex("alphaSUp")
theoryVariations["alphaSUp"] = f"lheweightS_{alphaSUp}"
# weights with theory variations
for wpt in wptbins:
for lepeta in etabins:
for chg in chgbins:
for var in theoryVariations.values():
sampMan.DefineMC(f"weight_{chg}_{var}_{wpt}_{lepeta}",
f"(TMath::IsNaN(evtWeight[0])) ? 0. : evtWeight[0] * ZptWeight * self.fnorm * {wpt} * {lepeta} * {var} * {chg}")
DataSamp.Define(
f"weight_{chg}_{var}_{wpt}_{lepeta}", f"1.0 * {wpt} * {lepeta} * {chg}")
#
# Some histograms for simple data-MC comparison
#
met_pt_bins = np.array([0., 2.0, 4., 6, 8, 10, 12, 14, 16, 18, 20, 22,
24, 26, 28, 30, 33, 36, 39, 42, 45, 48, 51, 55, 60, 65, 70, 75, 80])
mt_bins = np.concatenate(
(np.linspace(0, 36, 11), np.linspace(40, 90, 51), np.linspace(92, 100, 5), np.linspace(104, 120, 5)))
phimin = -ROOT.TMath.Pi()
phimax = ROOT.TMath.Pi()
dphi_bins = np.concatenate((np.linspace(0, 1, 3), np.linspace(1.2, 2.4, 7), np.linspace(
2.5, 3.5, 11), np.linspace(3.6, 4.8, 7), np.linspace(5.0, 6.0, 3))) * ROOT.TMath.Pi() / 3
eta_bins = np.concatenate(
(np.linspace(-2.4, -2.0, 3), np.linspace(-1.8, 1.8, 37), np.linspace(2.0, 2.4, 3)))
pt_bins = np.concatenate((np.linspace(25, 35, 6), np.linspace(
36, 55, 20), np.linspace(57, 63, 4), np.linspace(66, 70, 2)))
# mass_bins = np.concatenate((np.linspace(70, 76, 3),np.linspace(78,86,5), np.linspace(87, 96, 10), np.linspace(98,104,5), np.linspace(106, 110, 2)))
# do the fine binning first; then rebin in the processHists
mass_bins = np.array([0, 5.0, 10.0, 15.0, 20.0, 25.0, 30.0, 35.0, 40.0, 45.0, 50.0, 55.0, 60.0, 65.0,
70.0, 75.0, 80.0, 85.0, 90.0, 95.0, 100.0, 105.0, 110.0, 115.0, 120.0, 125.0, 130.0, 135.0, 140.])
# nPV
sampMan.cacheDraw("npv", "histo_nPV_"+lepname, 10, 0, 10, DrawConfig(xmin=0, xmax=10, xlabel='# PV',
ylabel='Events / 1', dology=False, ymax=9e5), weightname="weight_0_WpT_bin0_lepEta_bin0")
# lepton pt
sampMan.cacheDraw("Lep_pt", "histo_Lep_pt_"+lepname, pt_bins, DrawConfig(xmin=20, xmax=70,
xlabel='p_{T}(l) [GeV]', dology=False, ymax=1.05e5), weightname="weight_0_WpT_bin0_lepEta_bin0")
sampMan.cacheDraw("Lep_eta", "histo_Lep_eta_"+lepname, eta_bins, DrawConfig(xmin=-2.6, xmax=2.6,
xlabel='#eta (l) [GeV]', ylabel='Events / 1', dology=False, ymax=6e5), weightname="weight_0_WpT_bin0_lepEta_bin0")
sampMan.cacheDraw("Lep_phi", "histo_Lep_phi_"+lepname, 30, phimin, phimax, DrawConfig(xmin=phimin, xmax=phimax,xlabel='#phi (l) [GeV]', ylabel='Events / 1', dology=False, ymax=5e5), weightname="weight_0_WpT_bin0_lepEta_bin0")
sampMan.cacheDraw("Lep_pt", "histo_Lep_pt_"+lepname+"plus", pt_bins, DrawConfig(xmin=20, xmax=70,
xlabel='p_{T}(l) [GeV]', dology=False, ymax=6.05e4), weightname="weight_"+lepname+"plus_0_WpT_bin0_lepEta_bin0")
sampMan.cacheDraw("Lep_eta", "histo_Lep_eta_"+lepname+"plus", eta_bins, DrawConfig(xmin=-2.6, xmax=2.6,
xlabel='#eta (l) [GeV]', ylabel='Events / 1', dology=False, ymax=3.5e4), weightname="weight_"+lepname+"plus_0_WpT_bin0_lepEta_bin0")
sampMan.cacheDraw("Lep_phi", "histo_Lep_phi_"+lepname+"plus", 30, phimin, phimax, DrawConfig(xmin=phimin, xmax=phimax,xlabel='#phi (l) [GeV]', ylabel='Events / 1', dology=False, ymax=3e4), weightname="weight_"+lepname+"plus_0_WpT_bin0_lepEta_bin0")
sampMan.cacheDraw("Lep_pt", "histo_Lep_pt_"+lepname+"minus", pt_bins, DrawConfig(xmin=20, xmax=70,
xlabel='p_{T}(l) [GeV]', dology=False, ymax=5.05e4), weightname="weight_"+lepname+"minus_0_WpT_bin0_lepEta_bin0")
sampMan.cacheDraw("Lep_eta", "histo_Lep_eta_"+lepname+"minus", eta_bins, DrawConfig(xmin=-2.6, xmax=2.6,
xlabel='#eta (l) [GeV]', ylabel='Events / 1', dology=False, ymax=3e4), weightname="weight_"+lepname+"minus_0_WpT_bin0_lepEta_bin0")
sampMan.cacheDraw("Lep_phi", "histo_Lep_phi_"+lepname+"minus", 30, phimin, phimax, DrawConfig(xmin=phimin, xmax=phimax,xlabel='#phi (l) [GeV]', ylabel='Events / 1', dology=False, ymax=3e4), weightname="weight_"+lepname+"minus_0_WpT_bin0_lepEta_bin0")
# met and raw_met
sampMan.cacheDraw("met_1_pt", "histo_wjets_"+lepname+"_pfmet_pt", met_pt_bins, DrawConfig(xmin=0,
xmax=80, xlabel='PF MET [GeV]', dology=False, ymax=8e4), weightname="weight_0_WpT_bin0_lepEta_bin0")
sampMan.cacheDraw("met_1_phi", "histo_wjets_"+lepname+"_pfmet_phi", 30, phimin, phimax, DrawConfig(xmin=phimin,
xmax=phimax, xlabel='PF MET #phi', dology=False, ymax=6e5), weightname="weight_0_WpT_bin0_lepEta_bin0")
sampMan.cacheDraw("met_1_pt", "histo_wjets_"+lepname+"plus_pfmet_pt", met_pt_bins, DrawConfig(xmin=0,
xmax=80, xlabel='PF MET [GeV]', dology=False, ymax=5e4), weightname="weight_"+lepname+"plus_0_WpT_bin0_lepEta_bin0")
sampMan.cacheDraw("met_1_pt", "histo_wjets_"+lepname+"minus_pfmet_pt", met_pt_bins, DrawConfig(xmin=0,
xmax=80, xlabel='PF MET [GeV]', dology=False, ymax=5e4), weightname="weight_"+lepname+"minus_0_WpT_bin0_lepEta_bin0")
sampMan.cacheDraw("met_1_phi", "histo_wjets_"+lepname+"plus_pfmet_phi", 30, phimin, phimax, DrawConfig(xmin=phimin,
xmax=phimax, xlabel='PF MET #phi', dology=False, ymax=4e5), weightname="weight_"+lepname+"plus_0_WpT_bin0_lepEta_bin0")
sampMan.cacheDraw("met_1_phi", "histo_wjets_"+lepname+"minus_pfmet_phi", 30, phimin, phimax, DrawConfig(xmin=phimin,
xmax=phimax, xlabel='PF MET #phi', dology=False, ymax=4e5), weightname="weight_"+lepname+"minus_0_WpT_bin0_lepEta_bin0")
# raw MET without XY or recoil corrections
sampMan.cacheDraw("met_org_pt", "histo_wjets_"+lepname+"_rawmet_pt", met_pt_bins, DrawConfig(xmin=0,
xmax=80, xlabel='Raw MET [GeV]', dology=False, ymax=8e4), weightname="weight_0_WpT_bin0_lepEta_bin0")
sampMan.cacheDraw("met_org_phi", "histo_wjets_"+lepname+"_rawmet_phi", 30, phimin, phimax, DrawConfig(xmin=phimin,
xmax=phimax, xlabel='Raw MET #phi', dology=False, ymax=6e5), weightname="weight_0_WpT_bin0_lepEta_bin0")
# deltaPhi
sampMan.cacheDraw("deltaPhi", "histo_wjets_"+lepname+"_deltaphi", dphi_bins, DrawConfig(xmin=0, xmax=
2*phimax, xlabel='#Delta #phi(#mu, MET)', dology=False, ymax=2e6), weightname="weight_0_WpT_bin0_lepEta_bin0")
# mt
sampMan.cacheDraw("mtCorr", "histo_wjets_"+lepname+"_mtcorr", mt_bins, DrawConfig(xmin=0, xmax=120,
xlabel="m_{T} [GeV]", dology=False, ymax=7e4), weightname="weight_0_WpT_bin0_lepEta_bin0")
sampMan.cacheDraw("mtCorr", "histo_wjets_"+lepname+"plus_mtcorr", mt_bins, DrawConfig(xmin=0, xmax=120,
xlabel="m_{T} [GeV]", dology=False, ymax=4e4), weightname="weight_"+lepname+"plus_0_WpT_bin0_lepEta_bin0")
sampMan.cacheDraw("mtCorr", "histo_wjets_"+lepname+"minus_mtcorr", mt_bins, DrawConfig(xmin=0, xmax=120,
xlabel="m_{T} [GeV]", dology=False, ymax=3.5e4), weightname="weight_"+lepname+"minus_0_WpT_bin0_lepEta_bin0")
# wpt
sampMan.cacheDraw("WpT", "histo_wjets_"+lepname+"_wpt", 300, 0, 300, DrawConfig(xmin=0, xmax=300,
xlabel="p^{W}_{T} [GeV]", dology=True, ymax=1e6, ymin=1e1), weightname="weight_0_WpT_bin0_lepEta_bin0")
sampMan.cacheDraw("WpT", "histo_wjets_"+lepname+"plus_wpt", 300, 0, 300, DrawConfig(xmin=0, xmax=300,
xlabel="p^{W}_{T} [GeV]", dology=True, ymax=1e6, ymin=1e1), weightname="weight_"+lepname+"plus_0_WpT_bin0_lepEta_bin0")
sampMan.cacheDraw("WpT", "histo_wjets_"+lepname+"minus_wpt", 300, 0, 300, DrawConfig(xmin=0, xmax=300,
xlabel="p^{W}_{T} [GeV]", dology=True, ymax=1e6, ymin=1e1), weightname="weight_"+lepname+"minus_0_WpT_bin0_lepEta_bin0")
ymaxs = {lepname+"plus": 4e4, lepname+"minus": 3.5e4}
if is5TeV:
ymaxs = {lepname+"plus": 3e4, lepname+"minus": 2.5e4}
xmin = 0
xmax = 140
#
# templates and variations for combine
#
for chg in chgbins:
# variation on recoil corections
for i in [1, 2, 3, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16]:
for wpt in wptbins:
for lepeta in etabins:
sampMan.cacheDraw("mT_{}".format(str(i)), "histo_wjets_{}_mT_{}_{}_{}".format(chg, str(i), wpt, lepeta), mass_bins, DrawConfig(
xmin=xmin, xmax=xmax, xlabel="m_{T} [GeV]", dology=False, ymax=ymaxs[chg]*5.0, donormalizebin=False, addOverflow=False, addUnderflow=False), weightname="weight_{}_0_{}_{}".format(chg, wpt, lepeta))
# for signal MC, draw the histogram in different truth WpT bins
for wpttruth in wpttruthbins:
h_list = []
hname = "histo_wjets_{}_mT_{}_{}_{}_{}_signalMC".format(
chg, str(i), wpt, lepeta, wpttruth)
for isamp, samp in enumerate(signalSamps):
h_list.append(samp.rdf.Histo1D((hname+str(isamp), hname, mass_bins), "mT_{}".format(
str(i)), "weight_{}_0_{}_{}_{}".format(chg, wpt, lepeta, wpttruth)))
h_sigs[hname] = h_list
# variation on the scale factors and sample weights
for i in [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13]:
for wpt in wptbins:
for lepeta in etabins:
sampMan.cacheDraw("mT_1", f"histo_wjets_{chg}_mtcorr_weight_{i}_{wpt}_{lepeta}", mass_bins, DrawConfig(
xmin=xmin, xmax=xmax, xlabel="m_{T} [GeV]", dology=False, ymax=ymaxs[chg] * 5.0, donormalizebin=False, addOverflow=False, addUnderflow=False), weightname=f"weight_{chg}_{i}_{wpt}_{lepeta}")
# for signal MC, draw the histogram in different truth WpT bins
for wpttruth in wpttruthbins:
h_list = []
hname = "histo_wjets_{}_mtcorr_weight_{}_{}_{}_{}_signalMC".format(
chg, str(i), wpt, lepeta, wpttruth)
for isamp, samp in enumerate(signalSamps):
h_list.append(samp.rdf.Histo1D((hname+str(isamp), hname, mass_bins), "mT_1",
"weight_{}_{}_{}_{}_{}".format(chg, str(i), wpt, lepeta, wpttruth)))
h_sigs[hname] = h_list
# variations on the theory uncertainties
for wpt in wptbins:
for lepeta in etabins:
for var in theoryVariations.values():
sampMan.cacheDraw("mT_1", f"histo_wjets_{chg}_mtcorr_weight_{var}_{wpt}_{lepeta}", mass_bins, DrawConfig(
xmin=xmin, xmax=xmax, xlabel="m_{T} [GeV]", dology=False, ymax=ymaxs[chg] * 5.0, donormalizebin=False, addOverflow=False, addUnderflow=False), weightname=f"weight_{chg}_{var}_{wpt}_{lepeta}")
# Draw all these histograms
sampMan.launchDraw()
# sampMan.cacheDraw("WpT", "histo_wjets_"+lepname+"minus_wpt_test", 300, 0, 300, DrawConfig(xmin=0, xmax=300, xlabel="p^{W}_{T} [GeV]", dology=True, ymax=1e6, ymin=1e1), weightname="weight_"+lepname+"minus_0_WpT_bin0_lepEta_bin0")
# sampMan.launchDraw()
#
# draw the mT distributions of different processes for comparisons
#
for chg in chgbins:
for wpt in wptbins:
for lepeta in etabins:
labels = []
hists = []
hmcs = sampMan.hmcs["histo_wjets_{}_mT_1_{}_{}".format(
chg, wpt, lepeta)]
icolor = 1
for key, val in hmcs.items():
if any(x in key for x in ["WW", "WZ", "ZZ", "ttbar_0lepton", "ttbar_dilepton"]):
continue
labels.append(key)
hists.append(val)
val.SetLineColor(icolor)
val.SetMarkerColor(icolor)
icolor += 1
DrawHistos(hists, labels, xmin, xmax, "m_{T} [GeV]", 0., 0.24, "A.U.", "Comparison_mTShape_wjets_{}_mT_1_{}_{}".format(chg, wpt, lepeta), dology=False, addOverflow=True, addUnderflow=True, donormalize=True, is5TeV=is5TeV, legendPos=[0.30, 0.92, 0.90, 0.72], legendNCols=4, legendoptions="LE", drawoptions="LE", outdir="plots/" + outdir)
#
# merge the signal MC histograms in different samples
# mostly for WpT usage
#
def addSignals(hname):
h_list = h_sigs[hname]
hadded = h_list[0].Clone(hname)
# merge the signal MCs
for idx in range(1, len(h_list)):
hadded.Add(h_list[idx].GetValue())
return hadded
h_sigsMerged = OrderedDict()
for hname in list(h_sigs.keys()):
hadded = addSignals(hname)
h_sigsMerged[hname] = hadded
#
# preparing the outputs
#
dirpath = "root/" + outdir
if not os.path.exists(dirpath):
print(f"Make the directory {dirpath}")
os.makedirs(dirpath)
sqrtS = "5TeV" if is5TeV else "13TeV"
output_suffix = lepname + "nu"
if doWpT:
output_suffix += "_WpT"
output_suffix += f"_{sqrtS}"
if doTheoryNorm:
output_suffix += "_TheoryNormed.root"
else:
output_suffix += "_noTheoryNorm.root"
#
# write out mT histograms for combine
#
outfile = ROOT.TFile.Open(dirpath + "/output_shapes_"+output_suffix, "recreate")
# Data
# odir = outfile.mkdir("Data")
# outfile.cd("Data")
for chg in chgbins:
for wpt in wptbins:
for lepeta in etabins:
hdata = sampMan.hdatas["histo_wjets_{}_mT_1_{}_{}".format(
chg, wpt, lepeta)]
# hdata.SetDirectory(odir)
hdata.SetDirectory(outfile)
hdata.Write()
# MC
for wpttruth in ["MCTemplates"] + wpttruthbins:
# the 1st wpttruth bin is 'fake', for all MC templates
# the other wpttruth bins are for signal MC only
# odir = outfile.mkdir(wpttruth)
# outfile.cd(wpttruth)
for chg in chgbins:
for wpt in wptbins:
for lepeta in etabins:
if wpttruth == "MCTemplates":
hsmcs_central = sampMan.hsmcs["histo_wjets_{}_mT_1_{}_{}".format(
chg, wpt, lepeta)]
hlists_central = list(hsmcs_central.GetHists())
else:
# signal MC
hname = "histo_wjets_{}_mT_1_{}_{}_{}_signalMC".format(
chg, wpt, lepeta, wpttruth)
hlists_central = [h_sigsMerged[hname]]
# central values for MC
for ih in range(len(hlists_central)):
hcen = hlists_central[ih]
# hcen.SetDirectory(odir)
hcen.SetDirectory(outfile)
hcen.Write()
# recoil systematics
for i in [2, 3, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16]:
if wpttruth == "MCTemplates":
hsmcs_up = sampMan.hsmcs["histo_wjets_{}_mT_{}_{}_{}".format(
chg, str(i), wpt, lepeta)]
hlists_up = list(hsmcs_up.GetHists())
else:
# signal MC
hname = "histo_wjets_{}_mT_{}_{}_{}_{}_signalMC".format(
chg, str(i), wpt, lepeta, wpttruth)
hlists_up = [h_sigsMerged[hname]]
for ih in range(len(hlists_up)):
# loop over different simulated processes
hcen = hlists_central[ih]
hup = hlists_up[ih]
# if not doMuon and i !=2 and i!=3:
# if i!=2 and i!=3:
# suffix = lepname + "_" + lepeta + "_" + wpt + "_SysRecoil" + str(i)
# else:
# suffix = lepname + "_" + "SysRecoil" + str(i)
suffix = lepname + "_SysRecoil" + \
str(i) + "_" + sqrtS
hup.SetName("{}_{}Up".format(
hcen.GetName(), suffix))
hdn = hcen.Clone("{}_{}Down".format(
hcen.GetName(), suffix))
for ibin in range(1, hup.GetNbinsX()+1):
hdn.SetBinContent(
ibin, 2*hcen.GetBinContent(ibin) - hup.GetBinContent(ibin))
# hup.SetDirectory(odir)
hup.SetDirectory(outfile)
hup.Write()
# hdn.SetDirectory(odir)
hdn.SetDirectory(outfile)
hdn.Write()
# weights/corrections
for i in [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13]:
if wpttruth == "MCTemplates":
hsmcs_up = sampMan.hsmcs["histo_wjets_{}_mtcorr_weight_{}_{}_{}".format(
chg, str(i), wpt, lepeta)]
hlists_up = list(hsmcs_up.GetHists())
else:
# signal MC
hname = "histo_wjets_{}_mtcorr_weight_{}_{}_{}_{}_signalMC".format(
chg, str(i), wpt, lepeta, wpttruth)
hlists_up = [h_sigsMerged[hname]]
for ih in range(len(hlists_up)):
# loop over different processes
hcen = hlists_central[ih]
hup = hlists_up[ih]
prefix = ""
if i == 2 or i == 3 or i == 4 or i == 12 or i == 13:
# the systematics that should be decorrelated between lepton flavors
prefix = lepname + "_"
if i == 5:
# stat unc, decorrelate the plus and minus
prefix = chg + "_"
if i <= 6 or i == 8 or i == 10 or i == 12 or i == 13:
suffix = prefix + "SysWeight" + \
str(i) + "_" + sqrtS
# hup.SetName("{}_SysWeight{}Up".format(hcen.GetName(), str(i)))
hup.SetName("{}_{}Up".format(
hcen.GetName(), suffix))
else:
suffix = prefix + "SysWeight" + \
str(i-1) + "_" + sqrtS
# hup.SetName("{}_SysWeight{}Down".format(hcen.GetName(), str(i-1)))
hup.SetName("{}_{}Down".format(
hcen.GetName(), suffix))
if i < 6 or i == 12 or i == 13:
# for prefire, the up and down weights are calculated seperately
suffix = prefix + "SysWeight" + \
str(i) + "_" + sqrtS
# hdn = hcen.Clone("{}_SysWeight{}Down".format(hcen.GetName(), str(i)))
hdn = hcen.Clone("{}_{}Down".format(
hcen.GetName(), suffix))
for ibin in range(1, hup.GetNbinsX()+1):
hdn.SetBinContent(
ibin, 2*hcen.GetBinContent(ibin) - hup.GetBinContent(ibin))
# hup.SetDirectory(odir)
hup.SetDirectory(outfile)
hup.Write()
if i < 6 or i == 12 or i == 13:
# hdn.SetDirectory(odir)
hdn.SetDirectory(outfile)
hdn.Write()
# pdf, alphaS, and QCD scale uncertainties
for sysname, var in theoryVariations.items():
if wpttruth == "MCTemplates":
hsmcs_up = sampMan.hsmcs[f"histo_wjets_{chg}_mtcorr_weight_{var}_{wpt}_{lepeta}"]
hlists_up = list(hsmcs_up.GetHists())
else:
continue
for ih in range(len(hlists_up)):
# loop over different processes
hcen = hlists_central[ih]
hup = hlists_up[ih]
suffix = sqrtS + "_" + sysname
hup.SetName("{}_{}".format(hcen.GetName(), suffix))
if doTheoryNorm:
# normalize the number of events to the central values
# if the theoretical variations are normalized
# ONLY for the signals
if signame in hcen.GetName():
hup.Scale(hcen.Integral(
0, 1000000) / hup.Integral(0, 1000000))
if "PDF" or "alphaS" in sysname:
# prepare the down variation
# alphaS down variation is not saved in W + jets samples
# use the symmetrized up variation instead
suffix = sqrtS + "_" + \
sysname.replace("Up", "Down")
hdn = hcen.Clone("{}_{}".format(
hcen.GetName(), suffix))
for ibin in range(1, hup.GetNbinsX()+1):
hdn.SetBinContent(
ibin, 2*hcen.GetBinContent(ibin) - hup.GetBinContent(ibin))
hdn.SetDirectory(outfile)
hdn.Write()
hup.SetDirectory(outfile)
hup.Write()
outfile.Close()
#
# save all the unstacked mc histograms for understanding and debugging
#
outfile = ROOT.TFile.Open(
"root/output_sigshapes_"+output_suffix, "recreate")
for chg in chgbins:
for wpt in wptbins:
for lepeta in etabins:
hmcs = sampMan.hmcs["histo_wjets_{}_mT_1_{}_{}".format(
chg, wpt, lepeta)]
for key, val in hmcs.items():
val.SetDirectory(outfile)
val.Write()
outfile.Close()
sampMan.dumpCounts()
print("Program end...")
# input()
return
if __name__ == "__main__":
main()