def main():
print "Program start..."
#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 dotest:
input_data = "inputs/zmumu/input_data.txt"
input_dy = "inputs/zmumu/input_zjets.txt"
input_ttbar = "inputs/zmumu/input_ttbar_dilepton.txt"
else:
input_data = "inputs/zmumu/input_data.txt"
input_dy = "inputs/zmumu/input_zjets.txt"
input_ttbar = "inputs/zmumu/input_ttbar_dilepton.txt"
input_ttbar_1lep = "inputs/zmumu/input_ttbar_singlelepton.txt"
input_ttbar_0lep = "inputs/zmumu/input_ttbar_hadronic.txt"
input_ww = "inputs/zmumu/input_ww.txt"
input_wz = "inputs/zmumu/input_wz.txt"
input_zz = "inputs/zmumu/input_zz.txt"
input_zxx = "inputs/zmumu/input_zxx.txt"
DataSamp = Sample(input_data,
isMC=False,
legend="Data",
name="Data",
bjetVeto=VetoB)
DYSamp = Sample(input_dy,
xsec=6077.22 * 1e3,
color=92,
reweightzpt=True,
legend="Z#rightarrow#mu#mu",
name="DY",
bjetVeto=VetoB,
nmcevt=311461009200.830078 / 128007. * 126620.8)
TTbarSamp = Sample(input_ttbar,
xsec=831.76 * 0.105 * 1e3,
color=46,
reweightzpt=False,
legend="t#bar{t}",
name="ttbar2lep",
bjetVeto=VetoB,
nmcevt=360411094.548295 / 335.0 * 325.0)
if not dotest:
WWSamp = Sample(input_ww,
xsec=12.178 * 1e3,
color=38,
reweightzpt=False,
legend="WW2L",
name="WW",
bjetVeto=VetoB,
nmcevt=1000000.0)
WZSamp = Sample(input_wz,
xsec=5.26 * 1e3,
color=39,
reweightzpt=False,
legend="WZ3L",
name="WZ",
bjetVeto=VetoB,
nmcevt=885000.00)
ZZSamp = Sample(input_zz,
xsec=0.564 * 1e3,
color=37,
reweightzpt=False,
legend="ZZ2L",
name="ZZ",
bjetVeto=VetoB,
nmcevt=1000000.0)
ZXXSamp = Sample(input_zxx,
xsec=1.0,
color=40,
reweightzpt=False,
legend="ZXX",
name="ZXX",
bjetVeto=VetoB,
nmcevt=3.1146101e+11)
TT1LepSamp = Sample(input_ttbar_1lep,
xsec=831.76 * 0.219 * 1e3,
color=47,
reweightzpt=False,
legend="t#bar{t}",
name="ttbar1lep",
bjetVeto=VetoB,
nmcevt=1.2561491e+09 / 335.0 * 325.0)
TT0LepSamp = Sample(input_ttbar_0lep,
xsec=831.76 * 0.219 * 1e3,
color=48,
reweightzpt=False,
legend="t#bar{t}",
name="ttbar0lep",
bjetVeto=VetoB,
nmcevt=6.2414786e+09 / 335.0 * 325)
if not dotest:
sampMan = SampleManager(DataSamp, [
DYSamp, TTbarSamp, WWSamp, WZSamp, ZZSamp, ZXXSamp, TT1LepSamp,
TT0LepSamp
])
else:
sampMan = SampleManager(DataSamp, [DYSamp, TTbarSamp])
sampMan.groupMCs(["WW", "WZ", "ZZ", "ZXX"], "EWK", 216, "EWK")
sampMan.groupMCs(["ttbar2lep", "ttbar1lep", "ttbar0lep"], "ttbar", 96,
"t#bar{t}")
sampMan.DefineAll("zpt", "Z.Pt()")
sampMan.DefineAll("zmass", "ZMass")
sampMan.DefineAll("zy", "Z.Rapidity()")
sampMan.DefineAll("zeta", "Z.Rapidity()")
sampMan.DefineAll("zphi", "Z.Phi()")
sampMan.DefineAll("urawvec", "UVec(zpt, zphi, met_raw_pt, met_raw_phi)")
sampMan.DefineAll("uraw_pt", "urawvec.Mod()")
sampMan.DefineAll("uraw_phi", "urawvec.Phi()")
sampMan.DefineAll("uraw1",
"uraw_pt * TMath::Cos(uraw_phi + TMath::Pi() - zphi)")
sampMan.DefineAll("uraw2",
"uraw_pt * TMath::Sin(uraw_phi + TMath::Pi() - zphi)")
sampMan.DefineAll("uvec",
"UVec(zpt, zphi, met_corrected_pt, met_corrected_phi)")
sampMan.DefineAll("u_pt", "uvec.Mod()")
sampMan.DefineAll("u_phi", "uvec.Phi()")
sampMan.DefineAll("ucor1", "u_pt * TMath::Cos(u_phi + TMath::Pi() - zphi)")
sampMan.DefineAll("ucor2", "u_pt * TMath::Sin(u_phi + TMath::Pi() - zphi)")
sampMan.DefineAll("nPV", "npv")
sampMan.DefineAll("m1pt", "lep1_corr.Pt()")
sampMan.DefineAll("m1eta", "lep1_corr.Eta()")
sampMan.DefineAll("m2pt", "lep2_corr.Pt()")
sampMan.DefineAll("m2eta", "lep2_corr.Eta()")
sampMan.DefineAll("LeadMuon_pt", "(m1pt > m2pt ? m1pt : m2pt)")
sampMan.DefineAll("LeadMuon_eta", "(m1pt > m2pt ? m1eta : m2eta)")
sampMan.DefineAll("SubleadMuon_pt", "(m1pt > m2pt ? m2pt : m1pt)")
sampMan.DefineAll("SubleadMuon_eta", "(m1pt > m2pt ? m2eta : m1eta)")
#DYSamp.Define("u_pt_corr_central", "TMath::Sqrt(u1_corr_central*u1_corr_central + u2_corr_central*u2_corr_central)")
#sampMan.DefineAll("u1_corr_central", "u1" , excludes=['DY'])
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, 90, 100, 110, 120, 135,
150, 165, 180, 200
])
u1_bins = np.array([
-20.0, -16, -12, -10, -8, -6, -4, -2, 0, 2, 4, 6, 8, 10, 12, 14, 16,
18, 20, 22, 24, 26, 28, 30, 32, 34, 36, 38, 40, 42, 44, 46, 48, 50, 53,
56, 59, 64, 68, 72, 76, 80, 85, 90, 100
])
u2_bins = np.array([
-40, -35, -30, -25., -22., -20, -18, -16, -14, -12, -10, -8, -6, -4,
-2, 0, 2, 4, 6, 8, 10, 12, 16, 18, 20, 22, 25, 30, 35, 40
])
#u_bins = np.array([0., 2., 4., 6, 8, 10, 12, 14, 16, 18, 20, 22, 24, 26, 28, 30, 32, 34, 36, 38, 40, 43, 46, 49, 52, 56, 60, 64, 68, 72, 76, 80, 85, 90, 95, 100, 105, 110, 115, 120, 130, 140, 150])
phimin = -ROOT.TMath.Pi()
phimax = ROOT.TMath.Pi()
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)))
u_bins = np.concatenate((np.linspace(0, 20, 11), np.linspace(24, 80, 15),
np.linspace(85, 109, 4), np.linspace(120, 150,
3)))
# z pt befor and after pt reweighting
sampMan.cacheDraw("zpt",
"histo_zjets_zpt_WoZptWeight_mumu",
u_bins,
DrawConfig(xmin=0,
xmax=150,
xlabel='p_{T}^{#mu#mu} [GeV]'),
weightname="weight_WoVpt")
sampMan.cacheDraw("zmass", "histo_zjets_zmass_mumu", mass_bins,
DrawConfig(xmin=70, xmax=110, xlabel='m_{#mu#mu} [GeV]'))
sampMan.cacheDraw(
"zeta", "histo_zjets_zeta_mumu", eta_bins,
DrawConfig(xmin=-2.5,
xmax=2.5,
xlabel='#eta_{#mu#mu} [GeV]',
ymax=1e7,
ylabel='Events / 1'))
sampMan.cacheDraw(
"zy", "histo_zjets_zrapidity_mumu", eta_bins,
DrawConfig(xmin=-2.5,
xmax=2.5,
xlabel='y_{#mu#mu} [GeV]',
ymax=1e7,
ylabel='Events / 1'))
sampMan.cacheDraw(
"nPV", "histo_nPV_mumu", 10, 0, 10,
DrawConfig(xmin=0, xmax=10, xlabel='# PV', ylabel='Events / 1'))
sampMan.cacheDraw(
"LeadMuon_pt", "histo_leadMuon_pt_mumu", pt_bins,
DrawConfig(xmin=20, xmax=70, xlabel='p_{T}(Leading #mu) [GeV]'))
sampMan.cacheDraw(
"LeadMuon_eta", "histo_leadMuon_eta_mumu", eta_bins,
DrawConfig(xmin=-2.6,
xmax=2.6,
xlabel='#eta (Leading #mu) [GeV]',
ymax=1e7,
ylabel='Events / 1'))
sampMan.cacheDraw(
"SubleadMuon_pt", "histo_subleadMuon_pt_mumu", pt_bins,
DrawConfig(xmin=20, xmax=70, xlabel='p_{T}(Subleading #mu) [GeV]'))
sampMan.cacheDraw(
"SubleadMuon_eta", "histo_subleadMuon_eta_mumu", eta_bins,
DrawConfig(xmin=-2.6,
xmax=2.6,
xlabel='#eta (Subleading #mu) [GeV]',
ymax=1e7,
ylabel='Events / 1'))
sampMan.cacheDraw("met", "histo_zjets_mumu_pfmet_pt", met_pt_bins,
DrawConfig(xmin=0, xmax=100, xlabel='PF MET [GeV]'))
sampMan.cacheDraw(
"metPhi", "histo_zjets_mumu_pfmet_phi", 30, phimin, phimax,
DrawConfig(xmin=phimin, xmax=phimax, xlabel='PF MET #phi'))
sampMan.cacheDraw("met_raw_pt", "histo_zjets_mumu_pfmet_raw_pt",
met_pt_bins,
DrawConfig(xmin=0, xmax=100, xlabel='Raw PF MET [GeV]'))
sampMan.cacheDraw(
"met_raw_phi", "histo_zjets_mumu_pfmet_raw_phi", 30, phimin, phimax,
DrawConfig(xmin=phimin, xmax=phimax, xlabel='Raw PF MET #phi'))
sampMan.cacheDraw("met_wlepcorr_pt", "histo_zjets_mumu_pfmet_wlepcorr_pt",
met_pt_bins,
DrawConfig(xmin=0, xmax=100, xlabel='PF MET [GeV]'))
sampMan.cacheDraw(
"met_wlepcorr_phi", "histo_zjets_mumu_pfmet_wlepcorr_phi", 30, phimin,
phimax, DrawConfig(xmin=phimin, xmax=phimax, xlabel='PF MET #phi'))
sampMan.cacheDraw("met_corrected_pt",
"histo_zjets_mumu_pfmet_corrected_pt", met_pt_bins,
DrawConfig(xmin=0, xmax=100, xlabel='PF MET [GeV]'))
sampMan.cacheDraw(
"met_corrected_phi", "histo_zjets_mumu_pfmet_corrected_phi", 30,
phimin, phimax,
DrawConfig(xmin=phimin, xmax=phimax, xlabel='PF MET #phi'))
sampMan.cacheDraw(
"uraw1", "histo_zjets_mumu_pfmet_uraw1_pt", u1_bins,
DrawConfig(xmin=-20.0,
xmax=100.0,
xlabel="Raw u_{#parallel} [GeV]",
extraText='#mu#mu channel'))
sampMan.cacheDraw(
"uraw2", "histo_zjets_mumu_pfmet_uraw2_pt", u2_bins,
DrawConfig(xmin=-30.0,
xmax=30.0,
xlabel="Raw u_{#perp } [GeV]",
extraText='#mu#mu channel'))
sampMan.cacheDraw(
"ucor1", "histo_zjets_mumu_pfmet_ucor1_pt", u1_bins,
DrawConfig(xmin=-20.0,
xmax=100.0,
xlabel="u_{#parallel} [GeV]",
extraText='#mu#mu channel'))
sampMan.cacheDraw(
"ucor2", "histo_zjets_mumu_pfmet_ucor2_pt", u2_bins,
DrawConfig(xmin=-30.0,
xmax=30.0,
xlabel="u_{#perp } [GeV]",
extraText='#mu#mu channel'))
sampMan.launchDraw()
sampMan.dumpCounts()
print "Program end..."
raw_input()
return
def main():
print "Program start..."
#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 doMuon:
input_antiiso_data = "inputs/awmunu/input_data.txt"
input_antiiso_wl0 = "inputs/awmunu/input_wm0.txt"
input_antiiso_wl1 = "inputs/awmunu/input_wm1.txt"
input_antiiso_wl2 = "inputs/awmunu/input_wm2.txt"
input_antiiso_ttbar = "inputs/awmunu/input_ttbar_dilepton.txt"
input_antiiso_ttbar_1lep = "inputs/awmunu/input_ttbar_singlelepton.txt"
input_antiiso_ttbar_0lep = "inputs/awmunu/input_ttbar_hadronic.txt"
input_antiiso_ww = "inputs/awmunu/input_ww.txt"
input_antiiso_wz = "inputs/awmunu/input_wz.txt"
input_antiiso_zz = "inputs/awmunu/input_zz.txt"
input_antiiso_zxx = "inputs/awmunu/input_zxx.txt"
input_antiiso_wx0 = "inputs/awmunu/input_wx0.txt"
input_antiiso_wx1 = "inputs/awmunu/input_wx1.txt"
input_antiiso_wx2 = "inputs/awmunu/input_wx2.txt"
else:
input_antiiso_data = "inputs/awenu/input_data.txt"
input_antiiso_wl0 = "inputs/awenu/input_we0.txt"
input_antiiso_wl1 = "inputs/awenu/input_we1.txt"
input_antiiso_wl2 = "inputs/awenu/input_we2.txt"
input_antiiso_ttbar = "inputs/awenu/input_ttbar_dilepton.txt"
input_antiiso_ttbar_1lep = "inputs/awenu/input_ttbar_singlelepton.txt"
input_antiiso_ttbar_0lep = "inputs/awenu/input_ttbar_hadronic.txt"
input_antiiso_ww = "inputs/awenu/input_ww.txt"
input_antiiso_wz = "inputs/awenu/input_wz.txt"
input_antiiso_zz = "inputs/awenu/input_zz.txt"
input_antiiso_zxx = "inputs/awenu/input_zxx.txt"
input_antiiso_wx0 = "inputs/awenu/input_wx0.txt"
input_antiiso_wx1 = "inputs/awenu/input_wx1.txt"
input_antiiso_wx2 = "inputs/awenu/input_wx2.txt"
## for the QCD background estimation (data-driven)
qcdnorm = -1.0
DataAisoSamp = Sample(input_antiiso_data,
isMC=False,
name="Data_aiso",
isWSR=True,
additionalnorm=-1.0 * qcdnorm,
legend='QCD',
color='226')
# W -> lnu
Wl0AisoSamp = Sample(input_antiiso_wl0,
isMC=True,
name="wl0_aiso",
isWSR=True,
additionalnorm=-1.0 * qcdnorm)
Wl1AisoSamp = Sample(input_antiiso_wl1,
isMC=True,
name="wl1_aiso",
isWSR=True,
additionalnorm=-1.0 * qcdnorm)
Wl2AisoSamp = Sample(input_antiiso_wl2,
isMC=True,
name="wl2_aiso",
isWSR=True,
additionalnorm=-1.0 * qcdnorm)
# ttbar
TTbarAisoSamp = Sample(input_antiiso_ttbar,
isMC=True,
name="ttbar_dilepton_aiso",
isWSR=True,
additionalnorm=-1.0 * qcdnorm)
TT1LepAisoSamp = Sample(input_antiiso_ttbar_1lep,
isMC=True,
name="ttbar_1lepton_aiso",
isWSR=True,
additionalnorm=-1.0 * qcdnorm)
TT0LepAisoSamp = Sample(input_antiiso_ttbar_0lep,
isMC=True,
name="ttbar_0lepton_aiso",
isWSR=True,
additionalnorm=-1.0 * qcdnorm)
## dibosons
WWAisoSamp = Sample(input_antiiso_ww,
isMC=True,
name="WW_aiso",
isWSR=True,
additionalnorm=-1.0 * qcdnorm)
WZAisoSamp = Sample(input_antiiso_wz,
isMC=True,
name="WZ_aiso",
isWSR=True,
additionalnorm=-1.0 * qcdnorm)
ZZAisoSamp = Sample(input_antiiso_zz,
isMC=True,
name="ZZ_aiso",
isWSR=True,
additionalnorm=-1.0 * qcdnorm)
# tau
ZXXAisoSamp = Sample(input_antiiso_zxx,
isMC=True,
name="ZXX_aiso",
isWSR=True,
additionalnorm=-1.0 * qcdnorm)
Wx0AisoSamp = Sample(input_antiiso_wx0,
isMC=True,
name="wx0_aiso",
isWSR=True,
additionalnorm=-1.0 * qcdnorm)
Wx1AisoSamp = Sample(input_antiiso_wx1,
isMC=True,
name="wx1_aiso",
isWSR=True,
additionalnorm=-1.0 * qcdnorm)
Wx2AisoSamp = Sample(input_antiiso_wx2,
isMC=True,
name="wx2_aiso",
isWSR=True,
additionalnorm=-1.0 * qcdnorm)
sampMan = SampleManager(DataAisoSamp, [
Wl0AisoSamp, Wl1AisoSamp, Wl2AisoSamp, TTbarAisoSamp, TT1LepAisoSamp,
TT0LepAisoSamp, WWAisoSamp, WZAisoSamp, ZZAisoSamp, ZXXAisoSamp,
Wx0AisoSamp, Wx1AisoSamp, Wx2AisoSamp
])
sampMan.groupMCs([
"WW_aiso", "WZ_aiso", "ZZ_aiso", "ZXX_aiso", "wx0_aiso", "wx1_aiso",
"wx2_aiso"
], "EWK", 216, "EWK")
sampMan.groupMCs(
["ttbar_dilepton_aiso", "ttbar_1lepton_aiso", "ttbar_0lepton_aiso"],
"ttbar", 96, "t#bar{t}")
label = "W#rightarrow#mu#nu" if doMuon else "W#rightarrow e#nu"
sampMan.groupMCs(['wl0_aiso', 'wl1_aiso', 'wl2_aiso'], "wlnu", 92, label)
sampMan.DefineAll("Lep_pt", "lep.Pt()")
sampMan.ApplyCutAll("Lep_pt > 25.0")
sampMan.DefineAll("w_iso1", "(relIso > 0.15 && relIso < 0.30)")
sampMan.DefineAll("w_iso2", "(relIso > 0.30 && relIso < 0.45)")
sampMan.DefineAll("w_iso3", "(relIso > 0.45 && relIso < 0.55)")
sampMan.DefineAll("w_iso4", "(relIso > 0.55 && relIso < 0.65)")
# muon and electron isolation distributions are different
# more coarse binning for electrons to make sure enough statistics
if doMuon:
sampMan.DefineAll("w_iso5", "(relIso > 0.20 && relIso < 0.25)")
sampMan.DefineAll("w_iso6", "(relIso > 0.25 && relIso < 0.30)")
sampMan.DefineAll("w_iso7", "(relIso > 0.30 && relIso < 0.35)")
sampMan.DefineAll("w_iso8", "(relIso > 0.35 && relIso < 0.40)")
sampMan.DefineAll("w_iso9", "(relIso > 0.40 && relIso < 0.45)")
sampMan.DefineAll("w_iso10", "(relIso > 0.45 && relIso < 0.50)")
sampMan.DefineAll("w_iso11", "(relIso > 0.50 && relIso < 0.55)")
sampMan.DefineAll("w_iso12", "(relIso > 0.55 && relIso < 0.60)")
sampMan.DefineAll("w_iso13", "(relIso > 0.60 && relIso < 0.65)")
isobins = [
"iso1", "iso2", "iso3", "iso4", "iso5", "iso6", "iso7", "iso8",
"iso9", "iso10", "iso11", "iso12", "iso13"
]
else:
sampMan.DefineAll("w_iso5", "(relIso > 0.20 && relIso < 0.25)")
sampMan.DefineAll("w_iso6", "(relIso > 0.25 && relIso < 0.30)")
sampMan.DefineAll("w_iso7", "(relIso > 0.30 && relIso < 0.35)")
sampMan.DefineAll("w_iso8", "(relIso > 0.35 && relIso < 0.40)")
sampMan.DefineAll("w_iso9", "(relIso > 0.40 && relIso < 0.50)")
sampMan.DefineAll("w_iso10", "(relIso > 0.50 && relIso < 0.70)")
isobins = [
"iso1", "iso2", "iso3", "iso4", "iso5", "iso6", "iso7", "iso8",
"iso9", "iso10"
]
sampMan.DefineAll("Lep_eta", "lep.Eta()")
sampMan.DefineMC("met_pt", "metVars[1]", excludes=['Data_aiso'])
sampMan.DefineMC("met_phi",
"TVector2::Phi_mpi_pi(metVarsPhi[1])",
excludes=['Data_aiso'])
# Data does not run any recoil corrections
DataAisoSamp.Define("met_pt", "metVars[0]")
DataAisoSamp.Define("met_phi", "TVector2::Phi_mpi_pi(metVarsPhi[0])")
sampMan.DefineAll("met_raw_pt", "metVars[0]")
sampMan.DefineAll("met_raw_phi", "TVector2::Phi_mpi_pi(metVarsPhi[0])")
#sampMan.DefineAll("weight_wplus", "weight_WoVpt * (q>0)", excludeGroups=['QCD'])
#sampMan.DefineAll("weight_wminus", "weight_WoVpt * (q<0)", excludeGroups=['QCD'])
#sampMan.DefineSpecificMCs("weight_wplus", "weight_WoVpt * (q>0)", sampgroupnames=['QCD'])
#sampMan.DefineSpecificMCs("weight_wminus", "weight_WoVpt * (q<0)", sampgroupnames=['QCD'])
sampMan.DefineAll("weight_wplus", "weight_WoVpt * (q>0)")
sampMan.DefineAll("weight_wminus", "weight_WoVpt * (q<0)")
#sampMan.DefineAll("weight_eta0to0p8", "fabs(Lep_eta)<0.8")
#sampMan.DefineAll("weight_eta0p8to1p4", "fabs(Lep_eta)>0.8 && fabs(Lep_eta)<1.4")
#sampMan.DefineAll("weight_eta1p4to2", "fabs(Lep_eta)<1.4 && fabs(Lep_eta)<2.0")
#sampMan.DefineAll("weight_eta2to2p4", "fabs(Lep_eta)>2.0 && fabs(Lep_eta)<2.4")
# recoil variables
sampMan.DefineAll("V2W", "UVec(lep.Pt(), lep.Phi(), met_pt, met_phi)")
sampMan.DefineAll("WpT", "V2W.Mod()")
sampMan.DefineAll("Wphi", "TVector2::Phi_mpi_pi(V2W.Phi())")
# WpT bins
sampMan.DefineAll("WpT_bin0", "WpT>0.0")
sampMan.DefineAll("WpT_bin1", "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")
wptbins = [
"WpT_bin0", "WpT_bin1", "WpT_bin2", "WpT_bin3", "WpT_bin4", "WpT_bin5",
"WpT_bin6", "WpT_bin7", "WpT_bin8"
]
# 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"]
# pT_ell / mT
sampMan.DefineAll("ptOvermT", "Lep_pt / mtCorr")
#for iso in ['iso1', 'iso2', 'iso3', 'iso4', 'iso5', 'iso6', 'iso7', 'iso8', 'iso9', 'iso10', 'iso11', 'iso12', 'iso13']:
for iso in isobins:
for chg in ['WoVpt', 'wplus', 'wminus']:
#for eta in ['0to0p8', '0p8to1p4', '1p4to2', '2to2p4']:
#for wpt in ["WpT_bin0", "WpT_bin1", "WpT_bin2", "WpT_bin3", "WpT_bin4", "WpT_bin5", "WpT_bin6", "WpT_bin7", "WpT_bin8"]:
for wpt in wptbins:
for lepeta in etabins:
sampMan.DefineAll(
"weight_{}_{}_{}_{}".format(chg, iso, wpt, lepeta),
"w_{} * weight_{} * {} * {}".format(
iso, chg, wpt, lepeta))
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, 90, 100, 110, 120, 135,
150, 165, 180, 200
])
u1_bins = np.array([
-40., -36., -32., -28., -25., -22.0, -20.0, -18, -16, -14, -12, -10,
-8, -6, -4, -2, 0, 2, 4, 6, 8, 10, 12, 14, 16, 18, 20, 22, 24, 26, 28,
30, 32, 34, 36, 38, 40, 42, 44, 46, 48, 50, 53, 56, 59, 64, 68, 72, 76,
80, 85, 90, 100
])
u2_bins = np.array([
-80., -70., -65., -60., -56., -52, -48, -44, -40, -37, -34, -31, -28,
-25., -22., -20, -18, -16, -14, -12, -10, -8, -6, -4, -2, 0, 2, 4, 6,
8, 10, 12, 16, 18, 20, 22, 25, 28, 31, 34, 37, 40, 44, 48, 52, 56, 60,
65, 70, 80
])
#u_bins = np.array([0., 2., 4., 6, 8, 10, 12, 14, 16, 18, 20, 22, 24, 26, 28, 30, 32, 34, 36, 38, 40, 43, 46, 49, 52, 56, 60, 64, 68, 72, 76, 80, 85, 90, 95, 100, 105, 110, 115, 120, 130, 140, 150])
u_bins = np.concatenate((np.linspace(0, 20, 11), np.linspace(24, 60, 10)))
phimin = -ROOT.TMath.Pi()
phimax = ROOT.TMath.Pi()
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(0, 15, 6), np.linspace(17, 23, 4), np.linspace(25, 35, 6),
np.linspace(36, 55, 20), np.linspace(57, 63,
4), np.linspace(66, 70, 2),
np.linspace(75, 100, 6)))
mass_bins = np.concatenate(
(np.linspace(0, 52, 14), np.linspace(55, 67,
5), 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)))
u_bins = np.concatenate((np.linspace(0, 20, 11), np.linspace(24, 80, 15),
np.linspace(85, 109, 4), np.linspace(120, 150,
3)))
mt_bins = np.concatenate(
(np.linspace(0, 20, 6), np.linspace(22, 38,
9), np.linspace(40, 60, 21),
np.linspace(62, 80, 10), np.linspace(84, 120, 10)))
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
])
#for iso in ['iso1', 'iso2', 'iso3', 'iso4', 'iso5', 'iso6', 'iso7', 'iso8', 'iso9']:
#for iso in ['iso1', 'iso2', 'iso3', 'iso4', 'iso5', 'iso6', 'iso7', 'iso8', 'iso9', 'iso10', 'iso11', 'iso12', 'iso13']:
for iso in isobins:
for chg in ['WoVpt', 'wplus', 'wminus']:
#for wpt in ["WpT_bin0", "WpT_bin1", "WpT_bin2", "WpT_bin3", "WpT_bin4", "WpT_bin5", "WpT_bin6", "WpT_bin7", "WpT_bin8"]:
for wpt in wptbins:
for lepeta in etabins:
if chg == 'WoVpt':
continue
strname = "weight_{}_{}_{}_{}".format(
chg, iso, wpt, lepeta)
#outputname = "histo_wjetsAntiIso_mtcorr_" + strname
##sampMan.cacheDraw("mtCorr", outputname, mt_bins, DrawConfig(xmin=0, xmax=120, xlabel="m_{T} [GeV]", dology=False, ymax=1.0e4), weightname = strname)
#sampMan.cacheDraw("mtCorr", outputname, 25, 40, 140, DrawConfig(xmin=40, xmax=140, xlabel="m_{T} [GeV]", dology=False, ymax=1e4, donormalizebin=False, addOverflow=False, addUnderflow=False, showratio=True), weightname = strname)
outputname = "histo_wjetsAntiIso_fullrange_mtcorr_" + strname
sampMan.cacheDraw("mtCorr",
outputname,
70,
0,
140,
DrawConfig(xmin=0,
xmax=140,
xlabel="m_{T} [GeV]",
dology=False,
ymax=2e4,
donormalizebin=False,
addOverflow=False,
addUnderflow=False,
showratio=True),
weightname=strname)
#outputname = "histo_wjetsAntiIso_WpTcorr_" + strname
#sampMan.cacheDraw("WpT", outputname, u_bins, DrawConfig(xmin=0, xmax=60, xlabel="p^{W}_{T} [GeV]", dology=False, ymax=1.0e4), weightname = strname)
#outputname = "histo_wjetsAntiIso_leppt_" + strname
#sampMan.cacheDraw("Lep_pt", outputname, pt_bins, DrawConfig(xmin=25, xmax=100, xlabel="p^{#mu}_{T} [GeV]", dology=False, ymax=1.0e4), weightname = strname)
#outputname = "histo_wjetsAntiIso_metpt_" + strname
#sampMan.cacheDraw("met_pt", outputname, met_pt_bins, DrawConfig(xmin=0, xmax=80, xlabel="PF MET [GeV]", dology=False, ymax=1e4), weightname = strname)
sampMan.launchDraw()
#hmts_comp = OrderedDict()
##for iso in ['iso1', 'iso2', 'iso3', 'iso4', 'iso5', 'iso6', 'iso7', 'iso8', 'iso9']:
#for iso in ['iso1', 'iso2', 'iso3', 'iso4', 'iso5', 'iso6', 'iso7', 'iso8', 'iso9', 'iso10', 'iso11', 'iso12', 'iso13']:
# for chg in ['WoVpt', 'wplus', 'wminus']:
# for wpt in ["WpT_bin0", "WpT_bin1", "WpT_bin2", "WpT_bin3", "WpT_bin4", "WpT_bin5", "WpT_bin6", "WpT_bin7", "WpT_bin8"]:
# for lepeta in etabins:
# if chg == "WoVpt":
# continue
# strname = "weight_{}_{}_{}_{}".format(chg, iso, wpt, lepeta)
# outputname = "histo_wjetsAntiIso_mtcorr_" + strname
# hstacked = THStack2TH1(sampMan.hsmcs[outputname])
# for ibin in xrange(hstacked.GetNbinsX()+1):
# # hstacked should always be above 0
# hstacked.SetBinContent(ibin, max(hstacked.GetBinContent(ibin), 0))
# sampMan.hdatas[outputname].Add( hstacked, -1.0 )
# hmts_comp[strname] = sampMan.hdatas[outputname]
# hmts_comp[strname].SetName(outputname)
#outfile = ROOT.TFile("output_qcdshape.root", "recreate")
#for chg in ["wplus", "wminus"]:
# for i in xrange(1,13):
# for wpt in ["WpT_bin0", "WpT_bin1", "WpT_bin2", "WpT_bin3", "WpT_bin4", "WpT_bin5", "WpT_bin6", "WpT_bin7", "WpT_bin8"]:
# iso = "iso" + str(i)
# iso_next = "iso" + str(i+1)
# strname = "weight_{}_{}_{}".format(chg, iso, wpt)
# strname_next = "weight_{}_{}_{}".format(chg, iso_next, wpt)
# outputname = "histo_wjetsAntiIso_mtcorr_" + strname
# hcenter = hmts_comp[strname]
# hup = hmts_comp[strname_next].Clone(outputname+"_shapeUp")
# hdown = hmts_comp[strname_next].Clone(outputname+"_shapeDown")
# hup.Scale(hcenter.Integral() / hup.Integral())
# for ibin in xrange(1, hcenter.GetNbinsX()+1):
# center = hcenter.GetBinContent(ibin)
# up = hup.GetBinContent(ibin)
# hdown.SetBinContent(ibin, max(2*center - up, 0))
# hcenter.SetBinContent(ibin, max(center, 0))
# hup.SetBinContent(ibin, max(up, 0))
# hcenter.SetDirectory(outfile)
# hcenter.Write()
# hup.SetDirectory(outfile)
# hup.Write()
# hdown.SetDirectory(outfile)
# hdown.Write()
#outfile.Close()
# repeat the same for the full mT one
hmts_comp = OrderedDict()
#for iso in ['iso1', 'iso2', 'iso3', 'iso4', 'iso5', 'iso6', 'iso7', 'iso8', 'iso9']:
#for iso in ['iso1', 'iso2', 'iso3', 'iso4', 'iso5', 'iso6', 'iso7', 'iso8', 'iso9', 'iso10', 'iso11', 'iso12', 'iso13']:
for iso in isobins:
for chg in ['WoVpt', 'wplus', 'wminus']:
#for wpt in ["WpT_bin0", "WpT_bin1", "WpT_bin2", "WpT_bin3", "WpT_bin4", "WpT_bin5", "WpT_bin6", "WpT_bin7", "WpT_bin8"]:
for wpt in wptbins:
for lepeta in etabins:
if chg == "WoVpt":
continue
strname = "weight_{}_{}_{}_{}".format(
chg, iso, wpt, lepeta)
outputname = "histo_wjetsAntiIso_fullrange_mtcorr_" + strname
hstacked = THStack2TH1(sampMan.hsmcs[outputname])
for ibin in xrange(hstacked.GetNbinsX() + 1):
# hstacked should always be above 0
hstacked.SetBinContent(
ibin, max(hstacked.GetBinContent(ibin), 0))
sampMan.hdatas[outputname].Add(hstacked, -1.0)
hmts_comp[strname] = sampMan.hdatas[outputname]
hmts_comp[strname].SetName(outputname)
lepname = "mu" if doMuon else "e"
outfile = ROOT.TFile("output_qcdshape_fullrange_" + lepname + "nu.root",
"recreate")
for chg in ["wplus", "wminus"]:
#for i in xrange(1,13):
#for i in xrange(1,10):
for i in xrange(1, len(isobins)):
#for wpt in ["WpT_bin0", "WpT_bin1", "WpT_bin2", "WpT_bin3", "WpT_bin4", "WpT_bin5", "WpT_bin6", "WpT_bin7", "WpT_bin8"]:
for wpt in wptbins:
for lepeta in etabins:
# skip iso10 as it is used for the uncertainty cal for iso9
iso = "iso" + str(i)
iso_next = "iso" + str(i + 1)
strname = "weight_{}_{}_{}_{}".format(
chg, iso, wpt, lepeta)
strname_next = "weight_{}_{}_{}_{}".format(
chg, iso_next, wpt, lepeta)
outputname = "histo_wjetsAntiIso_fullrange_mtcorr_" + strname
hcenter = hmts_comp[strname]
hup = hmts_comp[strname_next].Clone(outputname +
"_shapeUp")
hdown = hmts_comp[strname_next].Clone(outputname +
"_shapeDown")
hup.Scale(hcenter.Integral() / hup.Integral())
for ibin in xrange(1, hcenter.GetNbinsX() + 1):
center = hcenter.GetBinContent(ibin)
up = hup.GetBinContent(ibin)
hdown.SetBinContent(ibin, max(2 * center - up, 0))
hcenter.SetBinContent(ibin, max(center, 0))
hup.SetBinContent(ibin, max(up, 0))
hcenter.SetDirectory(outfile)
hcenter.Write()
hup.SetDirectory(outfile)
hup.Write()
hdown.SetDirectory(outfile)
hdown.Write()
outfile.Close()
# calculate the shape uncertainty and save them to root file
#hmts_comp = OrderedDict()
##hwpts_comp = OrderedDict()
##hmupts_comp = OrderedDict()
##hmetpts_comp = OrderedDict()
#for iso in ['iso1', 'iso2', 'iso3', 'iso4', 'iso5', 'iso6', 'iso7', 'iso8', 'iso9']:
# for chg in ['WoVpt', 'wplus', 'wminus']:
# if chg == "WoVpt":
# continue
# strname = "weight_{}_{}".format(chg, iso)
# outputname = "histo_wjetsAntiIso_mtcorr_" + strname
# sampMan.hdatas[outputname].Add( THStack2TH1(sampMan.hsmcs[outputname]), -1 )
# hmts_comp[strname] = sampMan.hdatas[outputname]
#outputname = "histo_wjetsAntiIso_WpTcorr_" + strname
#sampMan.hdatas[outputname].Add( THStack2TH1(sampMan.hsmcs[outputname]), -1 )
#hwpts_comp[strname] = sampMan.hdatas[outputname]
#outputname = "histo_wjetsAntiIso_leppt_" + strname
#sampMan.hdatas[outputname].Add( THStack2TH1(sampMan.hsmcs[outputname]), -1 )
#hmupts_comp[strname] = sampMan.hdatas[outputname]
#outputname = "histo_wjetsAntiIso_metpt_" + strname
#sampMan.hdatas[outputname].Add( THStack2TH1(sampMan.hsmcs[outputname]), -1 )
#hmetpts_comp[strname] = sampMan.hdatas[outputname]
#labels = ["|#eta|<0.8", "0.8<|#eta|<1.4", "1.4<|#eta|<2.0", "2.0<|#eta|<2.4"]
#DrawHistos(hmts_comp.values(), labels, 0, 120, 'm_{T} [GeV]', 2e-4, 5e-1, 'A.U.', 'histo_wjetsAntiIso_comp_mT', dology=True, showratio=True, donormalize=True, mycolors=[1,2,3, 4], ratiobase=1, drawoptions=["e", "e", "e", "e"], legendoptions=['LPE', 'LPE', 'LPE', 'LPE'], yrmin=0.71, yrmax=1.29)
#DrawHistos(hwpts_comp.values(), labels, 0, 60, 'p^{W}_{T} [GeV]', 2e-3, 5e-1, 'A.U.', 'histo_wjetsAntiIso_comp_WpT', dology=True, showratio=True, donormalize=True, mycolors=[1,2,3, 4], ratiobase=1, drawoptions=["e", "e", "e", "e"], legendoptions=['LPE', 'LPE', 'LPE', 'LPE'], yrmin=0.71, yrmax=1.29)
#DrawHistos(hmupts_comp.values(), labels, 25, 100, 'p^{#mu}_{T} [GeV]', 2e-3, 5e-1, 'A.U.', 'histo_wjetsAntiIso_comp_mupt', dology=True, showratio=True, donormalize=True, mycolors=[1,2,3, 4], ratiobase=1, drawoptions=["e", "e", "e", "e"], legendoptions=['LPE', 'LPE', 'LPE', 'LPE'], yrmin=0.71, yrmax=1.29)
#DrawHistos(hmetpts_comp.values(), labels, 0, 80, 'p^{miss}_{T} [GeV]', 2e-3, 5e-1, 'A.U.', 'histo_wjetsAntiIso_comp_metpt', dology=True, showratio=True, donormalize=True, mycolors=[1,2,3, 4], ratiobase=1, drawoptions=["e", "e", "e", "e"], legendoptions=['LPE', 'LPE', 'LPE', 'LPE'], yrmin=0.71, yrmax=1.29)
#DrawHistos(hmts_comp.values(), ['0.15<I<0.30', '0.30<I<0.45', '0.45<I<0.55'], 40, 120, 'm_{T} [GeV]', 2e-4, 5e-1, 'A.U.', 'histo_wjetsAntiIso_comp_mT', dology=True, showratio=True, donormalize=True, mycolors=[1,2,3], ratiobase=1, drawoptions=["e", "e", "e"], legendoptions=['LPE', 'LPE', 'LPE'], yrmin=0.71, yrmax=1.29)
#DrawHistos(hwpts_comp.values(), ['0.15<I<0.30', '0.30<I<0.45', '0.45<I<0.55'], 0, 60, 'p^{W}_{T} [GeV]', 2e-3, 5e-1, 'A.U.', 'histo_wjetsAntiIso_comp_WpT', dology=True, showratio=True, donormalize=True, mycolors=[1,2,3], ratiobase=1, drawoptions=["e", "e", "e"], legendoptions=['LPE', 'LPE', 'LPE'], yrmin=0.71, yrmax=1.29)
#DrawHistos(hmupts_comp.values(), ['0.15<I<0.30', '0.30<I<0.45', '0.45<I<0.55'], 25, 70, 'p^{#mu}_{T} [GeV]', 2e-3, 5e-1, 'A.U.', 'histo_wjetsAntiIso_comp_mupt', dology=True, showratio=True, donormalize=True, mycolors=[1,2,3], ratiobase=1, drawoptions=["e", "e", "e"], legendoptions=['LPE', 'LPE', 'LPE'], yrmin=0.71, yrmax=1.29)
#DrawHistos(hmetpts_comp.values(), ['0.15<I<0.30', '0.30<I<0.45', '0.45<I<0.55'], 0, 80, 'p^{W}_{T} [GeV]', 2e-3, 5e-1, 'A.U.', 'histo_wjetsAntiIso_comp_metpt', dology=True, showratio=True, donormalize=True, mycolors=[1,2,3], ratiobase=1, drawoptions=["e", "e", "e"], legendoptions=['LPE', 'LPE', 'LPE'], yrmin=0.71, yrmax=1.29)
#sampMan.launchDraw()
sampMan.dumpCounts()
print "Program end..."
raw_input()
return
def main():
if isData:
inputfile = "inputs/inputs_Z/input_data.txt"
samp = Sample(inputfile, isMC=False, name="Data")
samp.donormalization = False
samp.varyQCDScale = False
samples = [samp]
elif isAMCNLO:
inputfile = "inputs/inputs_Z/input_zjets.txt"
samp = Sample(inputfile, isMC=True, name="ZJets_NLO")
samp.donormalization = False
samp.varyQCDScale = True
samples = [samp]
elif isMADGRAPH:
inputfile = "inputs/inputs_Z/input_zjets_madgraph.txt"
samp = Sample(inputfile, isMC=True, name="ZJets_MG")
samp.donormalization = False
samp.varyQCDScale = False
samples = [samp]
elif isTTbar:
inputfile = "inputs/inputs_Z/input_ttbar.txt"
samp = Sample(inputfile,
isMC=True,
name="TTbar",
xsec=831.76 * 0.105 * 1e3)
samp.donormalization = True
samp.varyQCDScale = True
samples = [samp]
elif isDiboson:
input_WW2L = "inputs/inputs_Z/input_WWTo2L2Nu.txt"
input_WZ3L = "inputs/inputs_Z/input_WZTo3LNu.txt"
input_ZZ2L = "inputs/inputs_Z/input_ZZTo2L2Nu.txt"
input_ZZ4L = "inputs/inputs_Z/input_ZZTo4L.txt"
WW2LSamp = Sample(input_WW2L, xsec=12.178 * 1e3, name="WW2L")
WZ3LSamp = Sample(input_WZ3L, xsec=5.26 * 1e3, name="WZ3L")
ZZ2LSamp = Sample(input_ZZ2L, xsec=0.564 * 1e3, name="ZZ2L")
ZZ4LSamp = Sample(input_ZZ4L, xsec=1.212 * 1e3, name="ZZ4L")
WW2LSamp.donormalization = True
WZ3LSamp.donormalization = True
ZZ2LSamp.donormalization = True
ZZ4LSamp.donormalization = True
WW2LSamp.varyQCDScale = False
WZ3LSamp.varyQCDScale = False
ZZ2LSamp.varyQCDScale = False
ZZ4LSamp.varyQCDScale = False
samples = [WW2LSamp, WZ3LSamp, ZZ2LSamp, ZZ4LSamp]
ptbins = getPtBins()
njetbins = getJetBins()
print ptbins
print njetbins
# prepare u1 (uparal) and u2 (uperp) distributions
# in differen Z pt and jet multiplicity bins
def prepareU1U2(rdf, postfix="", extra_weight="1.0"):
histos_u1 = OrderedDict()
histos_u2 = OrderedDict()
for ijet in xrange(njetbins.size - 1):
njetmin = njetbins[ijet]
njetmax = njetbins[ijet + 1]
histos_u1[(njetmin, njetmax)] = OrderedDict()
histos_u2[(njetmin, njetmax)] = OrderedDict()
for ipt in xrange(ptbins.size - 1):
ptmin = ptbins[ipt]
ptmax = ptbins[ipt + 1]
wstring = "njetbin_{}_ptbin_{}_{}".format(ijet, ipt, postfix)
rdf = rdf.Define(
wstring,
"(jet_n>={} && jet_n<={}) * (Z_pt>={} && Z_pt<{} ) * weight * {}"
.format(njetmin, njetmax, ptmin, ptmax, extra_weight))
hname_u1 = "hist_uparal_{}".format(wstring)
histos_u1[(njetmin, njetmax)][(ptmin, ptmax)] = rdf.Histo1D(
(hname_u1, hname_u1, 240 + int(ptmax) - int(ptmin),
-120.0 + int(ptmin), 120.0 + int(ptmax)), "u1", wstring)
hname_u2 = "hist_uperp_{}".format(wstring)
histos_u2[(njetmin, njetmax)][(ptmin, ptmax)] = rdf.Histo1D(
(hname_u2, hname_u2, 240, -120.0, 120.0), "u2", wstring)
return histos_u1, histos_u2
for samp in samples:
print "\n\n\nWork on sample ", samp.name
weights = OrderedDict()
if samp.varyQCDScale:
# do the QCD scale variations
# Skip mur_2_muf_0p5: EventWeights[5] and
# and mur_0p5_muf_2: EventWeights[7]
weights["weight_mur_1_muf_1"] = "EventWeights[0] / EventWeights[0]"
#weights["weight_mur_1_muf_2" ] = "EventWeights[1] / EventWeights[0]"
#weights["weight_mur_1_muf_0p5" ] = "EventWeights[2] / EventWeights[0]"
#weights["weight_mur_2_muf_1" ] = "EventWeights[3] / EventWeights[0]"
#weights["weight_mur_2_muf_2" ] = "EventWeights[4] / EventWeights[0]"
#weights["weight_mur_0p5_muf_1" ] = "EventWeights[6] / EventWeights[0]"
#weights["weight_mur_0p5_muf_0p5"] = "EventWeights[8] / EventWeights[0]"
else:
weights["central"] = "1.0"
histos_u1 = OrderedDict()
histos_u2 = OrderedDict()
print "\n\nMaking histograms..."
for wname, wstring in weights.iteritems():
# making all histograms first, such that rdataframe could handle
# everything in one loop.
print wname, wstring
samp.rdf = samp.rdf.Define(wname, wstring)
histos_u1[wname], histos_u2[wname] = prepareU1U2(
samp.rdf,
postfix="{}_{}".format(samp.name, wname),
extra_weight=wname)
if samp.donormalization:
print "\n\nScale the {} MC to the xsec with normalization factor {}".format(
samp.name, samp.normfactor)
for wname in histos_u1:
for ijetbin in histos_u1[wname]:
for iptbin in histos_u1[wname][ijetbin]:
histos_u1[wname][ijetbin][iptbin].Scale(
samp.normfactor)
histos_u2[wname][ijetbin][iptbin].Scale(
samp.normfactor)
print "\n\nWriting to output file..."
for wname, wstring in weights.iteritems():
ofilename = "results/U1U2/histos_u1u2_{}_njets_pt_{}.root".format(
samp.name, wname)
print "Write to output file ", ofilename
ofile = ROOT.TFile(ofilename, "recreate")
for ijetbin in histos_u1[wname].keys():
for iptbin in histos_u1[wname][ijetbin].keys():
histos_u1[wname][ijetbin][iptbin].GetValue().SetDirectory(
ofile)
histos_u1[wname][ijetbin][iptbin].GetValue().Write()
histos_u2[wname][ijetbin][iptbin].GetValue().SetDirectory(
ofile)
histos_u2[wname][ijetbin][iptbin].GetValue().Write()
ofile.Close()
print "Finished.."
return
def main():
print "Program start..."
if dotest:
input_data = "inputs/inputs_W/input_data_test.txt"
input_wjets = "inputs/inputs_W/input_wjets_test.txt"
# for the data-driven bkg estimation from the QCD dominated region
input_data_qcdcr = "inputs/inputs_QCDCR/input_data_test.txt"
input_wjets_qcdcr = "inputs/inputs_QCDCR/input_wjets_test.txt"
input_zjets_qcdcr = "inputs/inputs_QCDCR/input_zjets_test.txt"
input_ttbar_qcdcr = "inputs/inputs_QCDCR/input_ttbar_test.txt"
input_lept_qcdcr = "inputs/inputs_QCDCR/input_ttbar_singlelep_fromT_test.txt"
input_leptbar_qcdcr = "inputs/inputs_QCDCR/input_ttbar_singlelep_fromTbar_test.txt"
else:
input_data = "inputs/inputs_W/input_data.txt"
input_wjets = "inputs/inputs_W/input_wjets.txt"
input_zjets = "inputs/inputs_W/input_zjets.txt"
input_ttbar = "inputs/inputs_W/input_ttbar.txt"
input_lept = "inputs/inputs_W/input_ttbar_singlelep_fromT.txt"
input_leptbar = "inputs/inputs_W/input_ttbar_singlelep_fromTbar.txt"
#input_qcd = "inputs/inputs_W/input_qcd.txt"
# for the data-driven bkg estimation from the QCD dominated region
input_data_qcdcr = "inputs/inputs_QCDCR/input_data.txt"
input_wjets_qcdcr = "inputs/inputs_QCDCR/input_wjets.txt"
input_zjets_qcdcr = "inputs/inputs_QCDCR/input_zjets.txt"
input_ttbar_qcdcr = "inputs/inputs_QCDCR/input_ttbar.txt"
input_lept_qcdcr = "inputs/inputs_QCDCR/input_ttbar_singlelep_fromT.txt"
input_leptbar_qcdcr = "inputs/inputs_QCDCR/input_ttbar_singlelep_fromTbar.txt"
DataSamp = Sample(input_data,
isMC=False,
legend="Data",
name="Data",
isZSR=False,
isWSR=True)
WJetsSamp = Sample(input_wjets,
xsec=61526.7 * 1e3,
color=38,
legend="WJets",
name="WJets",
isZSR=False,
isWSR=True)
if not dotest:
ZJetsSamp = Sample(input_zjets,
xsec=6077.22 * 1e3,
color=5,
legend="DYJets",
name="ZJets",
isZSR=False,
isWSR=True)
TTbarSamp = Sample(input_ttbar,
xsec=831.76 * 0.105 * 1e3,
color=46,
legend="t#bar{t}",
name="ttbar2lep",
isZSR=False,
isWSR=True)
TTLepTSamp = Sample(input_lept,
xsec=831.76 * 0.219 * 1e3,
color=47,
legend="t#bar{t}",
name="ttbarlept",
isZSR=False,
isWSR=True)
TTLepTbarSamp = Sample(input_leptbar,
xsec=831.76 * 0.219 * 1e3,
color=48,
legend="t#bar{t}",
name="ttbarleptbar",
isZSR=False,
isWSR=True)
#QCDSamp = Sample(input_qcd, xsec = 720648000.0*0.00042*1e3, color=8, legend="QCD", name="QCD", isZSR=False, isWSR=True)
DataQCDCRSamp = Sample(input_data_qcdcr,
isMC=False,
legend="Data_QCDCR",
name="Data_QCDCR",
isZSR=False,
isWSR=True)
WJetsQCDCRSamp = Sample(input_wjets_qcdcr,
xsec=-61526.7 * 1e3,
color=38,
legend="WJets_QCDCR",
name="WJets_QCDCR",
isZSR=False,
isWSR=True,
applySF=False)
ZJetsQCDCRSamp = Sample(input_zjets_qcdcr,
xsec=-6077.22 * 1e3,
color=5,
legend="ZJets_QCDCR",
name="ZJets_QCDCR",
isZSR=False,
isWSR=True,
applySF=False)
TTbarQCDCRSamp = Sample(input_ttbar_qcdcr,
xsec=-831.76 * 0.105 * 1e3,
color=46,
legend="t#bar{t} QCDCR",
name="ttbar2lep_QCDCR",
isZSR=False,
isWSR=True,
applySF=False)
TTLepTQCDCRSamp = Sample(input_lept_qcdcr,
xsec=-831.76 * 0.219 * 1e3,
color=47,
legend="t#bar{t} QCDCR",
name="ttbarlept_QCDCR",
isZSR=False,
isWSR=True,
applySF=False)
TTLepTbarQCDCRSamp = Sample(input_leptbar_qcdcr,
xsec=-831.76 * 0.219 * 1e3,
color=48,
legend="t#bar{t} QCDCR",
name="ttbarleptb",
isZSR=False,
isWSR=True,
applySF=False)
if not dotest:
sampMan = SampleManager(DataSamp, [
WJetsSamp, ZJetsSamp, TTbarSamp, TTLepTSamp, TTLepTbarSamp,
DataQCDCRSamp, WJetsQCDCRSamp, ZJetsQCDCRSamp, TTbarQCDCRSamp,
TTLepTQCDCRSamp, TTLepTbarQCDCRSamp
])
else:
sampMan = SampleManager(DataSamp, [
WJetsSamp, DataQCDCRSamp, WJetsQCDCRSamp, ZJetsQCDCRSamp,
TTbarQCDCRSamp, TTLepTQCDCRSamp, TTLepTbarQCDCRSamp
])
# create renormalized QCD scale variation weights for WJets
def prepareWJetsQCDScaleVariations():
print "prepare the renormalized QCD scale variations"
QCDVariations = OrderedDict({
"central": 0,
"mur_1_muf_2": 1,
"mur_1_muf_0p5": 2,
"mur_2_muf_1": 3,
"mur_2_muf_2": 4,
"mur_0p5_muf_1": 6,
"mur_0p5_muf_0p5": 8
})
hcounts = OrderedDict()
WJetsSamp.Define("const_1", "1.0")
for var, index in QCDVariations.iteritems():
WJetsSamp.Define(
"weight_" + var,
"weight * EventWeights[%d]/EventWeights[0]" % index)
hcounts[var] = WJetsSamp.rdf.Histo1D(
("hcounts_" + var, "hcounts_" + var, 2, 0, 2), "const_1",
"weight_" + var)
nevents_norm = hcounts['central'].Integral()
for var, hist in hcounts.iteritems():
nevents = hcounts[var].Integral()
print "For {}: Total: {}, weighted:{}. Norm factor {}".format(
var, nevents_norm, nevents, nevents_norm / nevents)
weightname = "weight_" + var
WJetsSamp.Define(
weightname + "_scaled",
"{} * {}".format(weightname, nevents_norm / nevents))
print "finished preparing renormalized QCD scale variations"
prepareWJetsQCDScaleVariations()
sampMan.groupMCs([
"Data_QCDCR", "WJets_QCDCR", "ZJets_QCDCR", "ttbar2lep_QCDCR",
"ttbarlept_QCDCR", "ttbarleptb"
],
"QCD",
17,
"QCD",
renormalize=False,
renormalizefactor=3.29)
sampMan.groupMCs(["ttbar2lep", "ttbarlept", "ttbarleptbar"], "ttbar", 46,
"t#bar{t}")
# QCD enriched isolation regions
sampMan.ApplyCutSpecificMCs("(mu_pfIso[0]>0.30 && mu_pfIso[0]<0.60)",
sampgroupnames=["QCD"])
sampMan.DefineSpecificMCs(
"weight_Iso0",
"weight * (mu_pfIso[0]>0.30 && mu_pfIso[0]<0.60)",
sampgroupnames=["QCD"])
sampMan.DefineAll("weight_Iso0", "weight", excludeGroups=['QCD'])
sampMan.DefineSpecificMCs(
"weight_Iso1",
"weight * (mu_pfIso[0]>0.30 && mu_pfIso[0]<0.60) * 3.32/3.29",
sampgroupnames=["QCD"])
sampMan.DefineAll("weight_Iso1", "weight", excludeGroups=['QCD'])
sampMan.DefineSpecificMCs(
"weight_Iso2",
"weight * (mu_pfIso[0]>0.30 && mu_pfIso[0]<0.60) * 3.20/3.29",
sampgroupnames=["QCD"])
sampMan.DefineAll("weight_Iso2", "weight", excludeGroups=['QCD'])
sampMan.DefineAll("Mu_pt", "mu_pt[0]")
sampMan.DefineAll(
"mT_PF", "calMT_fromMET_PtPhi(mu_pt[0], mu_phi[0], met_pt, met_phi)")
sampMan.DefineAll(
"mT_Puppi",
"calMT_fromMET_PtPhi(mu_pt[0], mu_phi[0], puppimet_pt, puppimet_phi)")
sampMan.DefineAll(
"mT_Deep",
"calMT_fromMET_PtPhi(mu_pt[0], mu_phi[0], deepmet_pt, deepmet_phi)")
sampMan.DefineAll("u_reco_pt_PF",
"calUT_PtPhi(mu_pt[0], mu_phi[0], met_pt, met_phi)")
sampMan.DefineAll(
"u_reco_pt_Puppi",
"calUT_PtPhi(mu_pt[0], mu_phi[0], puppimet_pt, puppimet_phi)")
sampMan.DefineAll(
"u_reco_pt_Deep",
"calUT_PtPhi(mu_pt[0], mu_phi[0], deepmet_pt, deepmet_phi)")
# correct DeepMET
WJetsSamp.Define("trueW_index", "trueWIndex(trueW_n)")
WJetsSamp.Define(
"W_pt",
"(trueW_index >=0 && trueW_index<=1) ? trueW_pt[trueW_index] : 0")
WJetsSamp.Define(
"W_phi",
"(trueW_index>=0 && trueW_index<=1) ? trueW_phi[trueW_index] : 0")
WJetsSamp.Define("Uvec",
"UVec(mu_pt[0], mu_phi[0], deepmet_pt, deepmet_phi)")
WJetsSamp.Define("u_pt", "Uvec.Mod()")
WJetsSamp.Define("u_phi", "Uvec.Phi()")
WJetsSamp.Define("u1", "u_pt * TMath::Cos(u_phi + TMath::Pi() - W_phi)")
WJetsSamp.Define("u2", "u_pt * TMath::Sin(u_phi + TMath::Pi() - W_phi)")
ROOT.gROOT.ProcessLine(
'TFile* fitfunctions_Data = TFile::Open("results/Fit/fitfunctions_Data_njets_pt_central.root")'
)
ROOT.gROOT.ProcessLine(
'TH1F* h1_ptbins_Data_central = (TH1F*)fitfunctions_Data->Get("h1_ptbins_Data_central")'
)
ROOT.gROOT.ProcessLine(
'TH1F* h1_njetbins_Data_central = (TH1F*)fitfunctions_Data->Get("h1_njetbins_Data_central")'
)
ROOT.gROOT.ProcessLine(
'TList* tfs_Data_u1_njets_pt_central = (TList*)fitfunctions_Data->Get("tfs_Data_u1_njets_pt_central")'
)
ROOT.gROOT.ProcessLine(
'TList* tfs_Data_u2_njets_pt_central = (TList*)fitfunctions_Data->Get("tfs_Data_u2_njets_pt_central")'
)
ROOT.gROOT.ProcessLine(
'TFile* fitfunctions_ZJets_NLO_central = TFile::Open("results/Fit/fitfunctions_ZJets_NLO_njets_pt_central.root")'
)
ROOT.gROOT.ProcessLine(
'TList* tfs_MC_u1_njets_pt_central = (TList*)fitfunctions_ZJets_NLO_central->Get("tfs_ZJets_NLO_u1_njets_pt_central")'
)
ROOT.gROOT.ProcessLine(
'TList* tfs_MC_u2_njets_pt_central = (TList*)fitfunctions_ZJets_NLO_central->Get("tfs_ZJets_NLO_u2_njets_pt_central")'
)
WJetsSamp.Define(
"u1_corr_central",
"UCorrection_Quant(u1, jet_n, W_pt, h1_njetbins_Data_central, h1_ptbins_Data_central, tfs_Data_u1_njets_pt_central, tfs_MC_u1_njets_pt_central, 0.00001)"
)
WJetsSamp.Define(
"u2_corr_central",
"UCorrection_Quant(u2, jet_n, W_pt, h1_njetbins_Data_central, h1_ptbins_Data_central, tfs_Data_u2_njets_pt_central, tfs_MC_u2_njets_pt_central, 0.00001)"
)
WJetsSamp.Define(
"deepmet_corr_central",
"METVec(mu_pt[0], mu_phi[0], u1_corr_central, u2_corr_central, W_phi)")
WJetsSamp.Define("deepmet_pt_corr_central", "deepmet_corr_central.Mod()")
WJetsSamp.Define("deepmet_phi_corr_central",
"TVector2::Phi_mpi_pi(deepmet_corr_central.Phi())")
WJetsSamp.Define(
"mT_Deep_corr_central",
"calMT_fromMET_PtPhi(mu_pt[0], mu_phi[0], deepmet_pt_corr_central, deepmet_phi_corr_central)"
)
sampMan.DefineAll("deepmet_pt_corr_central",
"deepmet_pt",
excludes=['WJets'])
sampMan.DefineAll("deepmet_phi_corr_central",
"deepmet_phi",
excludes=['WJets'])
sampMan.DefineAll("mT_Deep_corr_central", "mT_Deep", excludes=['WJets'])
sampMan.DefineAll(
"u_reco_pt_Deep_corr_central",
"calUT_PtPhi(mu_pt[0], mu_phi[0], deepmet_pt_corr_central, deepmet_phi_corr_central)"
)
# systematics variations
# corrections from MadGraph
ROOT.gROOT.ProcessLine(
'TFile* fitfunctions_ZJets_MG_central = TFile::Open("results/Fit/fitfunctions_ZJets_MG_njets_pt_central.root")'
)
ROOT.gROOT.ProcessLine(
'TList* tfs_MC_MG_u1_njets_pt_central = (TList*)fitfunctions_ZJets_MG_central->Get("tfs_ZJets_MG_u1_njets_pt_central")'
)
ROOT.gROOT.ProcessLine(
'TList* tfs_MC_MG_u2_njets_pt_central = (TList*)fitfunctions_ZJets_MG_central->Get("tfs_ZJets_MG_u2_njets_pt_central")'
)
WJetsSamp.Define(
"u1_corr_central_MG",
"UCorrection_Quant(u1, jet_n, W_pt, h1_njetbins_Data_central, h1_ptbins_Data_central, tfs_Data_u1_njets_pt_central, tfs_MC_MG_u1_njets_pt_central, 0.00001)"
)
WJetsSamp.Define(
"u2_corr_central_MG",
"UCorrection_Quant(u2, jet_n, W_pt, h1_njetbins_Data_central, h1_ptbins_Data_central, tfs_Data_u2_njets_pt_central, tfs_MC_MG_u2_njets_pt_central, 0.00001)"
)
WJetsSamp.Define(
"deepmet_corr_central_MG",
"METVec(mu_pt[0], mu_phi[0], u1_corr_central_MG, u2_corr_central_MG, W_phi)"
)
WJetsSamp.Define("deepmet_pt_corr_central_MG",
"deepmet_corr_central_MG.Mod()")
WJetsSamp.Define("deepmet_phi_corr_central_MG",
"TVector2::Phi_mpi_pi(deepmet_corr_central_MG.Phi())")
WJetsSamp.Define(
"mT_Deep_corr_central_MG",
"calMT_fromMET_PtPhi(mu_pt[0], mu_phi[0], deepmet_pt_corr_central_MG, deepmet_phi_corr_central_MG)"
)
sampMan.DefineAll("deepmet_pt_corr_central_MG",
"deepmet_pt",
excludes=['WJets'])
sampMan.DefineAll("deepmet_phi_corr_central_MG",
"deepmet_phi",
excludes=['WJets'])
sampMan.DefineAll("mT_Deep_corr_central_MG", "mT_Deep", excludes=['WJets'])
sampMan.DefineAll(
"u_reco_pt_Deep_corr_central_MG",
"calUT_PtPhi(mu_pt[0], mu_phi[0], deepmet_pt_corr_central_MG, deepmet_phi_corr_central_MG)"
)
# corrections from Gaussian Smearing
ROOT.gROOT.ProcessLine(
'TFile* gaussSmoother_Data_njets_pt_central = TFile::Open("results/GaussSmoother/gaussSmoother_Data_njets_pt_central.root")'
)
ROOT.gROOT.ProcessLine(
'TList* cdfs_Data_u1_njets_pt_central = (TList*)gaussSmoother_Data_njets_pt_central->Get("cdfs_Data_u1_njets_pt_central")'
)
ROOT.gROOT.ProcessLine(
'TList* cdfs_Data_u2_njets_pt_central = (TList*)gaussSmoother_Data_njets_pt_central->Get("cdfs_Data_u2_njets_pt_central")'
)
ROOT.gROOT.ProcessLine(
'TFile* gaussSmoother_ZJets_NLO_njets_pt_central = TFile::Open("results/GaussSmoother/gaussSmoother_ZJets_NLO_njets_pt_central.root")'
)
ROOT.gROOT.ProcessLine(
'TList* cdfs_ZJets_NLO_u1_njets_pt_central = (TList*)gaussSmoother_ZJets_NLO_njets_pt_central->Get("cdfs_ZJets_NLO_u1_njets_pt_central")'
)
ROOT.gROOT.ProcessLine(
'TList* cdfs_ZJets_NLO_u2_njets_pt_central = (TList*)gaussSmoother_ZJets_NLO_njets_pt_central->Get("cdfs_ZJets_NLO_u2_njets_pt_central")'
)
WJetsSamp.Define(
"u1_corr_central_GKS",
"UCorrection_Quant(u1, jet_n, W_pt, h1_njetbins_Data_central, h1_ptbins_Data_central, cdfs_Data_u1_njets_pt_central, cdfs_ZJets_NLO_u1_njets_pt_central, 0.00001)"
)
WJetsSamp.Define(
"u2_corr_central_GKS",
"UCorrection_Quant(u2, jet_n, W_pt, h1_njetbins_Data_central, h1_ptbins_Data_central, cdfs_Data_u2_njets_pt_central, cdfs_ZJets_NLO_u2_njets_pt_central, 0.00001)"
)
WJetsSamp.Define(
"deepmet_corr_central_GKS",
"METVec(mu_pt[0], mu_phi[0], u1_corr_central_GKS, u2_corr_central_GKS, W_phi)"
)
WJetsSamp.Define("deepmet_pt_corr_central_GKS",
"deepmet_corr_central_GKS.Mod()")
WJetsSamp.Define("deepmet_phi_corr_central_GKS",
"TVector2::Phi_mpi_pi(deepmet_corr_central_GKS.Phi())")
WJetsSamp.Define(
"mT_Deep_corr_central_GKS",
"calMT_fromMET_PtPhi(mu_pt[0], mu_phi[0], deepmet_pt_corr_central_GKS, deepmet_phi_corr_central_GKS)"
)
sampMan.DefineAll("deepmet_pt_corr_central_GKS",
"deepmet_pt",
excludes=['WJets'])
sampMan.DefineAll("deepmet_phi_corr_central_GKS",
"deepmet_phi",
excludes=['WJets'])
sampMan.DefineAll("mT_Deep_corr_central_GKS",
"mT_Deep",
excludes=['WJets'])
sampMan.DefineAll(
"u_reco_pt_Deep_corr_central_GKS",
"calUT_PtPhi(mu_pt[0], mu_phi[0], deepmet_pt_corr_central_GKS, deepmet_phi_corr_central_GKS)"
)
# correction from ttbar qcd scale:
def varyTTbarQCDScale(wstring):
ROOT.gROOT.ProcessLine(
'TFile* fitfunctions_Data_{WS} = TFile::Open("results/Fit/fitfunctions_Data_njets_pt_{WS}.root")'
.format(WS=wstring))
ROOT.gROOT.ProcessLine(
'TList* tfs_Data_u1_njets_pt_{WS} = (TList*)fitfunctions_Data_{WS}->Get("tfs_Data_u1_njets_pt_{WS}")'
.format(WS=wstring))
ROOT.gROOT.ProcessLine(
'TList* tfs_Data_u2_njets_pt_{WS} = (TList*)fitfunctions_Data_{WS}->Get("tfs_Data_u2_njets_pt_{WS}")'
.format(WS=wstring))
WJetsSamp.Define(
"u1_corr_" + wstring,
"UCorrection_Quant(u1, jet_n, W_pt, h1_njetbins_Data_central, h1_ptbins_Data_central, tfs_Data_u1_njets_pt_{WS}, tfs_MC_u1_njets_pt_central, 0.00001)"
.format(WS=wstring))
WJetsSamp.Define(
"u2_corr_" + wstring,
"UCorrection_Quant(u2, jet_n, W_pt, h1_njetbins_Data_central, h1_ptbins_Data_central, tfs_Data_u2_njets_pt_{WS}, tfs_MC_u2_njets_pt_central, 0.00001)"
.format(WS=wstring))
WJetsSamp.Define(
"deepmet_corr_" + wstring,
"METVec(mu_pt[0], mu_phi[0], u1_corr_{WS}, u2_corr_{WS}, W_phi)".
format(WS=wstring))
WJetsSamp.Define("deepmet_pt_corr_" + wstring,
"deepmet_corr_{WS}.Mod()".format(WS=wstring))
WJetsSamp.Define(
"deepmet_phi_corr_" + wstring,
"TVector2::Phi_mpi_pi(deepmet_corr_{WS}.Phi())".format(WS=wstring))
WJetsSamp.Define(
"mT_Deep_corr_" + wstring,
"calMT_fromMET_PtPhi(mu_pt[0], mu_phi[0], deepmet_pt_corr_{WS}, deepmet_phi_corr_{WS})"
.format(WS=wstring))
sampMan.DefineAll("deepmet_pt_corr_" + wstring,
"deepmet_pt",
excludes=['WJets'])
sampMan.DefineAll("deepmet_phi_corr_" + wstring,
"deepmet_phi",
excludes=['WJets'])
sampMan.DefineAll("mT_Deep_corr_" + wstring,
"mT_Deep",
excludes=['WJets'])
sampMan.DefineAll(
"u_reco_pt_Deep_corr_" + wstring,
"calUT_PtPhi(mu_pt[0], mu_phi[0], deepmet_pt_corr_{WS}, deepmet_phi_corr_{WS})"
.format(WS=wstring))
varyTTbarQCDScale("mur_1_muf_0p5")
varyTTbarQCDScale("mur_1_muf_2")
varyTTbarQCDScale("mur_0p5_muf_1")
varyTTbarQCDScale("mur_2_muf_1")
varyTTbarQCDScale("mur_0p5_muf_0p5")
varyTTbarQCDScale("mur_2_muf_2")
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, 90, 100, 110, 120, 130,
140, 150, 160, 170, 180, 190, 200
])
u1_bins = np.array([
-40., -36., -32., -28., -25., -22.0, -20.0, -18, -16, -14, -12, -10,
-8, -6, -4, -2, 0, 2, 4, 6, 8, 10, 12, 14, 16, 18, 20, 22, 24, 26, 28,
30, 32, 34, 36, 38, 40, 42, 44, 46, 48, 50, 53, 56, 59, 64, 68, 72, 76,
80, 85, 90, 100
])
u2_bins = np.array([
-80., -75., -70., -65., -60., -56., -52, -48, -44, -40, -37, -34, -31,
-28, -25., -22., -20, -18, -16, -14, -12, -10, -8, -6, -4, -2, 0, 2, 4,
6, 8, 10, 12, 16, 18, 20, 22, 25, 28, 31, 34, 37, 40, 44, 48, 52, 56,
60, 65, 70, 75, 80
])
u_bins = np.array([
0., 2., 4., 6, 8, 10, 12, 14, 16, 18, 20, 22, 24, 26, 28, 30, 32, 34,
36, 38, 40, 43, 46, 49, 52, 56, 60, 64, 68, 72, 76, 80, 85, 90, 95,
100, 105, 110, 115, 120, 130, 140, 150
])
ymin = 1e3
ymax = 5e9
legendPos = [0.92, 0.88, 0.70, 0.62]
sampMan.cacheDraw(
"Mu_pt", "h_wjets_mu_pt", 35, 30, 100,
DrawConfig(xmin=30,
xmax=100,
xlabel='p_{T}^{#mu} [GeV]',
ymin=ymin,
ymax=ymax,
legendPos=legendPos))
sampMan.cacheDraw(
"met_pt", "h_wjets_met_pt", 50, 0, 150,
DrawConfig(xmin=0,
xmax=150,
xlabel='PF MET [GeV]',
ymin=ymin,
ymax=ymax,
legendPos=legendPos))
sampMan.cacheDraw(
"puppimet_pt", "h_wjets_puppimet_pt", 50, 0, 150,
DrawConfig(xmin=0,
xmax=150,
xlabel='Puppi MET [GeV]',
ymin=ymin,
ymax=ymax,
legendPos=legendPos))
sampMan.cacheDraw(
"deepmet_pt", "h_wjets_deepmet_pt", 50, 0, 150,
DrawConfig(xmin=0,
xmax=150,
xlabel='Deep MET [GeV]',
ymin=ymin,
ymax=ymax,
legendPos=legendPos))
sampMan.cacheDraw(
"met_phi", "h_wjets_met_phi", 20, -ROOT.TMath.Pi(), ROOT.TMath.Pi(),
DrawConfig(xmin=-ROOT.TMath.Pi(),
xmax=ROOT.TMath.Pi(),
xlabel='PF MET #phi',
ymin=10.,
ymax=1e12))
sampMan.cacheDraw(
"puppimet_phi", "h_wjets_puppimet_phi", 20, -ROOT.TMath.Pi(),
ROOT.TMath.Pi(),
DrawConfig(xmin=-ROOT.TMath.Pi(),
xmax=ROOT.TMath.Pi(),
xlabel='Puppi MET #phi',
ymin=10.,
ymax=1e12))
sampMan.cacheDraw(
"deepmet_phi", "h_wjets_deepmet_phi", 20, -ROOT.TMath.Pi(),
ROOT.TMath.Pi(),
DrawConfig(xmin=-ROOT.TMath.Pi(),
xmax=ROOT.TMath.Pi(),
xlabel='Deep MET #phi',
ymin=10.,
ymax=1e12))
sampMan.cacheDraw(
"mT_PF", "h_wjets_mT_PF", 70, 0, 140,
DrawConfig(xmin=0,
xmax=140,
xlabel='PF m_{T} [GeV]',
ymin=ymin,
ymax=ymax,
legendPos=legendPos))
sampMan.cacheDraw(
"mT_Puppi", "h_wjets_mT_Puppi", 70, 0, 140,
DrawConfig(xmin=0,
xmax=140,
xlabel='Puppi m_{T} [GeV]',
ymin=ymin,
ymax=ymax,
legendPos=legendPos))
sampMan.cacheDraw(
"mT_Deep", "h_wjets_mT_Deep", 70, 0, 140,
DrawConfig(xmin=0,
xmax=140,
xlabel='Deep m_{T} [GeV]',
ymin=ymin,
ymax=ymax,
legendPos=legendPos))
sampMan.cacheDraw(
"u_reco_pt_PF", "h_wjets_u_reco_pt_PF", 28, 0, 140,
DrawConfig(xmin=0,
xmax=140,
xlabel='q_{T} PF [GeV]',
ymin=ymin,
ymax=ymax,
legendPos=legendPos))
sampMan.cacheDraw(
"u_reco_pt_Puppi", "h_wjets_u_reco_pt_Puppi", 28, 0, 140,
DrawConfig(xmin=0,
xmax=140,
xlabel='q_{T} Puppi [GeV]',
ymin=ymin,
ymax=ymax,
legendPos=legendPos))
sampMan.cacheDraw(
"u_reco_pt_Deep", "h_wjets_u_reco_pt_Deep", 28, 0, 140,
DrawConfig(xmin=0,
xmax=140,
xlabel='Deep q_{T} [GeV]',
ymin=ymin,
ymax=ymax,
legendPos=legendPos))
# corrected deepmet
def DrawCorrection(postfix):
sampMan.cacheDraw(
"deepmet_pt_corr_" + postfix, "h_wjets_deepmet_pt_corr_" + postfix,
50, 0, 150,
DrawConfig(xmin=0,
xmax=150,
xlabel='Deep MET Corrected [GeV]',
ymin=ymin,
ymax=ymax,
legendPos=legendPos))
sampMan.cacheDraw(
"mT_Deep_corr_" + postfix, "h_wjets_mT_Deep_corr_" + postfix, 70,
0, 140,
DrawConfig(xmin=0,
xmax=140,
xlabel='Deep m_{T} Corrected [GeV]',
ymin=ymin,
ymax=ymax,
legendPos=legendPos))
sampMan.cacheDraw(
"u_reco_pt_Deep_corr_" + postfix,
"h_wjets_u_reco_pt_Deep_corr_" + postfix, 28, 0, 140,
DrawConfig(xmin=0,
xmax=140,
xlabel='Deep q_{T} Corrected [GeV]',
ymin=ymin,
ymax=ymax,
legendPos=legendPos))
DrawCorrection("central")
DrawCorrection("central_MG")
DrawCorrection("central_GKS")
DrawCorrection("mur_1_muf_0p5")
DrawCorrection("mur_1_muf_2")
DrawCorrection("mur_0p5_muf_1")
DrawCorrection("mur_2_muf_1")
DrawCorrection("mur_0p5_muf_0p5")
DrawCorrection("mur_2_muf_2")
# vary the QCD Scale in WJets and compare the variations
def CompareWJetsQCDScale(postfix, fixxsec=True):
QCDVariations = {
"central": 0,
"mur_1_muf_2": 1,
"mur_1_muf_0p5": 2,
"mur_2_muf_1": 3,
"mur_2_muf_2": 4,
"mur_0p5_muf_1": 6,
"mur_0p5_muf_0p5": 8
}
weightname = "weight_wjetsqcdscale_" + postfix
if fixxsec:
# use the pre-calculated weights
WJetsSamp.Define(weightname, "weight_" + postfix + "_scaled")
else:
WJetsSamp.Define(
weightname, "EventWeights[%d]/EventWeights[0] * weight" %
QCDVariations[postfix])
sampMan.DefineAll(weightname, "weight", excludes=['WJets'])
sampMan.cacheDraw("deepmet_pt",
"h_wjets_deepmet_pt_wjetsqcdscale_" + postfix,
50,
0,
150,
DrawConfig(xmin=0,
xmax=150,
xlabel='Deep MET [GeV]',
ymin=ymin,
ymax=ymax,
legendPos=legendPos),
weightname=weightname)
sampMan.cacheDraw("mT_Deep",
"h_wjets_mT_Deep_wjetsqcdscale_" + postfix,
70,
0,
140,
DrawConfig(xmin=0,
xmax=140,
xlabel='Deep m_{T} [GeV]',
ymin=ymin,
ymax=ymax,
legendPos=legendPos),
weightname=weightname)
sampMan.cacheDraw("u_reco_pt_Deep",
"h_wjets_u_reco_pt_Deep_wjetsqcdscale_" + postfix,
28,
0,
140,
DrawConfig(xmin=0,
xmax=140,
xlabel='Deep q_{T} [GeV]',
ymin=ymin,
ymax=ymax,
legendPos=legendPos),
weightname=weightname)
sampMan.cacheDraw("deepmet_pt_corr_central",
"h_wjets_deepmet_pt_corr_central_wjetsqcdscale_" +
postfix,
50,
0,
150,
DrawConfig(xmin=0,
xmax=150,
xlabel='Deep MET Corrected [GeV]',
ymin=ymin,
ymax=ymax,
legendPos=legendPos),
weightname=weightname)
sampMan.cacheDraw("mT_Deep_corr_central",
"h_wjets_mT_Deep_corr_central_wjetsqcdscale_" +
postfix,
70,
0,
140,
DrawConfig(xmin=0,
xmax=140,
xlabel='Deep m_{T} Corrected [GeV]',
ymin=ymin,
ymax=ymax,
legendPos=legendPos),
weightname=weightname)
sampMan.cacheDraw(
"u_reco_pt_Deep_corr_central",
"h_wjets_u_reco_pt_Deep_corr_central_wjetsqcdscale_" + postfix,
28,
0,
140,
DrawConfig(xmin=0,
xmax=140,
xlabel='Deep q_{T} Corrected [GeV]',
ymin=ymin,
ymax=ymax,
legendPos=legendPos),
weightname=weightname)
CompareWJetsQCDScale("central")
CompareWJetsQCDScale("mur_1_muf_2")
CompareWJetsQCDScale("mur_1_muf_0p5")
CompareWJetsQCDScale("mur_2_muf_1")
CompareWJetsQCDScale("mur_2_muf_2")
CompareWJetsQCDScale("mur_0p5_muf_1")
CompareWJetsQCDScale("mur_0p5_muf_0p5")
def CompareWeights(weightname, postfix):
sampMan.cacheDraw("deepmet_pt",
"h_wjets_deepmet_pt_" + postfix,
50,
0,
150,
DrawConfig(xmin=0,
xmax=150,
xlabel='Deep MET [GeV]',
ymin=ymin,
ymax=ymax,
legendPos=legendPos),
weightname=weightname)
sampMan.cacheDraw("mT_Deep",
"h_wjets_mT_Deep_" + postfix,
70,
0,
140,
DrawConfig(xmin=0,
xmax=140,
xlabel='Deep m_{T} [GeV]',
ymin=ymin,
ymax=ymax,
legendPos=legendPos),
weightname=weightname)
sampMan.cacheDraw("u_reco_pt_Deep",
"h_wjets_u_reco_pt_Deep_" + postfix,
28,
0,
140,
DrawConfig(xmin=0,
xmax=140,
xlabel='Deep q_{T} [GeV]',
ymin=ymin,
ymax=ymax,
legendPos=legendPos),
weightname=weightname)
sampMan.cacheDraw("deepmet_pt_corr_central",
"h_wjets_deepmet_pt_corr_central_" + postfix,
50,
0,
150,
DrawConfig(xmin=0,
xmax=150,
xlabel='Deep MET Corrected [GeV]',
ymin=ymin,
ymax=ymax,
legendPos=legendPos),
weightname=weightname)
sampMan.cacheDraw("mT_Deep_corr_central",
"h_wjets_mT_Deep_corr_central_" + postfix,
70,
0,
140,
DrawConfig(xmin=0,
xmax=140,
xlabel='Deep m_{T} Corrected [GeV]',
ymin=ymin,
ymax=ymax,
legendPos=legendPos),
weightname=weightname)
sampMan.cacheDraw("u_reco_pt_Deep_corr_central",
"h_wjets_u_reco_pt_Deep_corr_central_" + postfix,
28,
0,
140,
DrawConfig(xmin=0,
xmax=140,
xlabel='Deep q_{T} Corrected [GeV]',
ymin=ymin,
ymax=ymax,
legendPos=legendPos),
weightname=weightname)
CompareWeights("weight_Iso0", "MuIso0")
CompareWeights("weight_Iso1", "MuIso1")
CompareWeights("weight_Iso2", "MuIso2")
sampMan.launchDraw()
def compMCRatios(hnames,
colors,
linestyles,
legends,
outputtag,
ymin=0.8,
ymax=1.2):
# compare MC with MC
histos_met = [
THStack2TH1(sampMan.hsmcs["h_wjets_deepmet_pt_{}".format(hname)],
"MCRatio") for hname in hnames
]
histos_u_pt = [
THStack2TH1(
sampMan.hsmcs["h_wjets_u_reco_pt_Deep_{}".format(hname)],
"MCRatio") for hname in hnames
]
histos_mt = [
THStack2TH1(sampMan.hsmcs["h_wjets_mT_Deep_{}".format(hname)],
"MCRatio") for hname in hnames
]
histos_met_base = histos_met[0].Clone(histos_met[0].GetName() +
"_Cloned")
histos_u_pt_base = histos_u_pt[0].Clone(histos_u_pt[0].GetName() +
"_Cloned")
histos_mt_base = histos_mt[0].Clone(histos_mt[0].GetName() + "_Cloned")
for hmet, hupt, hmt in zip(histos_met, histos_u_pt, histos_mt):
hmet.Divide(histos_met_base)
hmet.SetFillColor(0)
hupt.Divide(histos_u_pt_base)
hupt.SetFillColor(0)
hmt.Divide(histos_mt_base)
hmt.SetFillColor(0)
if len(hnames) > 5:
legendNCols = 2
legendPos = [0.20, 0.88, 0.70, 0.74]
elif len(hnames) > 8:
legendNCols = 3
legendPos = [0.15, 0.99, 0.92, 0.72]
else:
legendNCols = 1
legendPos = [0.20, 0.88, 0.35, 0.74]
if "corr" in hnames[0]:
metlabel = "Deep MET Corrected [GeV]"
qtlabel = "Deep q_{T} Corrected [GeV]"
mtlabel = "Deep m_{T} Corrected [GeV]"
else:
metlabel = "Deep MET [GeV]"
qtlabel = "Deep q_{T} [GeV]"
mtlabel = "Deep m_{T} [GeV]"
DrawHistos(histos_met,
legends,
0.,
150.,
metlabel,
ymin,
ymax,
"Ratio",
"h_wjets_MCratio_deepmet_pt_{}".format(outputtag),
dology=False,
drawashist=True,
mycolors=colors,
linestyles=linestyles,
legendPos=legendPos,
legendNCols=legendNCols)
DrawHistos(histos_u_pt,
legends,
0.,
140.,
qtlabel,
ymin,
ymax,
"Ratio",
"h_wjets_MCratio_u_reco_pt_Deep_{}".format(outputtag),
dology=False,
drawashist=True,
mycolors=colors,
linestyles=linestyles,
legendPos=legendPos,
legendNCols=legendNCols)
DrawHistos(histos_mt,
legends,
0.,
140.,
mtlabel,
ymin,
ymax,
"Ratio",
"h_wjets_MCratio_mT_Deep_{}".format(outputtag),
dology=False,
drawashist=True,
mycolors=colors,
linestyles=linestyles,
legendPos=legendPos,
legendNCols=legendNCols)
colors = [1, 2]
linestyles = [1, 1]
legends = ["amc@NLO", "MadGraph"]
compMCRatios(["corr_central", "corr_central_MG"],
colors,
linestyles,
legends,
"MCSample",
ymin=0.9,
ymax=1.1)
legends = ["2-Gaussian Fit", "Gaussian Smoothing"]
compMCRatios(["corr_central", "corr_central_GKS"],
colors,
linestyles,
legends,
"FitVSSmoothing",
ymin=0.9,
ymax=1.1)
legends = [
"#mu_{r}=1, #mu_{f}=1", "#mu_{r}=1, #mu_{f}=0.5",
"#mu_{r}=1, #mu_{f}=2", "#mu_{r}=0.5, #mu_{f}=1",
"#mu_{r}=2, #mu_{f}=1", "#mu_{r}=0.5, #mu_{f}=0.5",
"#mu_{r}=2, #mu_{f}=2"
]
postfixs = [
"corr_central", "corr_mur_1_muf_0p5", "corr_mur_1_muf_2",
"corr_mur_0p5_muf_1", "corr_mur_2_muf_1", "corr_mur_0p5_muf_0p5",
"corr_mur_2_muf_2"
]
colors = [1, 2, 3, 4, 5, 6, 7]
linestyles = [1, 1, 1, 1, 1, 1, 1]
compMCRatios(postfixs,
colors,
linestyles,
legends,
"QCDScale",
ymin=0.9,
ymax=1.1)
colors = [1, 2, 3, 4, 5, 6, 7, 8, 9]
linestyles = [1, 1, 1, 1, 1, 1, 1, 1, 1]
legends = [
"central", "MadGraph", "Gauss Smoothing", "#mu_{r}=1, #mu_{f}=0.5",
"#mu_{r}=1, #mu_{f}=2", "#mu_{r}=0.5, #mu_{f}=1",
"#mu_{r}=2, #mu_{f}=1", "#mu_{r}=0.5, #mu_{f}=0.5",
"#mu_{r}=2, #mu_{f}=2"
]
postfixs = [
"corr_central", "corr_central_MG", "corr_central_GKS",
"corr_mur_1_muf_0p5", "corr_mur_1_muf_2", "corr_mur_0p5_muf_1",
"corr_mur_2_muf_1", "corr_mur_0p5_muf_0p5", "corr_mur_2_muf_2"
]
compMCRatios(postfixs,
colors,
linestyles,
legends,
"Systematics",
ymin=0.9,
ymax=1.1)
colors = [1, 2, 3, 4, 5, 6, 7]
linestyles = [1, 1, 1, 1, 1, 1, 1]
legends = [
"#mu_{r}=1, #mu_{f}=1", "#mu_{r}=1, #mu_{f}=0.5",
"#mu_{r}=1, #mu_{f}=2", "#mu_{r}=0.5, #mu_{f}=1",
"#mu_{r}=2, #mu_{f}=1", "#mu_{r}=0.5, #mu_{f}=0.5",
"#mu_{r}=2, #mu_{f}=2"
]
postfixs = [
"wjetsqcdscale_central", "wjetsqcdscale_mur_1_muf_0p5",
"wjetsqcdscale_mur_1_muf_2", "wjetsqcdscale_mur_0p5_muf_1",
"wjetsqcdscale_mur_2_muf_1", "wjetsqcdscale_mur_0p5_muf_0p5",
"wjetsqcdscale_mur_2_muf_2"
]
compMCRatios(postfixs, colors, linestyles, legends, "WJetsQCDScale")
colors = [1, 2, 3, 4, 5, 6, 7]
linestyles = [1, 1, 1, 1, 1, 1, 1]
legends = [
"#mu_{r}=1, #mu_{f}=1", "#mu_{r}=1, #mu_{f}=0.5",
"#mu_{r}=1, #mu_{f}=2", "#mu_{r}=0.5, #mu_{f}=1",
"#mu_{r}=2, #mu_{f}=1", "#mu_{r}=0.5, #mu_{f}=0.5",
"#mu_{r}=2, #mu_{f}=2"
]
postfixs = [
"corr_central_wjetsqcdscale_central",
"corr_central_wjetsqcdscale_mur_1_muf_0p5",
"corr_central_wjetsqcdscale_mur_1_muf_2",
"corr_central_wjetsqcdscale_mur_0p5_muf_1",
"corr_central_wjetsqcdscale_mur_2_muf_1",
"corr_central_wjetsqcdscale_mur_0p5_muf_0p5",
"corr_central_wjetsqcdscale_mur_2_muf_2"
]
compMCRatios(postfixs, colors, linestyles, legends, "corr_WJetsQCDScale")
colors = [1, 2, 3]
linestyles = [1, 1, 1]
postfixs = [
"corr_central_MuIso0", "corr_central_MuIso1", "corr_central_MuIso2"
]
legends = ["0.30<I<0.60", "0.30<I<0.45", "0.45<I<0.60"]
legends = ["From m_{T} < 40", "From m_{T} < 30", "From m_{T} < 50"]
compMCRatios(postfixs, colors, linestyles, legends, "corr_MuIso")
return
def main():
print "Program start..."
#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")')
input_data = "inputs/wenu/input_data.txt"
input_we0 = "inputs/wenu/input_we0.txt"
input_we1 = "inputs/wenu/input_we1.txt"
input_we2 = "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"
input_antiiso_data = "inputs/awenu/input_data.txt"
input_antiiso_we0 = "inputs/awenu/input_we0.txt"
input_antiiso_we1 = "inputs/awenu/input_we1.txt"
input_antiiso_we2 = "inputs/awenu/input_we2.txt"
input_antiiso_ttbar = "inputs/awenu/input_ttbar_dilepton.txt"
input_antiiso_ttbar_1lep = "inputs/awenu/input_ttbar_singlelepton.txt"
input_antiiso_ttbar_0lep = "inputs/awenu/input_ttbar_hadronic.txt"
input_antiiso_ww = "inputs/awenu/input_ww.txt"
input_antiiso_wz = "inputs/awenu/input_wz.txt"
input_antiiso_zz = "inputs/awenu/input_zz.txt"
input_antiiso_zxx = "inputs/awenu/input_zxx.txt"
input_antiiso_wx0 = "inputs/awenu/input_wx0.txt"
input_antiiso_wx1 = "inputs/awenu/input_wx1.txt"
input_antiiso_wx2 = "inputs/awenu/input_wx2.txt"
DataSamp = Sample(input_data,
isMC=False,
legend="Data",
name="Data",
isWSR=True)
# W -> enu
wjetsnorm = 1.075
Wm0Samp = Sample(input_we0,
isMC=True,
name="we0",
isWSR=True,
additionalnorm=wjetsnorm)
Wm1Samp = Sample(input_we1,
isMC=True,
name="we1",
isWSR=True,
additionalnorm=wjetsnorm)
Wm2Samp = Sample(input_we2,
isMC=True,
name="we2",
isWSR=True,
additionalnorm=wjetsnorm)
# ttbar
ttbarnorm = 1.2054
TTbarSamp = Sample(input_ttbar,
isMC=True,
name="ttbar_dilepton",
isWSR=True,
additionalnorm=ttbarnorm)
TT1LepSamp = Sample(input_ttbar_1lep,
isMC=True,
name="ttbar_1lepton",
isWSR=True,
additionalnorm=ttbarnorm)
TT0LepSamp = Sample(input_ttbar_0lep,
isMC=True,
name="ttbar_0lepton",
isWSR=True,
additionalnorm=ttbarnorm)
## 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)
Wx0Samp = Sample(input_wx0, isMC=True, name="wx0", isWSR=True)
Wx1Samp = Sample(input_wx1, isMC=True, name="wx1", isWSR=True)
Wx2Samp = Sample(input_wx2, isMC=True, name="wx2", isWSR=True)
## for the QCD background estimation (data-driven)
qcdnorm = 16.7254
DataAisoSamp = Sample(input_antiiso_data,
isMC=False,
name="Data_aiso",
isWSR=True,
additionalnorm=qcdnorm,
legend='QCD',
color='226')
# W -> enu
Wm0AisoSamp = Sample(input_antiiso_we0,
isMC=True,
name="we0_aiso",
isWSR=True,
additionalnorm=-1.0 * qcdnorm)
Wm1AisoSamp = Sample(input_antiiso_we1,
isMC=True,
name="we1_aiso",
isWSR=True,
additionalnorm=-1.0 * qcdnorm)
Wm2AisoSamp = Sample(input_antiiso_we2,
isMC=True,
name="we2_aiso",
isWSR=True,
additionalnorm=-1.0 * qcdnorm)
# ttbar
TTbarAisoSamp = Sample(input_antiiso_ttbar,
isMC=True,
name="ttbar_dilepton_aiso",
isWSR=True,
additionalnorm=-1.0 * qcdnorm)
TT1LepAisoSamp = Sample(input_antiiso_ttbar_1lep,
isMC=True,
name="ttbar_1lepton_aiso",
isWSR=True,
additionalnorm=-1.0 * qcdnorm)
TT0LepAisoSamp = Sample(input_antiiso_ttbar_0lep,
isMC=True,
name="ttbar_0lepton_aiso",
isWSR=True,
additionalnorm=-1.0 * qcdnorm)
## dibosons
WWAisoSamp = Sample(input_antiiso_ww,
isMC=True,
name="WW_aiso",
isWSR=True,
additionalnorm=-1.0 * qcdnorm)
WZAisoSamp = Sample(input_antiiso_wz,
isMC=True,
name="WZ_aiso",
isWSR=True,
additionalnorm=-1.0 * qcdnorm)
ZZAisoSamp = Sample(input_antiiso_zz,
isMC=True,
name="ZZ_aiso",
isWSR=True,
additionalnorm=-1.0 * qcdnorm)
# tau
ZXXAisoSamp = Sample(input_antiiso_zxx,
isMC=True,
name="ZXX_aiso",
isWSR=True,
additionalnorm=-1.0 * qcdnorm)
Wx0AisoSamp = Sample(input_antiiso_wx0,
isMC=True,
name="wx0_aiso",
isWSR=True,
additionalnorm=-1.0 * qcdnorm)
Wx1AisoSamp = Sample(input_antiiso_wx1,
isMC=True,
name="wx1_aiso",
isWSR=True,
additionalnorm=-1.0 * qcdnorm)
Wx2AisoSamp = Sample(input_antiiso_wx2,
isMC=True,
name="wx2_aiso",
isWSR=True,
additionalnorm=-1.0 * qcdnorm)
sampMan = SampleManager(DataSamp, [
Wm0Samp, Wm1Samp, Wm2Samp, TTbarSamp, TT1LepSamp, TT0LepSamp, WWSamp,
WZSamp, ZZSamp, ZXXSamp, Wx0Samp, Wx1Samp, Wx2Samp, DataAisoSamp,
Wm0AisoSamp, Wm1AisoSamp, Wm2AisoSamp, TTbarAisoSamp, TT1LepAisoSamp,
TT0LepAisoSamp, WWAisoSamp, WZAisoSamp, ZZAisoSamp, ZXXAisoSamp,
Wx0AisoSamp, Wx1AisoSamp, Wx2AisoSamp
])
#sampMan = SampleManager(DataSamp, [Wm0Samp, Wm1Samp, Wm2Samp, TTbarSamp, TT1LepSamp, TT0LepSamp, WWSamp, WZSamp, ZZSamp, ZXXSamp, Wx0Samp, Wx1Samp, Wx2Samp,
# DataAisoSamp])
sampMan.groupMCs(["WW", "WZ", "ZZ", "ZXX", "wx0", "wx1", "wx2"], "EWK",
216, "EWK")
sampMan.groupMCs(["ttbar_dilepton", "ttbar_1lepton", "ttbar_0lepton"],
"ttbar", 96, "t#bar{t}")
sampMan.groupMCs(['we0', 'we1', 'we2'], "wenu", 92, "W#rightarrow e#nu")
sampMan.groupMCs([
'Data_aiso', 'we0_aiso', 'we1_aiso', 'we2_aiso', 'ttbar_dilepton_aiso',
'ttbar_1lepton_aiso', 'ttbar_0lepton_aiso', 'WW_aiso', 'WZ_aiso',
'ZZ_aiso', 'ZXX_aiso', 'wx0_aiso', 'wx1_aiso', 'wx2_aiso'
], 'QCD', 226, 'QCD')
sampMan.ApplyCutSpecificMCs('relIso > 0.35 && relIso < 0.45',
sampgroupnames=['QCD'])
#sampMan.DefineAll("zpt", "Z.Pt()")
#sampMan.DefineAll("zmass", "ZMass")
#sampMan.DefineAll("zy", "Z.Rapidity()")
#sampMan.DefineAll("zeta", "Z.Rapidity()")
#sampMan.DefineAll("nPV", "npv")
sampMan.DefineAll("Muon_pt", "lep.Pt()")
sampMan.DefineAll("Muon_eta", "lep.Eta()")
sampMan.DefineMC("met_pt", "metVars[1]", excludes=['Data_aiso'])
sampMan.DefineMC("met_phi",
"TVector2::Phi_mpi_pi(metVarsPhi[1])",
excludes=['Data_aiso'])
# Data does not run any recoil corrections
DataSamp.Define("met_pt", "metVars[0]")
DataSamp.Define("met_phi", "TVector2::Phi_mpi_pi(metVarsPhi[0])")
DataAisoSamp.Define("met_pt", "metVars[0]")
DataAisoSamp.Define("met_phi", "TVector2::Phi_mpi_pi(metVarsPhi[0])")
sampMan.DefineAll("met_raw_pt", "metVars[0]")
sampMan.DefineAll("met_raw_phi", "TVector2::Phi_mpi_pi(metVarsPhi[0])")
sampMan.DefineAll("weight_wplus",
"weight_WoVpt * (q>0)",
excludeGroups=['QCD'])
sampMan.DefineAll("weight_wminus",
"weight_WoVpt * (q<0)",
excludeGroups=['QCD'])
sampMan.DefineSpecificMCs("weight_wplus",
"weight_WoVpt * (q>0)",
sampgroupnames=['QCD'])
sampMan.DefineSpecificMCs("weight_wminus",
"weight_WoVpt * (q<0)",
sampgroupnames=['QCD'])
# deltaPhi
sampMan.DefineAll("deltaPhi", "TVector2::Phi_0_2pi(lep.Phi() - met_phi)")
# recoil variables
sampMan.DefineAll("V2W", "UVec(lep.Pt(), lep.Phi(), met_pt, met_phi)")
sampMan.DefineAll("WpT", "V2W.Mod()")
sampMan.DefineAll("Wphi", "TVector2::Phi_mpi_pi(V2W.Phi())")
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
])
u1_bins = np.array([
-40., -36., -32., -28., -25., -22.0, -20.0, -18, -16, -14, -12, -10,
-8, -6, -4, -2, 0, 2, 4, 6, 8, 10, 12, 14, 16, 18, 20, 22, 24, 26, 28,
30, 32, 34, 36, 38, 40, 42, 44, 46, 48, 50, 53, 56, 59, 64, 68, 72, 76,
80, 85, 90, 100
])
u2_bins = np.array([
-80., -70., -65., -60., -56., -52, -48, -44, -40, -37, -34, -31, -28,
-25., -22., -20, -18, -16, -14, -12, -10, -8, -6, -4, -2, 0, 2, 4, 6,
8, 10, 12, 16, 18, 20, 22, 25, 28, 31, 34, 37, 40, 44, 48, 52, 56, 60,
65, 70, 80
])
#u_bins = np.array([0., 2., 4., 6, 8, 10, 12, 14, 16, 18, 20, 22, 24, 26, 28, 30, 32, 34, 36, 38, 40, 43, 46, 49, 52, 56, 60, 64, 68, 72, 76, 80, 85, 90, 95, 100, 105, 110, 115, 120, 130, 140, 150])
mt_bins = np.concatenate(
(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)))
u_bins = np.concatenate((np.linspace(0, 20, 11), np.linspace(24, 80, 15),
np.linspace(85, 109, 4), np.linspace(120, 150,
3)))
u_bins = np.concatenate((np.linspace(0, 20, 11), np.linspace(24, 60, 10)))
#sampMan.cacheDraw("zpt", "histo_wjets_zpt_WoZptWeight_enu", u_bins, DrawConfig(xmin=0, xmax=150, xlabel='p_{T}^{#mu#mu} [GeV]'), weightname="weight_WoVpt")
#sampMan.cacheDraw("zmass", "histo_wjets_zmass_enu", mass_bins, DrawConfig(xmin=70, xmax=110, xlabel='m_{#mu#mu} [GeV]'))
#sampMan.cacheDraw("zeta", "histo_wjets_zeta_enu", eta_bins, DrawConfig(xmin=-2.5, xmax=2.5, xlabel='#eta_{#mu#mu} [GeV]', ymax=1e7, ylabel='Events / 1'))
#sampMan.cacheDraw("zy", "histo_wjets_zrapidity_enu", eta_bins, DrawConfig(xmin=-2.5, xmax=2.5, xlabel='y_{#mu#mu} [GeV]', ymax=1e7, ylabel='Events / 1'))
sf = 0.7
# nPV
sampMan.cacheDraw(
"npv", "histo_nPV_enu", 10, 0, 10,
DrawConfig(xmin=0,
xmax=10,
xlabel='# PV',
ylabel='Events / 1',
dology=False,
ymax=9e5 * sf))
sampMan.cacheDraw("npv",
"histo_nPV_eplusnu",
10,
0,
10,
DrawConfig(xmin=0,
xmax=10,
xlabel='# PV',
ylabel='Events / 1',
dology=False,
ymax=5e5 * sf),
weightname="weight_wplus")
sampMan.cacheDraw("npv",
"histo_nPV_eminusnu",
10,
0,
10,
DrawConfig(xmin=0,
xmax=10,
xlabel='# PV',
ylabel='Events / 1',
dology=False,
ymax=4.5e5 * sf),
weightname="weight_wminus")
# lepton pt
sampMan.cacheDraw(
"Muon_pt", "histo_Muon_pt_enu", pt_bins,
DrawConfig(xmin=20,
xmax=70,
xlabel='p_{T}(e) [GeV]',
dology=False,
ymax=1.05e5 * sf))
sampMan.cacheDraw(
"Muon_eta", "histo_Muon_eta_enu", eta_bins,
DrawConfig(xmin=-2.6,
xmax=2.6,
xlabel='#eta (e) [GeV]',
ylabel='Events / 1',
dology=False,
ymax=6e5 * sf))
sampMan.cacheDraw("Muon_pt",
"histo_Muon_pt_eplusnu",
pt_bins,
DrawConfig(xmin=20,
xmax=70,
xlabel='p_{T}(e) [GeV]',
dology=False,
ymax=6.05e4 * sf),
weightname="weight_wplus")
sampMan.cacheDraw("Muon_eta",
"histo_Muon_eta_eplusnu",
eta_bins,
DrawConfig(xmin=-2.6,
xmax=2.6,
xlabel='#eta (e) [GeV]',
ylabel='Events / 1',
dology=False,
ymax=4e5 * sf),
weightname="weight_wminus")
sampMan.cacheDraw("Muon_pt",
"histo_Muon_pt_eminusnu",
pt_bins,
DrawConfig(xmin=20,
xmax=70,
xlabel='p_{T}(e) [GeV]',
dology=False,
ymax=5.05e4 * sf),
weightname="weight_wminus")
sampMan.cacheDraw("Muon_eta",
"histo_Muon_eta_eminusnu",
eta_bins,
DrawConfig(xmin=-2.6,
xmax=2.6,
xlabel='#eta (e) [GeV]',
ylabel='Events / 1',
dology=False,
ymax=3.5e5 * sf),
weightname="weight_wminus")
# met and raw_met
sampMan.cacheDraw(
"met_pt", "histo_wjets_enu_pfmet_pt", met_pt_bins,
DrawConfig(xmin=0,
xmax=80,
xlabel='PF MET [GeV]',
dology=False,
ymax=8e4 * sf))
sampMan.cacheDraw(
"met_phi", "histo_wjets_enu_pfmet_phi", 30, phimin, phimax,
DrawConfig(xmin=phimin,
xmax=phimax,
xlabel='PF MET #phi',
dology=False,
ymax=6e5 * sf))
sampMan.cacheDraw(
"met_raw_pt", "histo_wjets_enu_pfmet_raw_pt", met_pt_bins,
DrawConfig(xmin=0,
xmax=80,
xlabel='Raw PF MET [GeV]',
dology=False,
ymax=8e4 * sf))
sampMan.cacheDraw(
"met_raw_phi", "histo_wjets_enu_pfmet_raw_phi", 30, phimin, phimax,
DrawConfig(xmin=phimin,
xmax=phimax,
xlabel='Raw PF MET #phi',
dology=False,
ymax=6e5 * sf))
sampMan.cacheDraw("met_pt",
"histo_wjets_eplusnu_pfmet_pt",
met_pt_bins,
DrawConfig(xmin=0,
xmax=80,
xlabel='PF MET [GeV]',
dology=False,
ymax=5e4 * sf),
weightname="weight_wplus")
sampMan.cacheDraw("met_phi",
"histo_wjets_eplusnu_pfmet_phi",
30,
phimin,
phimax,
DrawConfig(xmin=phimin,
xmax=phimax,
xlabel='PF MET #phi',
dology=False,
ymax=4e5 * sf),
weightname="weight_wplus")
sampMan.cacheDraw("met_raw_pt",
"histo_wjets_eplusnu_pfmet_raw_pt",
met_pt_bins,
DrawConfig(xmin=0,
xmax=80,
xlabel='Raw PF MET [GeV]',
dology=False,
ymax=5e4 * sf),
weightname="weight_wplus")
sampMan.cacheDraw("met_raw_phi",
"histo_wjets_eplusnu_pfmet_raw_phi",
30,
phimin,
phimax,
DrawConfig(xmin=phimin,
xmax=phimax,
xlabel='Raw PF MET #phi',
dology=False,
ymax=3.5e5 * sf),
weightname="weight_wplus")
sampMan.cacheDraw("met_pt",
"histo_wjets_eminusnu_pfmet_pt",
met_pt_bins,
DrawConfig(xmin=0,
xmax=80,
xlabel='PF MET [GeV]',
dology=False,
ymax=4e4 * sf),
weightname="weight_wminus")
sampMan.cacheDraw("met_phi",
"histo_wjets_eminusnu_pfmet_phi",
30,
phimin,
phimax,
DrawConfig(xmin=phimin,
xmax=phimax,
xlabel='PF MET #phi',
dology=False,
ymax=3e5 * sf),
weightname="weight_wminus")
sampMan.cacheDraw("met_raw_pt",
"histo_wjets_eminusnu_pfmet_raw_pt",
met_pt_bins,
DrawConfig(xmin=0,
xmax=80,
xlabel='Raw PF MET [GeV]',
dology=False,
ymax=4e4 * sf),
weightname="weight_wminus")
sampMan.cacheDraw("met_raw_phi",
"histo_wjets_eminusnu_pfmet_raw_phi",
30,
phimin,
phimax,
DrawConfig(xmin=phimin,
xmax=phimax,
xlabel='Raw PF MET #phi',
dology=False,
ymax=3e5 * sf),
weightname="weight_wminus")
# deltaPhi
sampMan.cacheDraw(
"deltaPhi", "histo_wjets_enu_deltaphi", dphi_bins,
DrawConfig(xmin=0.,
xmax=2 * phimax,
xlabel='#Delta #phi(e, MET)',
dology=False,
ymax=2e6 * sf))
sampMan.cacheDraw("deltaPhi",
"histo_wjets_eplusnu_deltaphi",
dphi_bins,
DrawConfig(xmin=0.,
xmax=2 * phimax,
xlabel='#Delta #phi(e, MET)',
dology=False,
ymax=1.4e6 * sf),
weightname="weight_wplus")
sampMan.cacheDraw("deltaPhi",
"histo_wjets_eminusnu_deltaphi",
dphi_bins,
DrawConfig(xmin=0.,
xmax=2 * phimax,
xlabel='#Delta #phi(e, MET)',
dology=False,
ymax=1.4e6 * sf),
weightname="weight_wminus")
# mt
sampMan.cacheDraw(
"mtCorr", "histo_wjets_enu_mtcorr", mt_bins,
DrawConfig(xmin=40,
xmax=120,
xlabel="m_{T} [GeV]",
dology=False,
ymax=7e4 * sf))
sampMan.cacheDraw("mtCorr",
"histo_wjets_eplusnu_mtcorr",
mt_bins,
DrawConfig(xmin=40,
xmax=120,
xlabel="m_{T} [GeV]",
dology=False,
ymax=4e4 * sf),
weightname="weight_wplus")
sampMan.cacheDraw("mtCorr",
"histo_wjets_eminusnu_mtcorr",
mt_bins,
DrawConfig(xmin=40,
xmax=120,
xlabel="m_{T} [GeV]",
dology=False,
ymax=3.5e4 * sf),
weightname="weight_wminus")
# W pt
sampMan.cacheDraw(
"WpT", "histo_wjets_enu_wpt", u_bins,
DrawConfig(xmin=0.,
xmax=60,
xlabel="p^{W}_{T} [GeV]",
dology=False,
ymax=1.1e5 * sf))
sampMan.cacheDraw("WpT",
"histo_wjets_eplusnu_wpt",
u_bins,
DrawConfig(xmin=0.,
xmax=60,
xlabel="p^{W}_{T} [GeV]",
dology=False,
ymax=7e4 * sf),
weightname="weight_wplus")
sampMan.cacheDraw("WpT",
"histo_wjets_eminusnu_wpt",
u_bins,
DrawConfig(xmin=0.,
xmax=60,
xlabel="p^{W}_{T} [GeV]",
dology=False,
ymax=5.0e4 * sf),
weightname="weight_wminus")
sampMan.cacheDraw(
"Wphi", "histo_wjets_enu_wphi", 30, phimin, phimax,
DrawConfig(xmin=phimin,
xmax=phimax,
xlabel="#phi^{W}",
dology=False,
ymax=6e5 * sf))
sampMan.cacheDraw("Wphi",
"histo_wjets_eplusnu_wphi",
30,
phimin,
phimax,
DrawConfig(xmin=phimin,
xmax=phimax,
xlabel="#phi^{W}",
dology=False,
ymax=4e5 * sf),
weightname="weight_wplus")
sampMan.cacheDraw("Wphi",
"histo_wjets_eminusnu_wphi",
30,
phimin,
phimax,
DrawConfig(xmin=phimin,
xmax=phimax,
xlabel="#phi^{W}",
dology=False,
ymax=3e5 * sf),
weightname="weight_wminus")
sampMan.launchDraw()
sampMan.dumpCounts()
print "Program end..."
raw_input()
return
def main():
print "Program start..."
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 dotest:
input_data = "inputs/inputs_Z/input_data_test.txt"
input_dy = "inputs/inputs_Z/input_zjets_test.txt"
input_ttbar = "inputs/inputs_Z/input_ttbar_test.txt"
else:
input_data = "inputs/inputs_Z/input_data.txt"
input_dy = "inputs/inputs_Z/input_zjets.txt"
input_ttbar = "inputs/inputs_Z/input_ttbar.txt"
input_WW2L = "inputs/inputs_Z/input_WWTo2L2Nu.txt"
input_WZ3L = "inputs/inputs_Z/input_WZTo3LNu.txt"
input_ZZ2L = "inputs/inputs_Z/input_ZZTo2L2Nu.txt"
input_ZZ4L = "inputs/inputs_Z/input_ZZTo4L.txt"
input_lept = "inputs/inputs_Z/input_ttbar_singlelep_fromT.txt"
input_leptbar = "inputs/inputs_Z/input_ttbar_singlelep_fromTbar.txt"
DataSamp = Sample(input_data,
isMC=False,
legend="Data",
name="Data",
bjetVeto=VetoB)
DYSamp = Sample(input_dy,
xsec=6077.22 * 1e3,
color=5,
reweightzpt=True,
legend="DY",
name="DY",
bjetVeto=VetoB)
TTbarSamp = Sample(input_ttbar,
xsec=831.76 * 0.105 * 1e3,
color=46,
reweightzpt=False,
legend="t#bar{t}",
name="ttbar",
bjetVeto=VetoB)
if not dotest:
WW2LSamp = Sample(input_WW2L,
xsec=12.178 * 1e3,
color=38,
reweightzpt=False,
legend="WW2L",
name="WW2L",
bjetVeto=VetoB)
WZ3LSamp = Sample(input_WZ3L,
xsec=5.26 * 1e3,
color=39,
reweightzpt=False,
legend="WZ3L",
name="WZ3L",
bjetVeto=VetoB)
ZZ2LSamp = Sample(input_ZZ2L,
xsec=0.564 * 1e3,
color=37,
reweightzpt=False,
legend="ZZ2L",
name="ZZ2L",
bjetVeto=VetoB)
ZZ4LSamp = Sample(input_ZZ4L,
xsec=1.212 * 1e3,
color=36,
reweightzpt=False,
legend="ZZ4L",
name="ZZ4L",
bjetVeto=VetoB)
#TTLepTSamp = Sample(input_lept, xsec = 831.76*0.219*1e3, color=47, reweightzpt = False, legend="t#bar{t}", name="ttbarlept", bjetVeto=VetoB)
#TTLepTbarSamp = Sample(input_leptbar, xsec = 831.76*0.219*1e3, color=48, reweightzpt = False, legend="t#bar{t}", name="ttbarleptb", bjetVeto=VetoB)
if not dotest:
sampMan = SampleManager(
DataSamp,
[DYSamp, WW2LSamp, WZ3LSamp, TTbarSamp, ZZ2LSamp, ZZ4LSamp])
else:
sampMan = SampleManager(DataSamp, [DYSamp, TTbarSamp])
sampMan.groupMCs(["WW2L", "WZ3L", "ZZ2L", "ZZ4L"], "Dibosons", 38,
"Dibosons")
sampMan.DefineAll("zpt", "Z_pt")
# define u1 and u2 for PUPPI and PF
# u1 and u2 for DeepMET has already been defined in SampleManager
sampMan.DefineAll("Uvec_PF", "UVec(Z_pt, Z_phi, met_pt, met_phi)")
sampMan.DefineAll("u_PF_pt", "Uvec_PF.Mod()")
sampMan.DefineAll("u_PF_phi", "Uvec_PF.Phi()")
sampMan.DefineAll("u1_PF",
"u_PF_pt * TMath::Cos(u_PF_phi + TMath::Pi() - Z_phi)")
sampMan.DefineAll("u2_PF",
"u_PF_pt * TMath::Sin(u_PF_phi + TMath::Pi() - Z_phi)")
sampMan.DefineAll("Uvec_PUPPI",
"UVec(Z_pt, Z_phi, puppimet_pt, puppimet_phi)")
sampMan.DefineAll("u_PUPPI_pt", "Uvec_PUPPI.Mod()")
sampMan.DefineAll("u_PUPPI_phi", "Uvec_PUPPI.Phi()")
sampMan.DefineAll(
"u1_PUPPI",
"u_PUPPI_pt * TMath::Cos(u_PUPPI_phi + TMath::Pi() - Z_phi)")
sampMan.DefineAll(
"u2_PUPPI",
"u_PUPPI_pt * TMath::Sin(u_PUPPI_phi + TMath::Pi() - Z_phi)")
# Default correction:
ROOT.gROOT.ProcessLine(
'TFile* fitfunctions_Data = TFile::Open("results/Fit/fitfunctions_Data_njets_pt_central.root")'
)
ROOT.gROOT.ProcessLine(
'TH1F* h1_ptbins_Data_central = (TH1F*)fitfunctions_Data->Get("h1_ptbins_Data_central")'
)
ROOT.gROOT.ProcessLine(
'TH1F* h1_njetbins_Data_central = (TH1F*)fitfunctions_Data->Get("h1_njetbins_Data_central")'
)
ROOT.gROOT.ProcessLine(
'TList* tfs_Data_u1_njets_pt_central = (TList*)fitfunctions_Data->Get("tfs_Data_u1_njets_pt_central")'
)
ROOT.gROOT.ProcessLine(
'TList* tfs_Data_u2_njets_pt_central = (TList*)fitfunctions_Data->Get("tfs_Data_u2_njets_pt_central")'
)
ROOT.gROOT.ProcessLine(
'TFile* fitfunctions_ZJets_NLO_central = TFile::Open("results/Fit/fitfunctions_ZJets_NLO_njets_pt_central.root")'
)
ROOT.gROOT.ProcessLine(
'TList* tfs_MC_u1_njets_pt_central = (TList*)fitfunctions_ZJets_NLO_central->Get("tfs_ZJets_NLO_u1_njets_pt_central")'
)
ROOT.gROOT.ProcessLine(
'TList* tfs_MC_u2_njets_pt_central = (TList*)fitfunctions_ZJets_NLO_central->Get("tfs_ZJets_NLO_u2_njets_pt_central")'
)
DYSamp.Define(
"u1_corr_central",
"UCorrection_Quant(u1, jet_n, Z_pt, h1_njetbins_Data_central, h1_ptbins_Data_central, tfs_Data_u1_njets_pt_central, tfs_MC_u1_njets_pt_central, 0.00001)"
)
DYSamp.Define(
"u2_corr_central",
"UCorrection_Quant(u2, jet_n, Z_pt, h1_njetbins_Data_central, h1_ptbins_Data_central, tfs_Data_u2_njets_pt_central, tfs_MC_u2_njets_pt_central, 0.00001)"
)
DYSamp.Define(
"u_pt_corr_central",
"TMath::Sqrt(u1_corr_central*u1_corr_central + u2_corr_central*u2_corr_central)"
)
sampMan.DefineAll("u1_corr_central", "u1", excludes=['DY'])
sampMan.DefineAll("u2_corr_central", "u2", excludes=['DY'])
sampMan.DefineAll("u_pt_corr_central", "u_pt", excludes=['DY'])
sampMan.DefineAll("deepmet_corr_central",
"METVec(Z_pt, Z_phi, u1_corr_central, u2_corr_central)")
sampMan.DefineAll("deepmet_pt_corr_central", "deepmet_corr_central.Mod()")
sampMan.DefineAll("deepmet_phi_corr_central",
"TVector2::Phi_mpi_pi(deepmet_corr_central.Phi())")
# systematic variations
# corrections from MadGraph
ROOT.gROOT.ProcessLine(
'TFile* fitfunctions_ZJets_MG_central = TFile::Open("results/Fit/fitfunctions_ZJets_MG_njets_pt_central.root")'
)
ROOT.gROOT.ProcessLine(
'TList* tfs_MC_MG_u1_njets_pt_central = (TList*)fitfunctions_ZJets_MG_central->Get("tfs_ZJets_MG_u1_njets_pt_central")'
)
ROOT.gROOT.ProcessLine(
'TList* tfs_MC_MG_u2_njets_pt_central = (TList*)fitfunctions_ZJets_MG_central->Get("tfs_ZJets_MG_u2_njets_pt_central")'
)
DYSamp.Define(
"u1_corr_central_MG",
"UCorrection_Quant(u1, jet_n, Z_pt, h1_njetbins_Data_central, h1_ptbins_Data_central, tfs_Data_u1_njets_pt_central, tfs_MC_MG_u1_njets_pt_central, 0.00001)"
)
DYSamp.Define(
"u2_corr_central_MG",
"UCorrection_Quant(u2, jet_n, Z_pt, h1_njetbins_Data_central, h1_ptbins_Data_central, tfs_Data_u2_njets_pt_central, tfs_MC_MG_u2_njets_pt_central, 0.00001)"
)
DYSamp.Define(
"u_pt_corr_central_MG",
"TMath::Sqrt(u1_corr_central_MG*u1_corr_central_MG + u2_corr_central_MG*u2_corr_central_MG)"
)
sampMan.DefineAll("u1_corr_central_MG", "u1", excludes=['DY'])
sampMan.DefineAll("u2_corr_central_MG", "u2", excludes=['DY'])
sampMan.DefineAll("u_pt_corr_central_MG", "u_pt", excludes=['DY'])
sampMan.DefineAll(
"deepmet_corr_central_MG",
"METVec(Z_pt, Z_phi, u1_corr_central_MG, u2_corr_central_MG)")
sampMan.DefineAll("deepmet_pt_corr_central_MG",
"deepmet_corr_central_MG.Mod()")
sampMan.DefineAll("deepmet_phi_corr_central_MG",
"TVector2::Phi_mpi_pi(deepmet_corr_central_MG.Phi())")
# corrections from Gaussian Smearing
ROOT.gROOT.ProcessLine(
'TFile* gaussSmoother_Data_njets_pt_central = TFile::Open("results/GaussSmoother/gaussSmoother_Data_njets_pt_central.root")'
)
ROOT.gROOT.ProcessLine(
'TList* cdfs_Data_u1_njets_pt_central = (TList*)gaussSmoother_Data_njets_pt_central->Get("cdfs_Data_u1_njets_pt_central")'
)
ROOT.gROOT.ProcessLine(
'TList* cdfs_Data_u2_njets_pt_central = (TList*)gaussSmoother_Data_njets_pt_central->Get("cdfs_Data_u2_njets_pt_central")'
)
ROOT.gROOT.ProcessLine(
'TFile* gaussSmoother_ZJets_NLO_njets_pt_central = TFile::Open("results/GaussSmoother/gaussSmoother_ZJets_NLO_njets_pt_central.root")'
)
ROOT.gROOT.ProcessLine(
'TList* cdfs_ZJets_NLO_u1_njets_pt_central = (TList*)gaussSmoother_ZJets_NLO_njets_pt_central->Get("cdfs_ZJets_NLO_u1_njets_pt_central")'
)
ROOT.gROOT.ProcessLine(
'TList* cdfs_ZJets_NLO_u2_njets_pt_central = (TList*)gaussSmoother_ZJets_NLO_njets_pt_central->Get("cdfs_ZJets_NLO_u2_njets_pt_central")'
)
DYSamp.Define(
"u1_corr_central_GKS",
"UCorrection_Quant(u1, jet_n, Z_pt, h1_njetbins_Data_central, h1_ptbins_Data_central, cdfs_Data_u1_njets_pt_central, cdfs_ZJets_NLO_u1_njets_pt_central, 0.00001)"
)
DYSamp.Define(
"u2_corr_central_GKS",
"UCorrection_Quant(u2, jet_n, Z_pt, h1_njetbins_Data_central, h1_ptbins_Data_central, cdfs_Data_u2_njets_pt_central, cdfs_ZJets_NLO_u2_njets_pt_central, 0.00001)"
)
DYSamp.Define(
"u_pt_corr_central_GKS",
"TMath::Sqrt(u1_corr_central_GKS*u1_corr_central_GKS + u2_corr_central_GKS*u2_corr_central_GKS)"
)
sampMan.DefineAll("u1_corr_central_GKS", "u1", excludes=['DY'])
sampMan.DefineAll("u2_corr_central_GKS", "u2", excludes=['DY'])
sampMan.DefineAll("u_pt_corr_central_GKS", "u_pt", excludes=['DY'])
sampMan.DefineAll(
"deepmet_corr_central_GKS",
"METVec(Z_pt, Z_phi, u1_corr_central_GKS, u2_corr_central_GKS)")
sampMan.DefineAll("deepmet_pt_corr_central_GKS",
"deepmet_corr_central_GKS.Mod()")
sampMan.DefineAll("deepmet_phi_corr_central_GKS",
"TVector2::Phi_mpi_pi(deepmet_corr_central_GKS.Phi())")
# correction from ttbar qcd scale:
def varyQCDScale(wstring):
ROOT.gROOT.ProcessLine(
'TFile* fitfunctions_Data_{WS} = TFile::Open("results/Fit/fitfunctions_Data_njets_pt_{WS}.root")'
.format(WS=wstring))
ROOT.gROOT.ProcessLine(
'TList* tfs_Data_u1_njets_pt_{WS} = (TList*)fitfunctions_Data_{WS}->Get("tfs_Data_u1_njets_pt_{WS}")'
.format(WS=wstring))
ROOT.gROOT.ProcessLine(
'TList* tfs_Data_u2_njets_pt_{WS} = (TList*)fitfunctions_Data_{WS}->Get("tfs_Data_u2_njets_pt_{WS}")'
.format(WS=wstring))
DYSamp.Define(
"u1_corr_{}".format(wstring),
"UCorrection_Quant(u1, jet_n, Z_pt, h1_njetbins_Data_central, h1_ptbins_Data_central, tfs_Data_u1_njets_pt_{WS}, tfs_MC_u1_njets_pt_central, 0.00001)"
.format(WS=wstring))
DYSamp.Define(
"u2_corr_{}".format(wstring),
"UCorrection_Quant(u2, jet_n, Z_pt, h1_njetbins_Data_central, h1_ptbins_Data_central, tfs_Data_u2_njets_pt_{WS}, tfs_MC_u2_njets_pt_central, 0.00001)"
.format(WS=wstring))
DYSamp.Define(
"u_pt_corr_{}".format(wstring),
"TMath::Sqrt(u1_corr_{WS}*u1_corr_{WS} + u2_corr_{WS}*u2_corr_{WS})"
.format(WS=wstring))
sampMan.DefineAll("u1_corr_{}".format(wstring), "u1", excludes=['DY'])
sampMan.DefineAll("u2_corr_{}".format(wstring), "u2", excludes=['DY'])
sampMan.DefineAll("u_pt_corr_{}".format(wstring),
"u_pt",
excludes=['DY'])
sampMan.DefineAll(
"deepmet_corr_{}".format(wstring),
"METVec(Z_pt, Z_phi, u1_corr_{WS}, u2_corr_{WS})".format(
WS=wstring))
sampMan.DefineAll("deepmet_pt_corr_{}".format(wstring),
"deepmet_corr_{}.Mod()".format(wstring))
sampMan.DefineAll(
"deepmet_phi_corr_{}".format(wstring),
"TVector2::Phi_mpi_pi(deepmet_corr_{}.Phi())".format(wstring))
varyQCDScale("mur_1_muf_0p5")
varyQCDScale("mur_1_muf_2")
varyQCDScale("mur_0p5_muf_1")
varyQCDScale("mur_2_muf_1")
varyQCDScale("mur_0p5_muf_0p5")
varyQCDScale("mur_2_muf_2")
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, 90, 100, 110, 120, 135,
150, 165, 180, 200
])
u1_bins = np.array([
-40., -36., -32., -28., -25., -22.0, -20.0, -18, -16, -14, -12, -10,
-8, -6, -4, -2, 0, 2, 4, 6, 8, 10, 12, 14, 16, 18, 20, 22, 24, 26, 28,
30, 32, 34, 36, 38, 40, 42, 44, 46, 48, 50, 53, 56, 59, 64, 68, 72, 76,
80, 85, 90, 100
])
u2_bins = np.array([
-80., -70., -65., -60., -56., -52, -48, -44, -40, -37, -34, -31, -28,
-25., -22., -20, -18, -16, -14, -12, -10, -8, -6, -4, -2, 0, 2, 4, 6,
8, 10, 12, 16, 18, 20, 22, 25, 28, 31, 34, 37, 40, 44, 48, 52, 56, 60,
65, 70, 80
])
u_bins = np.array([
0., 2., 4., 6, 8, 10, 12, 14, 16, 18, 20, 22, 24, 26, 28, 30, 32, 34,
36, 38, 40, 43, 46, 49, 52, 56, 60, 64, 68, 72, 76, 80, 85, 90, 95,
100, 105, 110, 115, 120, 130, 140, 150
])
phimin = -ROOT.TMath.Pi()
phimax = ROOT.TMath.Pi()
# z pt befor and after pt reweighting
sampMan.cacheDraw("zpt",
"histo_zjets_zpt_WoZptWeight",
30,
0,
60,
DrawConfig(xmin=0, xmax=60, xlabel='p^{ll}_{T} [GeV]'),
weightname="weight_WoVpt")
sampMan.cacheDraw("zpt", "histo_zjets_zpt", 30, 0, 60,
DrawConfig(xmin=0, xmax=60, xlabel='p^{ll}_{T} [GeV]'))
sampMan.cacheDraw("met_pt", "histo_zjets_pfmet_pt", met_pt_bins,
DrawConfig(xmin=0, xmax=200, xlabel='PF MET [GeV]'))
sampMan.cacheDraw("met_phi", "histo_zjets_pfmet_phi", 30, phimin, phimax,
DrawConfig(xmin=phimin, xmax=phimax, xlabel='PF #phi'))
sampMan.cacheDraw("puppimet_pt", "histo_zjets_puppimet_pt", met_pt_bins,
DrawConfig(xmin=0, xmax=200, xlabel='PUPPI MET [GeV]'))
sampMan.cacheDraw(
"puppimet_phi", "histo_zjets_puppimet_phi", 30, phimin, phimax,
DrawConfig(xmin=phimin, xmax=phimax, xlabel='PUPPI #phi'))
# uncorrected deepmet
sampMan.cacheDraw("deepmet_pt", "histo_zjets_deepmet_pt", met_pt_bins,
DrawConfig(xmin=0, xmax=200, xlabel='Deep MET [GeV]'))
sampMan.cacheDraw(
"deepmet_phi", "histo_zjets_deepmet_phi", 30, phimin, phimax,
DrawConfig(xmin=phimin, xmax=phimax, xlabel='Deep MET #phi'))
sampMan.cacheDraw(
"u1", "histo_zjets_u1", u1_bins,
DrawConfig(xmin=-40.0, xmax=100, xlabel='u_{#parallel} [GeV]'))
sampMan.cacheDraw(
"u2", "histo_zjets_u2", u2_bins,
DrawConfig(xmin=-80., xmax=80., xlabel='u_{#perp} [GeV]'))
sampMan.cacheDraw("u_pt", "histo_zjets_u_pt", u_bins,
DrawConfig(xmin=0, xmax=150, xlabel='u [GeV]'))
# corrected deepmet
def DrawCorrection(postfix):
sampMan.cacheDraw(
"deepmet_pt_corr_" + postfix,
"histo_zjets_deepmet_pt_corr_" + postfix, met_pt_bins,
DrawConfig(xmin=0, xmax=200, xlabel='Deep MET Corrected [GeV]'))
sampMan.cacheDraw(
"deepmet_phi_corr_" + postfix,
"histo_zjets_deepmet_phi_corr_" + postfix, 30, phimin, phimax,
DrawConfig(xmin=phimin,
xmax=phimax,
xlabel='Deep MET Corrected #phi'))
sampMan.cacheDraw(
"u1_corr_" + postfix, "histo_zjets_u1_corr_" + postfix, u1_bins,
DrawConfig(xmin=-40.0,
xmax=100,
xlabel='u_{#parallel} Corrected [GeV]'))
sampMan.cacheDraw(
"u2_corr_" + postfix, "histo_zjets_u2_corr_" + postfix, u2_bins,
DrawConfig(xmin=-80., xmax=80.,
xlabel='u_{#perp} Corrected [GeV]'))
sampMan.cacheDraw(
"u_pt_corr_" + postfix, "histo_zjets_u_pt_corr_" + postfix, u_bins,
DrawConfig(xmin=0, xmax=150, xlabel='u Corrected [GeV]'))
DrawCorrection("central")
DrawCorrection("central_MG")
DrawCorrection("central_GKS")
DrawCorrection("mur_1_muf_0p5")
DrawCorrection("mur_1_muf_2")
DrawCorrection("mur_0p5_muf_1")
DrawCorrection("mur_2_muf_1")
DrawCorrection("mur_0p5_muf_0p5")
DrawCorrection("mur_2_muf_2")
## sys: corrected deepmet from MG
#sampMan.cacheDraw("deepmet_pt_corr_central_MG", "histo_zjets_deepmet_pt_corr_central_MG", met_pt_bins, DrawConfig(xmin=0, xmax=200, xlabel='Deep MET Corrected [GeV]'))
#sampMan.cacheDraw("u1_corr_central_MG", "histo_zjets_u1_corr_central_MG", u1_bins, DrawConfig(xmin=-40.0, xmax=100, xlabel='u_{#parallel} Corrected [GeV]'))
#sampMan.cacheDraw("u2_corr_central_MG", "histo_zjets_u2_corr_central_MG", u2_bins, DrawConfig(xmin=-80., xmax=80., xlabel='u_{#perp} Corrected [GeV]'))
#sampMan.cacheDraw("u_pt_corr_central_MG", "histo_zjets_u_pt_corr_central_MG", u_bins, DrawConfig(xmin=0, xmax=150, xlabel='u Corrected [GeV]'))
## sys: corrected deepmet from Gauss Smearing
#sampMan.cacheDraw("deepmet_pt_corr_central_GKS", "histo_zjets_deepmet_pt_corr_central_GKS", met_pt_bins, DrawConfig(xmin=0, xmax=200, xlabel='Deep MET Corrected [GeV]'))
#sampMan.cacheDraw("u1_corr_central_GKS", "histo_zjets_u1_corr_central_GKS", u1_bins, DrawConfig(xmin=-40.0, xmax=100, xlabel='u_{#parallel} Corrected [GeV]'))
#sampMan.cacheDraw("u2_corr_central_GKS", "histo_zjets_u2_corr_central_GKS", u2_bins, DrawConfig(xmin=-80., xmax=80., xlabel='u_{#perp} Corrected [GeV]'))
#sampMan.cacheDraw("u_pt_corr_central_GKS", "histo_zjets_u_pt_corr_central_GKS", u_bins, DrawConfig(xmin=0, xmax=150, xlabel='u Corrected [GeV]'))
sampMan.launchDraw()
# compare some ratio distributions for systematics
rmin = 0.7
rmax = 1.3
colors = [1, 2, 3]
linestyles = [1, 3, 3]
def compRatios(hnames, colors, linestyles, legends, outputtag):
histos_met = [
sampMan.hratios["histo_zjets_deepmet_pt_{}".format(
hname)].values()[0] for hname in hnames
]
histos_u_pt = [
sampMan.hratios["histo_zjets_u_pt_{}".format(hname)].values()[0]
for hname in hnames
]
histos_u1 = [
sampMan.hratios["histo_zjets_u1_{}".format(hname)].values()[0]
for hname in hnames
]
histos_u2 = [
sampMan.hratios["histo_zjets_u2_{}".format(hname)].values()[0]
for hname in hnames
]
if len(hnames) > 5:
legendNCols = 2
legendPos = [0.20, 0.88, 0.70, 0.74]
else:
legendNCols = 1
legendPos = [0.20, 0.88, 0.35, 0.74]
DrawHistos(histos_met,
legends,
0.,
150.,
"Deep MET Corrected [GeV]",
rmin,
rmax,
"Data / MC",
"histo_zjets_ratio_deepmet_pt_{}".format(outputtag),
dology=False,
drawashist=True,
mycolors=colors,
linestyles=linestyles,
legendPos=legendPos,
legendNCols=legendNCols)
DrawHistos(histos_u_pt,
legends,
0.,
150.,
"u Corrected [GeV]",
0.7,
1.3,
"Data / MC",
"histo_zjets_ratio_u_pt_{}".format(outputtag),
dology=False,
drawashist=True,
mycolors=colors,
linestyles=linestyles,
legendPos=legendPos,
legendNCols=legendNCols)
DrawHistos(histos_u1,
legends,
-40.0,
100.,
"u_{#parallel} Corrected [GeV]",
0.7,
1.3,
"Data / MC",
"histo_zjets_ratio_u1_{}".format(outputtag),
dology=False,
drawashist=True,
mycolors=colors,
linestyles=linestyles,
legendPos=legendPos,
legendNCols=legendNCols)
DrawHistos(histos_u2,
legends,
-80.0,
80.,
"u_{#perp} Corrected [GeV]",
0.7,
1.3,
"Data / MC",
"histo_zjets_ratio_u2_{}".format(outputtag),
dology=False,
drawashist=True,
mycolors=colors,
linestyles=linestyles,
legendPos=legendPos,
legendNCols=legendNCols)
def compMCRatios(hnames, colors, linestyles, legends, outputtag):
# compare MC with MC
histos_met = [
THStack2TH1(
sampMan.hsmcs["histo_zjets_deepmet_pt_{}".format(hname)],
"MCRatio") for hname in hnames
]
histos_u_pt = [
THStack2TH1(sampMan.hsmcs["histo_zjets_u_pt_{}".format(hname)],
"MCRatio") for hname in hnames
]
histos_u1 = [
THStack2TH1(sampMan.hsmcs["histo_zjets_u1_{}".format(hname)],
"MCRatio") for hname in hnames
]
histos_u2 = [
THStack2TH1(sampMan.hsmcs["histo_zjets_u2_{}".format(hname)],
"MCRatio") for hname in hnames
]
histos_met_base = histos_met[0].Clone(histos_met[0].GetName() +
"_Cloned")
histos_u_pt_base = histos_u_pt[0].Clone(histos_u_pt[0].GetName() +
"_Cloned")
histos_u1_base = histos_u1[0].Clone(histos_u1[0].GetName() + "_Cloned")
histos_u2_base = histos_u2[0].Clone(histos_u2[0].GetName() + "_Cloned")
for hmet, hupt, hu1, hu2 in zip(histos_met, histos_u_pt, histos_u1,
histos_u2):
hmet.Divide(histos_met_base)
hmet.SetFillColor(0)
hupt.Divide(histos_u_pt_base)
hupt.SetFillColor(0)
hu1.Divide(histos_u1_base)
hu1.SetFillColor(0)
hu2.Divide(histos_u2_base)
hu2.SetFillColor(0)
if len(hnames) > 5:
legendNCols = 2
legendPos = [0.20, 0.88, 0.70, 0.74]
else:
legendNCols = 1
legendPos = [0.20, 0.88, 0.35, 0.74]
DrawHistos(histos_met,
legends,
0.,
150.,
"Deep MET Corrected [GeV]",
rmin,
rmax,
"Ratio",
"histo_zjets_MCratio_deepmet_pt_{}".format(outputtag),
dology=False,
drawashist=True,
mycolors=colors,
linestyles=linestyles,
legendPos=legendPos,
legendNCols=legendNCols)
DrawHistos(histos_u_pt,
legends,
0.,
150.,
"u Corrected [GeV]",
0.7,
1.3,
"Ratio",
"histo_zjets_MCratio_u_pt_{}".format(outputtag),
dology=False,
drawashist=True,
mycolors=colors,
linestyles=linestyles,
legendPos=legendPos,
legendNCols=legendNCols)
DrawHistos(histos_u1,
legends,
-40.0,
100.,
"u_{#parallel} Corrected [GeV]",
0.7,
1.3,
"Ratio",
"histo_zjets_MCratio_u1_{}".format(outputtag),
dology=False,
drawashist=True,
mycolors=colors,
linestyles=linestyles,
legendPos=legendPos,
legendNCols=legendNCols)
DrawHistos(histos_u2,
legends,
-80.0,
80.,
"u_{#perp} Corrected [GeV]",
0.7,
1.3,
"Ratio",
"histo_zjets_MCratio_u2_{}".format(outputtag),
dology=False,
drawashist=True,
mycolors=colors,
linestyles=linestyles,
legendPos=legendPos,
legendNCols=legendNCols)
colors = [1, 2]
linestyles = [1, 1]
legends = ["amc@NLO", "MadGraph"]
compRatios(["corr_central", "corr_central_MG"], colors, linestyles,
legends, "MCSample")
compMCRatios(["corr_central", "corr_central_MG"], colors, linestyles,
legends, "MCSample")
legends = ["2-Gaussian Fit", "Gaussian Smoothing"]
compRatios(["corr_central", "corr_central_GKS"], colors, linestyles,
legends, "FitVSSmoothing")
compMCRatios(["corr_central", "corr_central_GKS"], colors, linestyles,
legends, "FitVSSmoothing")
legends = [
"#mu_{r}=1, #mu_{f}=1", "#mu_{r}=1, #mu_{f}=0.5",
"#mu_{r}=1, #mu_{f}=2", "#mu_{r}=0.5, #mu_{f}=1",
"#mu_{r}=2, #mu_{f}=1", "#mu_{r}=0.5, #mu_{f}=0.5",
"#mu_{r}=2, #mu_{f}=2"
]
postfixs = [
"corr_central", "corr_mur_1_muf_0p5", "corr_mur_1_muf_2",
"corr_mur_0p5_muf_1", "corr_mur_2_muf_1", "corr_mur_0p5_muf_0p5",
"corr_mur_2_muf_2"
]
colors = [1, 2, 3, 4, 5, 6, 7]
linestyles = [1, 1, 1, 1, 1, 1, 1]
compRatios(postfixs, colors, linestyles, legends, "QCDScale")
compMCRatios(postfixs, colors, linestyles, legends, "QCSScale")
doDump = False
if doDump:
print "Dump corrections into root file..."
branchList = ROOT.vector('string')()
for branchName in [
"zpt", "deepmet_pt", "u1", "u2", "u1_corr_njets_3Gauss",
"u2_corr_njets_3Gauss", "u_pt_corr_njets_3Gauss",
"deepmet_pt_corr_njets_3Gauss", "weight", "weight_WoVpt",
"vtx_n", "u1_PF", "u2_PF", "u1_PUPPI", "u2_PUPPI",
"jet_CSVLoose_n"
]:
branchList.push_back(branchName)
#TTbarSamp.rdf.Snapshot("DeepMETCorr_TTbar", "results/deepmetcorr_TTbar.root", branchList)
DYSamp.rdf.Snapshot("DeepMETCorr_DY", "results/deepmetcorr_DY.root",
branchList)
branchList = ROOT.vector('string')()
for branchName in [
"zpt", "deepmet_pt", "u1", "u2", "weight", "weight_WoVpt",
"vtx_n", "u1_PF", "u2_PF", "u1_PUPPI", "u2_PUPPI",
"jet_CSVLoose_n"
]:
branchList.push_back(branchName)
DataSamp.rdf.Snapshot("DeepMETCorr_Data",
"results/deepmetcorr_Data.root", branchList)
print "Program end..."
raw_input()
return