def el_fakerate():
# Glob the file lists
mcs = [
output_dirpath + "/wj_ht.root",
output_dirpath + "/tt_1l.root",
]
num = "ElClosureTight__elptcorretarolledcoarse"
den = "ElClosureLoose__elptcorretarolledcoarse"
h_num = ru.get_summed_histogram(mcs, num)
h_den = ru.get_summed_histogram(mcs, den)
u.move_in_overflows(h_num)
u.move_in_overflows(h_den)
h_num.Divide(h_den)
qcds = [
output_dirpath + "/qcd_em.root",
output_dirpath + "/qcd_bc.root",
]
qcd_num = "OneElTightMR__elptcorretarolledcoarse"
qcd_den = "OneElMR__elptcorretarolledcoarse"
h_qcd_num = ru.get_summed_histogram(qcds, qcd_num)
h_qcd_den = ru.get_summed_histogram(qcds, qcd_den)
u.move_in_overflows(h_qcd_num)
u.move_in_overflows(h_qcd_den)
h_qcd_num.Divide(h_qcd_den)
h_qcd_num.SetName("QCD(e)")
# Color settings
colors = [
2005,
2001,
]
# Options
alloptions = {
"ratio_range": [0.0, 2.0],
"nbins": 180,
"autobin": False,
"legend_scalex": 1.8,
"legend_scaley": 1.1,
"output_name": "plots/fakeratemc/{}.pdf".format(num + "__" + den),
"bkg_sort_method": "unsorted",
"no_ratio": False,
"print_yield": True,
"yield_prec": 3,
"draw_points": True,
"lumi_value": 41.3,
"legend_datalabel": "W+t#bar{t}"
}
# Plot them
p.plot_hist(bgs=[h_qcd_num],
data=h_num,
colors=colors,
syst=None,
options=alloptions)
def get_fakerate_histograms(num, den, ps=0, sf=0, sfden=0):
h_num, _, _, h_num_qcd_mu, h_num_qcd_el, h_num_qcd_bc, _, _, _, _ = plot(
num, ps, sf)
if sfden == 0:
h_den, _, _, h_den_qcd_mu, h_den_qcd_el, h_den_qcd_bc, _, _, _, _ = plot(
den, ps, sf)
else:
h_den, _, _, h_den_qcd_mu, h_den_qcd_el, h_den_qcd_bc, _, _, _, _ = plot(
den, ps, sfden)
# Creating a summed histogram (EM + HF sourced e-fake) where the ratio will be only of importance as we will divide the histograms to get fake rate
h_num_qcd_esum = h_num_qcd_el.Clone("QCD(e)")
h_den_qcd_esum = h_den_qcd_el.Clone("QCD(e)")
h_num_qcd_esum.Add(h_num_qcd_bc)
h_den_qcd_esum.Add(h_den_qcd_bc)
# Data
u.move_in_overflows(h_num)
u.move_in_overflows(h_den)
h_num.Divide(h_den)
# Mu fake rate
u.move_in_overflows(h_num_qcd_mu)
u.move_in_overflows(h_den_qcd_mu)
h_num_qcd_mu.Divide(h_den_qcd_mu)
# EM fake rate
u.move_in_overflows(h_num_qcd_el)
u.move_in_overflows(h_den_qcd_el)
h_num_qcd_el.Divide(h_den_qcd_el)
# HF fake rate
u.move_in_overflows(h_num_qcd_bc)
u.move_in_overflows(h_den_qcd_bc)
h_num_qcd_bc.Divide(h_den_qcd_bc)
# Total summed electron fake rate
u.move_in_overflows(h_num_qcd_esum)
u.move_in_overflows(h_den_qcd_esum)
h_num_qcd_esum.Divide(h_den_qcd_esum)
# Set any negative fake rate to 0 or some tiny number
def set_nonzero(h):
for i in xrange(1, h.GetNbinsX() + 1):
bc = h.GetBinContent(i)
if bc < 0:
h.SetBinContent(i, 1e-6)
set_nonzero(h_num)
set_nonzero(h_num_qcd_mu)
set_nonzero(h_num_qcd_esum)
set_nonzero(h_num_qcd_el)
set_nonzero(h_num_qcd_bc)
return h_num, h_num_qcd_mu, h_num_qcd_esum, h_num_qcd_el, h_num_qcd_bc
def get_fakerate_histograms(num, den, ps=0, sf=0):
h_num, _, _, h_num_qcd_mu, h_num_qcd_el, h_num_qcd_bc = plot(
num, ps, sf)
h_den, _, _, h_den_qcd_mu, h_den_qcd_el, h_den_qcd_bc = plot(
den, ps, sf)
# Creating a summed histogram (EM + HF sourced e-fake) where the ratio will be only of importance as we will divide the histograms to get fake rate
h_num_qcd_esum = h_num_qcd_el.Clone("QCD(e)")
h_den_qcd_esum = h_den_qcd_el.Clone("QCD(e)")
h_num_qcd_esum.Add(h_num_qcd_bc)
h_den_qcd_esum.Add(h_den_qcd_bc)
# Data
u.move_in_overflows(h_num)
u.move_in_overflows(h_den)
h_num.Divide(h_den)
# Mu fake rate
u.move_in_overflows(h_num_qcd_mu)
u.move_in_overflows(h_den_qcd_mu)
h_num_qcd_mu.Divide(h_den_qcd_mu)
# EM fake rate
u.move_in_overflows(h_num_qcd_el)
u.move_in_overflows(h_den_qcd_el)
h_num_qcd_el.Divide(h_den_qcd_el)
# HF fake rate
u.move_in_overflows(h_num_qcd_bc)
u.move_in_overflows(h_den_qcd_bc)
h_num_qcd_bc.Divide(h_den_qcd_bc)
# Total summed electron fake rate
u.move_in_overflows(h_num_qcd_esum)
u.move_in_overflows(h_den_qcd_esum)
h_num_qcd_esum.Divide(h_den_qcd_esum)
return h_num, h_num_qcd_mu, h_num_qcd_esum, h_num_qcd_el, h_num_qcd_bc