exp_draw_option = 'l'
if args.noobs and args.showpoints:
exp_draw_option += 'p'
exp.Draw(exp_draw_option)
if not args.noobs:
obs = limitplot.build_obs_line(limit_data, key)
obs_draw_option = 'l'
if args.showpoints:
obs_draw_option += 'p'
obs.Draw(obs_draw_option)
cms_label = styling.cms_preliminary(
args.lumi,
is_preliminary=args.preliminary,
lumi_on_top = True,
)
# Add legend
legend_args = [ float(x) for x in args.legendpos.split(',') ] + ["", "NDC"]
legend = ROOT.TLegend(*legend_args)
legend.SetBorderSize(0)
legend.SetFillStyle(0)
if not args.noobs:
legend.AddEntry(obs,"Observed", 'lp')
legend.AddEntry(exp, "Expected", 'l')
legend.AddEntry(onesig, "#pm 1 #sigma", 'f')
legend.AddEntry(twosig, "#pm 2 #sigma", 'f')
legend.Draw()
)
data = plotter.get_histogram(
fr_info['pd'],
'/%s/final/Ntuple:%s' % (fr_info['ntuple'], name),
show_overflows = True,
rebin = rebin,
)
stack.Draw()
stack.GetXaxis().SetTitle(xtitle)
data.Draw("pe, same")
legend.Draw()
stack.SetMaximum(max(stack.GetMaximum(), data.GetMaximum())*1.5)
stack.GetHistogram().SetTitle(
xtitle + ' in ' + fr_info['evtType'] + ' events')
cms_label = styling.cms_preliminary(int_lumi)
saveplot(fr_type + '_' + name)
# Make efficiency curve
data_num = plotter.get_histogram(
fr_info['pd'],
'/%s/final/Ntuple:%s' % (
fr_info['ntuple'], fr_type + 'Num' + fr_info['varname']),
show_overflows = True,
rebin = fr_info['rebin'],
)
log.info("Data numerator has %i entries", data_num.Integral())
data_denom = plotter.get_histogram(
fr_info['pd'],
'/%s/final/Ntuple:%s' % (
label.SetBorderSize(1)
label.SetFillColor(ROOT.EColor.kWhite)
label.AddText(object_info['label'])
label.Draw()
legend = ROOT.TLegend(*legend_pos)
legend.SetBorderSize(1)
legend.SetFillColor(ROOT.EColor.kWhite)
legend.AddEntry(curves['data'], object_info['comb_label'] + " events", "p")
legend.AddEntry(curves['nom'], object_info['comb_label'] + " fit", "l")
legend.AddEntry(curves['band'], "1#sigma fit error", "f")
legend.AddEntry(curves['scale'], "#pm %i%%" % scale_err, "l")
legend.Draw()
canvas.Update()
canvas.SetLogy(True)
cms_label = styling.cms_preliminary(4684)
canvas.SaveAs("plots/combineFakeRates/%s_combined_eff_roofit.pdf" % object)
############################################################################
### Compare all regions to fitted fake rate ###############################
############################################################################
for type, type_info in scenarios.iteritems():
roo_frame = jet_pt.frame(ROOT.RooFit.Title("Efficiency"))
roo_frame.SetAxisRange(object_info['min_x'], 100)
roo_data = ROOT.RooDataHist(
"data", "data",
ROOT.RooArgList(jet_pt), ROOT.RooFit.Index(roo_cut),
ROOT.RooFit.Import("accept", type_info['data_pass']),
ROOT.RooFit.Import("reject", type_info['data_fail']),
exp_draw_option = 'l'
if args.noobs and args.showpoints:
exp_draw_option += 'p'
exp.Draw(exp_draw_option)
if not args.noobs:
obs = limitplot.build_obs_line(limit_data, key)
obs_draw_option = 'l'
if args.showpoints:
obs_draw_option += 'p'
obs.Draw(obs_draw_option)
cms_label = styling.cms_preliminary(
args.lumi,
is_preliminary=args.preliminary,
lumi_on_top=True,
)
# Add legend
legend_args = [float(x) for x in args.legendpos.split(',')] + ["", "NDC"]
# Translate the legend in X,Y, if desired.
nudge = [float(x) for x in args.legendnudge.split(',')]
legend_args[0] += nudge[0]
legend_args[2] += nudge[0]
legend_args[1] += nudge[1]
legend_args[3] += nudge[1]
legend = ROOT.TLegend(*legend_args)
legend.SetBorderSize(1)