def do_pf_fraction_plot(hist_map, pt_bins, output_filename):
"""Plot PF particle type fractioin for matches, binned by GenParticle pT"""
entries = []
for pt_low, pt_high, mark in zip(pt_bins[:-1], pt_bins[1:],
cu.Marker().cycle()):
values = {}
for pf_ind, (pf_name, hist) in hist_map.items():
ax = hist.GetXaxis()
binx1 = ax.FindBin(pt_low)
binx2 = ax.FindBin(pt_high) - 1
if pt_high == ax.GetBinUpEdge(ax.GetLast()):
binx2 = ax.GetLast()
biny1 = 1
biny2 = hist.GetNbinsY()
binz1 = 1
binz2 = hist.GetNbinsZ()
values[pf_ind] = hist.Integral(
binx1, binx2, biny1, biny2, binz1,
binz2) # integral includes the last bin
sum_values = sum(values.values())
fracs = {k: (v / sum_values) for k, v in values.items()}
h = ROOT.TH1D("h_pt_bin_%gto%g" % (pt_low, pt_high), "", len(values),
0, len(values))
ax = h.GetXaxis()
for ind, k in enumerate(sorted(fracs.keys()), 1):
h.SetBinContent(ind, fracs[k])
h.SetBinError(ind, sqrt(values[k]) / sum_values)
ax.SetBinLabel(ind, hist_map[k][0])
c = Contribution(h,
label='%g < GenParticle p_{T} < %g GeV' %
(pt_low, pt_high),
line_width=1,
marker_size=0.75,
marker_style=mark,
normalise_hist=False)
entries.append(c)
ROOT.gStyle.SetPalette(55)
plot = Plot(entries,
'hist',
xtitle='PF particle type',
ytitle='Fraction matched as type',
ylim=(1E-3, 2),
has_data=False)
plot.default_canvas_size = (800, 600)
plot.plot("NOSTACK PMC PLC HISTE")
plot.set_logy(do_more_labels=False)
plot.save(output_filename)
ROOT.gStyle.SetPalette(ROOT.kViridis)
def do_comparison_plots(workdir_label_pairs, output_dir):
dirnames = [w[0] for w in workdir_label_pairs]
# templates, we'll change the filename/dir as per instance
total_len = len(workdir_label_pairs)
mark = cu.Marker()
sources = [{
"root_dir": wd,
'label': label,
"style": {
'line_style': 1,
'line_color': cu.get_colour_seq(ind, total_len),
'marker_color': cu.get_colour_seq(ind, total_len),
'marker_style': m,
'marker_size': 0.75,
}
} for ind, ((wd, label), m) in enumerate(
zip(workdir_label_pairs, mark.cycle(cycle_filling=True)))]
# print(sources)
# COMPARE NOMINAL QCD
if exists_in_all(qgc.QCD_FILENAME, dirnames):
# qgp.do_all_exclusive_plots_comparison(sources,
# var_list=qgc.COMMON_VARS,
# pt_bins=qgc.PT_BINS,
# qcd_filename=qgc.QCD_FILENAME,
# dj_cen_dirname="Dijet_QG_central_tighter",
# dj_fwd_dirname=None,
# zpj_dirname=None,
# plot_dir=os.path.join(output_dir, "plots_qcd_compare_dijet_central"),
# subplot_type="ratio", # will use the 1st entry by default
# subplot_title="* / %s" % (sources[0]['label']),
# do_flav_tagged=False,
# has_data=False)
# qgp.do_all_exclusive_plots_comparison(sources,
# var_list=qgc.COMMON_VARS,
# pt_bins=qgc.PT_BINS,
# qcd_filename=qgc.QCD_FILENAME,
# dj_cen_dirname=None,
# dj_fwd_dirname="Dijet_QG_forward_tighter",
# zpj_dirname=None,
# plot_dir=os.path.join(output_dir, "plots_qcd_compare_dijet_forward"),
# subplot_type="ratio", # will use the 1st entry by default
# subplot_title="* / %s" % (sources[0]['label']),
# do_flav_tagged=False,
# has_data=False)
# do both dijet jets together
# add gen level
gen_qcd_sources = [deepcopy(sources[0])] # only 1st one for now
for gd in gen_qcd_sources:
gd.update({
'dj_fwd_dirname': 'Dijet_QG_gen',
'label': gd['label'] + ' [Gen]'
})
style_dict = gd['style']
style_dict.update({'line_style': 2})
style_dict.update({'line_color': style_dict['line_color'] + 5})
style_dict.update({'marker_color': style_dict['marker_color'] + 5})
style_dict.update({'marker_style': style_dict['marker_style'] + 1})
qgp.do_all_exclusive_plots_comparison(
sources + gen_qcd_sources,
var_list=qgc.COMMON_VARS,
pt_bins=qgc.PT_BINS,
qcd_filename=qgc.QCD_FILENAME,
dj_cen_dirname=None,
dj_fwd_dirname="Dijet_QG_tighter",
zpj_dirname=None,
plot_dir=os.path.join(output_dir, "plots_qcd_compare_dijet"),
subplot_type="ratio", # will use the 1st entry by default
subplot_title="* / %s" % (sources[0]['label']),
do_flav_tagged=False,
has_data=False,
title=qgc.Dijet_LABEL,
show_region_labels=False)
# COMPARE NOMINAL DY
if exists_in_all(qgc.DY_FILENAME, dirnames):
qgp.do_all_exclusive_plots_comparison(
sources,
var_list=qgc.COMMON_VARS,
pt_bins=qgc.PT_BINS,
qcd_filename=qgc.DY_FILENAME,
dj_cen_dirname=None,
dj_fwd_dirname=None,
zpj_dirname="ZPlusJets_QG",
plot_dir=os.path.join(output_dir, "plots_dy_compare"),
subplot_type="ratio", # will use the 1st entry by default
subplot_title="* / %s" % (sources[0]['label']),
do_flav_tagged=False,
has_data=False,
title=qgc.ZpJ_LABEL,
show_region_labels=False)
# COMPARE JETHT+ZEROBIAS
if exists_in_all(qgc.JETHT_ZB_FILENAME, dirnames):
qgp.do_all_exclusive_plots_comparison(
sources,
var_list=qgc.COMMON_VARS,
pt_bins=qgc.PT_BINS,
qcd_filename=qgc.JETHT_ZB_FILENAME,
dj_cen_dirname="Dijet_QG_central_tighter",
dj_fwd_dirname=None,
zpj_dirname=None,
plot_dir=os.path.join(output_dir,
"plots_jetht_zb_compare_dijet_central"),
subplot_type="ratio", # will use the 1st entry by default
subplot_title="* / %s" % (sources[0]['label']),
do_flav_tagged=False,
has_data=True)
qgp.do_all_exclusive_plots_comparison(
sources,
var_list=qgc.COMMON_VARS,
pt_bins=qgc.PT_BINS,
qcd_filename=qgc.JETHT_ZB_FILENAME,
dj_cen_dirname=None,
dj_fwd_dirname="Dijet_QG_forward_tighter",
zpj_dirname=None,
plot_dir=os.path.join(output_dir,
"plots_jetht_zb_compare_dijet_forward"),
subplot_type="ratio", # will use the 1st entry by default
subplot_title="* / %s" % (sources[0]['label']),
do_flav_tagged=False,
has_data=True)
# COMPARE SINGLEMU
# COMPARE HERWIG++ QCD
if exists_in_all(qgc.QCD_HERWIG_FILENAME, dirnames):
qgp.do_all_exclusive_plots_comparison(
sources,
var_list=qgc.COMMON_VARS,
pt_bins=qgc.PT_BINS,
qcd_filename=qgc.QCD_HERWIG_FILENAME,
dj_cen_dirname="Dijet_QG_central_tighter",
dj_fwd_dirname=None,
zpj_dirname=None,
plot_dir=os.path.join(output_dir,
"plots_qcd_herwig_compare_dijet_central"),
subplot_type="ratio", # will use the 1st entry by default
subplot_title="* / %s" % (sources[0]['label']),
subplot_limits=[0.9, 1.1],
do_flav_tagged=False,
has_data=False)
qgp.do_all_exclusive_plots_comparison(
sources,
var_list=qgc.COMMON_VARS,
pt_bins=qgc.PT_BINS,
qcd_filename=qgc.QCD_HERWIG_FILENAME,
dj_cen_dirname=None,
dj_fwd_dirname="Dijet_QG_forward_tighter",
zpj_dirname=None,
plot_dir=os.path.join(output_dir,
"plots_qcd_herwig_compare_dijet_forward"),
subplot_type="ratio", # will use the 1st entry by default
subplot_title="* / %s" % (sources[0]['label']),
subplot_limits=[0.9, 1.1],
do_flav_tagged=False,
has_data=False)
def do_comparison_plots(workdir_label_pairs, output_dir):
dirnames = [w[0] for w in workdir_label_pairs]
# templates, we'll change the filename/dir as per instance
total_len = len(workdir_label_pairs)
mark = cu.Marker()
sources = [
{
# "root_dir": wd,
'label': label,
"style": {
'line_style': 1,
'line_color': cu.get_colour_seq(ind, total_len),
'marker_color': cu.get_colour_seq(ind, total_len),
'marker_style': m,
'marker_size': 0.75,
}
}
for ind, ((wd, label), m) in enumerate(zip(workdir_label_pairs, mark.cycle(cycle_filling=True)))
]
jet_config_str = qgc.extract_jet_config(dirnames[0])
if len(dirnames) >1 and qgc.extract_jet_config(dirnames[1]) != jet_config_str:
print("Conflicting jet config str, not adding")
jet_config_str = None
# COMPARE NOMINAL QCD
if exists_in_all(qgc.QCD_FILENAME, dirnames):
print("Found", qgc.QCD_FILENAME, "in all dirs")
root_files = [cu.open_root_file(os.path.join(d, qgc.QCD_FILENAME)) for d in dirnames]
directories = [cu.get_from_tfile(rf, "Dijet_tighter") for rf in root_files]
this_sources = deepcopy(sources)
for s in this_sources:
s['label'] = "QCD [MG+PY8] [%s]" % s['label']
do_all_1D_projection_plots_in_dir(directories=directories,
components_styles_dicts=this_sources,
output_dir=os.path.join(output_dir, "plots_qcd_compare_dijet_tighter_kinematics_normalised"),
jet_config_str=jet_config_str,
normalise_hists=True,
bin_by='ave')
directories = [cu.get_from_tfile(rf, "Dijet_eta_ordered") for rf in root_files]
do_all_1D_projection_plots_in_dir(directories=directories,
components_styles_dicts=this_sources,
output_dir=os.path.join(output_dir, "plots_qcd_compare_dijet_eta_ordered_kinematics_normalised"),
jet_config_str=jet_config_str,
normalise_hists=True,
bin_by='ave')
# COMPARE NOMINAL DY
if exists_in_all(qgc.DY_FILENAME, dirnames):
root_files = [cu.open_root_file(os.path.join(d, qgc.DY_FILENAME)) for d in dirnames]
directories = [cu.get_from_tfile(rf, "ZPlusJets") for rf in root_files]
this_sources = deepcopy(sources)
for s in this_sources:
s['label'] = "Z+Jet [MG+PY8] [%s]" % s['label']
do_all_1D_projection_plots_in_dir(directories=directories,
components_styles_dicts=this_sources,
output_dir=os.path.join(output_dir, "plots_dy_compare_kinematics_absolute"),
jet_config_str=jet_config_str,
normalise_hists=False,
bin_by='Z')
do_all_1D_projection_plots_in_dir(directories=directories,
components_styles_dicts=this_sources,
output_dir=os.path.join(output_dir, "plots_dy_compare_kinematics_normalised"),
jet_config_str=jet_config_str,
normalise_hists=True,
bin_by='Z')
# COMPARE JETHT+ZEROBIAS
if exists_in_all(qgc.JETHT_ZB_FILENAME, dirnames):
print("Found", qgc.JETHT_ZB_FILENAME, "in all dirs")
root_files = [cu.open_root_file(os.path.join(d, qgc.JETHT_ZB_FILENAME)) for d in dirnames]
directories = [cu.get_from_tfile(rf, "Dijet_tighter") for rf in root_files]
this_sources = deepcopy(sources)
for s in this_sources:
s['label'] = "Data [%s]" % s['label']
directories = [cu.get_from_tfile(rf, "Dijet_Presel") for rf in root_files]
do_all_1D_projection_plots_in_dir(directories=directories,
components_styles_dicts=this_sources,
output_dir=os.path.join(output_dir, "plots_jetht_zb_compare_dijet_presel_kinematics_normalised"),
jet_config_str=jet_config_str,
normalise_hists=False,
bin_by='ave')
directories = [cu.get_from_tfile(rf, "Dijet_tighter") for rf in root_files]
do_all_1D_projection_plots_in_dir(directories=directories,
components_styles_dicts=this_sources,
output_dir=os.path.join(output_dir, "plots_jetht_zb_compare_dijet_tighter_kinematics_normalised"),
jet_config_str=jet_config_str,
normalise_hists=True,
bin_by='ave')
do_all_1D_projection_plots_in_dir(directories=directories,
components_styles_dicts=this_sources,
output_dir=os.path.join(output_dir, "plots_jetht_zb_compare_dijet_tighter_kinematics_abs"),
jet_config_str=jet_config_str,
normalise_hists=False,
bin_by='ave')
# COMPARE SINGLEMU
# COMPARE HERWIG++ QCD
if exists_in_all(qgc.QCD_HERWIG_FILENAME, dirnames):
root_files = [cu.open_root_file(os.path.join(d, qgc.QCD_HERWIG_FILENAME)) for d in dirnames]
directories = [cu.get_from_tfile(rf, "Dijet_tighter") for rf in root_files]
this_sources = deepcopy(sources)
for s in this_sources:
s['label'] = "QCD [H++] [%s]" % s['label']
# do_all_1D_projection_plots_in_dir(directories=directories,
# components_styles_dicts=this_sources,
# output_dir=os.path.join(output_dir, "plots_qcd_hpp_compare_dijet_tighter_kinematics_normalised"),
# jet_config_str=jet_config_str,
# normalise_hists=True,
# bin_by='ave')
# directories = [cu.get_from_tfile(rf, "Dijet_eta_ordered") for rf in root_files]
# do_all_1D_projection_plots_in_dir(directories=directories,
# components_styles_dicts=this_sources,
# output_dir=os.path.join(output_dir, "plots_qcd_hpp_compare_dijet_eta_ordered_kinematics_normalised"),
# jet_config_str=jet_config_str,
# normalise_hists=True,
# bin_by='ave')
do_all_1D_projection_plots_in_dir(directories=directories,
components_styles_dicts=this_sources,
output_dir=os.path.join(output_dir, "plots_qcd_hpp_compare_dijet_tighter_kinematics_absolute"),
jet_config_str=jet_config_str,
normalise_hists=False,
bin_by='ave')
directories = [cu.get_from_tfile(rf, "Dijet_eta_ordered") for rf in root_files]
do_all_1D_projection_plots_in_dir(directories=directories,
components_styles_dicts=this_sources,
output_dir=os.path.join(output_dir, "plots_qcd_hpp_compare_dijet_eta_ordered_kinematics_absolute"),
jet_config_str=jet_config_str,
normalise_hists=False,
bin_by='ave')
# COMPARE HERWIG++ DY
if exists_in_all(qgc.DY_HERWIG_FILENAME, dirnames):
root_files = [cu.open_root_file(os.path.join(d, qgc.DY_HERWIG_FILENAME)) for d in dirnames]
directories = [cu.get_from_tfile(rf, "ZPlusJets") for rf in root_files]
this_sources = deepcopy(sources)
for s in this_sources:
s['label'] = "Z+Jet [H++] [%s]" % s['label']
do_all_1D_projection_plots_in_dir(directories=directories,
components_styles_dicts=this_sources,
output_dir=os.path.join(output_dir, "plots_dy_hpp_compare_kinematics_absolute"),
jet_config_str=jet_config_str,
normalise_hists=False,
bin_by='Z')
do_all_1D_projection_plots_in_dir(directories=directories,
components_styles_dicts=this_sources,
output_dir=os.path.join(output_dir, "plots_dy_hpp_compare_kinematics_normalised"),
jet_config_str=jet_config_str,
normalise_hists=True,
bin_by='Z')
def do_plots(root_dir):
# QG variable plots
pt_bins = qgc.PT_BINS[:]
var_list = qgc.COMMON_VARS
radius, pus = cu.get_jet_config_from_dirname(root_dir)
jet_str = "AK%s" % (radius.upper())
dy_tfile, qcd_tfile = None, None
if os.path.isfile(os.path.join(root_dir, qgc.DY_FILENAME)):
dy_tfile = cu.TFileCacher(os.path.join(root_dir, qgc.DY_FILENAME))
if os.path.isfile(os.path.join(root_dir, qgc.QCD_FILENAME)):
qcd_tfile = cu.TFileCacher(os.path.join(root_dir, qgc.QCD_FILENAME))
for gr_append in ["", "_groomed"]:
if gr_append == "_groomed":
print("Doing groomed plots...")
else:
print("Doing ungroomed plots...")
# GEnJets matched to recojet, reco selection
zpj_dirname = "ZPlusJets_QG%s" % (gr_append)
dj_cen_dirname = "Dijet_QG_central_tighter%s" % (gr_append)
dj_fwd_dirname = "Dijet_QG_forward_tighter%s" % (gr_append)
# Gen Jets from gen selection
zpj_dirname = "ZPlusJets_QG_gen%s" % (gr_append)
dj_cen_dirname = "Dijet_QG_gen_central%s" % (gr_append)
dj_fwd_dirname = "Dijet_QG_gen_forward%s" % (gr_append)
for ang in var_list[:]:
print("...Doing", ang.name)
var_template = "{prefix}%s_vs_pt" % (ang.var
) # {prefix} is for flavour
for pt_ind, (start_val, end_val) in enumerate(pt_bins):
zpj_entries = []
dijet_cen_entries = []
dijet_fwd_entries = []
# Get all plots
lw = 2
msize = 1.1
mc_msize = 1E-3 # small enough to not be seen but not 0 - otherwise the horizontal lines on error bars don't get drawn
mc_msize = msize # small enough to not be seen but not 0 - otherwise the horizontal lines on error bars don't get drawn
flavours_dicts = [
{
"prefix": "q",
"label": "u/d/s"
},
{
"prefix": "g",
"label": "g"
},
{
"prefix": "bc",
"label": "b/c"
},
]
if dy_tfile:
# Z+JETS REGION
marker = cu.Marker(qgc.DY_MARKER)
for flav_dict, color, mark in zip(flavours_dicts,
qgc.DY_COLOURS,
marker.cycle()):
h2d_dyj_mc = dy_tfile.get(
"%s/%s" %
(zpj_dirname, var_template.format(**flav_dict)))
dy_kwargs_mc = dict(line_color=color,
line_width=lw,
fill_color=color,
marker_color=color,
marker_style=mark,
marker_size=mc_msize,
label="%s flavour" %
(flav_dict['label']),
subplot=None)
zpj_entries.append(
(qgp.get_projection_plot(h2d_dyj_mc, start_val,
end_val), dy_kwargs_mc))
if qcd_tfile:
# DIJET CENTRAL REGION
marker = cu.Marker(qgc.QCD_MARKER)
for flav_dict, color, mark in zip(flavours_dicts,
qgc.QCD_COLOURS,
marker.cycle()):
h2d_qcd_cen_mc = qcd_tfile.get(
"%s/%s" %
(dj_cen_dirname, var_template.format(**flav_dict)))
qcd_cen_kwargs_mc = dict(line_color=color,
line_width=lw,
fill_color=color,
marker_color=color,
marker_style=mark,
marker_size=mc_msize,
label="%s flavour" %
(flav_dict['label']),
subplot=None)
dijet_mgpy_hist = qgp.get_projection_plot(
h2d_qcd_cen_mc, start_val, end_val)
dijet_cen_entries.append(
(dijet_mgpy_hist, qcd_cen_kwargs_mc))
# DIJET FORWARD REGION
marker = cu.Marker(qgc.QCD_MARKER)
for flav_dict, color, mark in zip(flavours_dicts,
qgc.QCD_COLOURS,
marker.cycle()):
h2d_qcd_fwd_mc = qcd_tfile.get(
"%s/%s" %
(dj_fwd_dirname, var_template.format(**flav_dict)))
qcd_fwd_kwargs_mc = dict(line_color=color,
line_width=lw,
fill_color=color,
marker_color=color,
marker_style=mark,
marker_size=mc_msize,
label="%s flavour" %
(flav_dict['label']),
subplot=None)
dijet_mgpy_hist = qgp.get_projection_plot(
h2d_qcd_fwd_mc, start_val, end_val)
dijet_fwd_entries.append(
(dijet_mgpy_hist, qcd_fwd_kwargs_mc))
#################
# SETUP PLOTTING
#################
rebin = 2
v_lower = var_template.lower()
if "multiplicity" in v_lower:
rebin = 1
# elif "flavour" in v_lower or "thrust" in v_lower:
# rebin = 1
# elif 'ptd' in v_lower:
# rebin = 4
# elif 'lha_charged' in v_lower:
# rebin = 4
# rebin = 1
xlim = None
if "width" in v_lower or "ptd" in v_lower:
xlim = (0, 1)
elif "thrust" in v_lower:
xlim = (0, 0.5)
# elif "multiplicity" in v_lower and "ak4" in root_dir.lower():
# if end_val <= 150:
# xlim = (0, 50)
# else:
# xlim = (0, 80)
auto_xlim = False
if "multiplicity" in v_lower or "thrust" in v_lower:
auto_xlim = True
ylim = [0, None]
if "flavour" in v_lower:
ylim = (0, 1)
# elif "lha" in v_lower:
# ylim = (0, 5)
plot_dir = os.path.join(
root_dir,
"plots_gen_lambda_flav_comparison%s" % (gr_append))
subplot_title = "Simulation / Data"
subplot_limits = (0, 2)
xlabel = ang.name + " (" + ang.lambda_str + ")"
if gr_append is not "":
xlabel = "Groomed " + ang.name + " (" + ang.lambda_str + ")"
def _title(region_str, start_val, end_val):
pt_var_str = "p_{T}^{jet}"
s = (("{jet_algo}\n"
"{region_label}\n"
"{mc_sample}\n"
"{bin_edge_low:g} < {pt_str} < {bin_edge_high:g} GeV"
).format(jet_algo=jet_str,
region_label=region_str,
mc_sample="MG5+Pythia8",
pt_str=pt_var_str,
bin_edge_low=start_val,
bin_edge_high=end_val))
return s
has_data = False
draw_opt = "NOSTACK HIST E1"
# dj central only
# dont' try to do multiple signal regions per plot, it looks rubbish
if len(dijet_cen_entries) > 0:
qgp.do_comparison_plot(
dijet_cen_entries,
"%s/ptBinned/%s_pt%dto%d_dijet_central.%s" %
(plot_dir, ang.var, start_val, end_val, OUTPUT_FMT),
rebin=rebin,
draw_opt=draw_opt,
title=_title(qgc.Dijet_CEN_LABEL, start_val, end_val),
xtitle=xlabel,
xlim='auto' if auto_xlim else
xlim, # don't use calc_auto_xlim, since do_comparison_plot will rebin it anyway
ylim=ylim,
data_first=has_data,
mean_rel_error=0.4,
subplot_type=None,
lumi=cu.get_lumi_str(
do_dijet=False,
do_zpj=True)) # full lumi as just MC
# dj forward only
if len(dijet_fwd_entries) > 0:
qgp.do_comparison_plot(
dijet_fwd_entries,
"%s/ptBinned/%s_pt%dto%d_dijet_forward.%s" %
(plot_dir, ang.var, start_val, end_val, OUTPUT_FMT),
rebin=rebin,
draw_opt=draw_opt,
title=_title(qgc.Dijet_FWD_LABEL, start_val, end_val),
xtitle=xlabel,
xlim='auto' if auto_xlim else xlim,
ylim=ylim,
data_first=has_data,
mean_rel_error=0.4,
subplot_type=None,
lumi=cu.get_lumi_str(
do_dijet=False,
do_zpj=True)) # full lumi as just MC
# zpj only
if len(zpj_entries) > 0:
if start_val > 149:
# rebin *= 2
rebin += 1
# find nearest divisor
while (zpj_entries[0][0].GetNbinsX() % rebin != 0):
rebin += 1
if "multiplicity" in v_lower:
if start_val > 300:
rebin += 1
# find nearest divisor
while (zpj_entries[0][0].GetNbinsX() % rebin != 0):
rebin += 1
qgp.do_comparison_plot(
zpj_entries,
"%s/ptBinned/%s_pt%dto%d_zpj.%s" %
(plot_dir, ang.var, start_val, end_val, OUTPUT_FMT),
rebin=rebin,
draw_opt=draw_opt,
title=_title(qgc.ZpJ_LABEL, start_val, end_val),
xtitle=xlabel,
xlim=qgp.calc_auto_xlim([d[0] for d in zpj_entries])
if auto_xlim else xlim,
ylim=ylim,
data_first=has_data,
mean_rel_error=0.4,
subplot_type=None,
lumi=cu.get_lumi_str(do_dijet=False, do_zpj=True))
def do_pileup_plot(input_dir, trigger_names, output_filename):
# get histograms
hists = [
cu.grab_obj_from_file(
os.path.join(input_dir, 'MyDataPileupHistogram_%s.root' % t),
'pileup') for t in trigger_names
]
h_up = cu.grab_obj_from_file(
os.path.join(input_dir, 'MyDataPileupHistogram_PFJet500_72383.root'),
'pileup')
h_down = cu.grab_obj_from_file(
os.path.join(input_dir, 'MyDataPileupHistogram_PFJet500_66017.root'),
'pileup')
h_down3 = cu.grab_obj_from_file(
os.path.join(input_dir, 'MyDataPileupHistogram_PFJet500_59650.root'),
'pileup')
ratio_up = h_up.Clone()
ratio_up.Divide(hists[-1])
ratio_down = h_down.Clone()
ratio_down.Divide(hists[-1])
# hists.append(h_up)
# hists.append(h_down)
# trigger_names.append('72.383')
# trigger_names.append('66.017')
# Create contributions
mark = cu.Marker()
n_hists = len(hists)
conts = [
Contribution(h,
label=t,
line_width=2,
line_color=cu.get_colour_seq(ind, n_hists),
marker_color=cu.get_colour_seq(ind, n_hists),
marker_style=m,
normalise_hist=True)
for ind, (h, t, m) in enumerate(
zip(hists, trigger_names, mark.cycle(cycle_filling=True)))
]
conts.insert(
-1,
Contribution(
h_up,
label='72.383 (+4.6%)',
line_width=2,
line_color=ROOT.kRed,
marker_color=ROOT.kRed,
normalise_hist=True,
))
conts.insert(
-1,
Contribution(
h_down,
label='66.017 (-4.6%)',
line_width=2,
line_color=ROOT.kMagenta,
marker_color=ROOT.kMagenta,
normalise_hist=True,
))
conts.insert(
-1,
Contribution(
h_down3,
label='59.650 (-13.8%)',
line_width=2,
line_style=1,
line_color=ROOT.kMagenta + 3,
marker_color=ROOT.kMagenta + 3,
normalise_hist=True,
))
print([h.Integral() for h in hists])
plot = Plot(
conts,
what='hist',
xtitle='Pileup',
lumi=cu.get_lumi_str(do_dijet=True, do_zpj=True),
subplot_type='ratio',
subplot=conts[-1],
)
plot.subplot_maximum_ceil = 4.5
plot.plot("NOSTACK HISTE", "NOSTACK HIST")
plot.subplot_pad.cd()
# To shade region between up and down hists, need to create graph with
# the error bars as the up/down variations
x_low = np.array([
ratio_up.GetBinLowEdge(i) for i in range(1,
ratio_up.GetNbinsX() + 1)
],
dtype=float)
x_high = np.array([
ratio_up.GetBinLowEdge(i) for i in range(2,
ratio_up.GetNbinsX() + 2)
],
dtype=float)
x_mid = 0.5 * (x_low + x_high)
x_err = x_high - x_low
y_high = np.array([
max(ratio_up.GetBinContent(i), ratio_down.GetBinContent(i))
for i in range(1,
ratio_up.GetNbinsX() + 1)
])
y_high -= 1
y_low = np.array([
min(ratio_up.GetBinContent(i), ratio_down.GetBinContent(i))
for i in range(1,
ratio_up.GetNbinsX() + 1)
])
y_low = 1 - y_low
y_mid = np.array([1. for i in range(1, ratio_up.GetNbinsX() + 1)])
gr = ROOT.TGraphAsymmErrors(len(x_mid), x_mid, y_mid, x_err, x_err, y_low,
y_high)
gr.SetFillColor(ROOT.kGray + 2)
gr.SetFillStyle(3254)
gr.Draw('2 SAME')
plot.subplot_container.Draw("SAME NOSTACK HIST")
plot.subplot_line.Draw()
plot.save(output_filename)