def do_plots(root_dir):
# QG variable plots
pt_bins = qgc.PT_BINS[:]
var_list = qgc.COMMON_VARS
var_prepend = ""
radius, pus = cu.get_jet_config_from_dirname(root_dir)
jet_str = "AK%s PF %s" % (radius.upper(), pus.upper())
for gr_append in ["", "_groomed"][:1]:
if gr_append == "_groomed":
print("Doing groomed plots...")
else:
print("Doing ungroomed plots...")
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)
# tfiles = {
# "data_run_B": cu.open_root_file(os.path.join(root_dir, "uhh2.AnalysisModuleRunner.DATA.Data_JetHT_RunB.root")),
# "data_run_C": cu.open_root_file(os.path.join(root_dir, "uhh2.AnalysisModuleRunner.DATA.Data_JetHT_RunC.root")),
# "data_run_D": cu.open_root_file(os.path.join(root_dir, "uhh2.AnalysisModuleRunner.DATA.Data_JetHT_RunD.root")),
# "data_run_E": cu.open_root_file(os.path.join(root_dir, "uhh2.AnalysisModuleRunner.DATA.Data_JetHT_RunE.root")),
# "data_run_F": cu.open_root_file(os.path.join(root_dir, "uhh2.AnalysisModuleRunner.DATA.Data_JetHT_RunF.root")),
# "data_run_G": cu.open_root_file(os.path.join(root_dir, "uhh2.AnalysisModuleRunner.DATA.Data_JetHT_RunG.root")),
# "data_run_H": cu.open_root_file(os.path.join(root_dir, "uhh2.AnalysisModuleRunner.DATA.Data_JetHT_RunH.root")),
# }
tfiles = {
"data_run_B":
cu.open_root_file(
os.path.join(
root_dir,
"uhh2.AnalysisModuleRunner.DATA.Data_JetHT_ZeroBias_RunB.root"
)),
"data_run_C":
cu.open_root_file(
os.path.join(
root_dir,
"uhh2.AnalysisModuleRunner.DATA.Data_JetHT_ZeroBias_RunC.root"
)),
"data_run_D":
cu.open_root_file(
os.path.join(
root_dir,
"uhh2.AnalysisModuleRunner.DATA.Data_JetHT_ZeroBias_RunD.root"
)),
"data_run_E":
cu.open_root_file(
os.path.join(
root_dir,
"uhh2.AnalysisModuleRunner.DATA.Data_JetHT_ZeroBias_RunE.root"
)),
"data_run_F":
cu.open_root_file(
os.path.join(
root_dir,
"uhh2.AnalysisModuleRunner.DATA.Data_JetHT_ZeroBias_RunF.root"
)),
"data_run_G":
cu.open_root_file(
os.path.join(
root_dir,
"uhh2.AnalysisModuleRunner.DATA.Data_JetHT_ZeroBias_RunG.root"
)),
"data_run_H":
cu.open_root_file(
os.path.join(
root_dir,
"uhh2.AnalysisModuleRunner.DATA.Data_JetHT_ZeroBias_RunH.root"
)),
}
for ang in var_list[:]:
print("...Doing", ang.name)
v = "%s%s_vs_pt" % (var_prepend, ang.var)
zpj_1d_entries = []
dijet_cen_1d_entries = []
dijet_fwd_1d_entries = []
for pt_ind, (start_val, end_val) in enumerate(pt_bins):
entries = []
zpj_entries = []
dijet_cen_entries = []
dijet_fwd_entries = []
# Get all plots
lw = 2
msize = 1.1
data_line_width = lw
colours = [
ROOT.kBlack, ROOT.kRed, ROOT.kBlue, ROOT.kGreen + 2,
ROOT.kOrange + 1, ROOT.kAzure + 1, ROOT.kGreen + 3
]
# --------------------------------------------------------------
# Create reference hists, for Run G+H
# --------------------------------------------------------------
####################
# DIJET CENTRAL REGION
####################
h2d_qcd_cen_data_g = cu.get_from_tfile(
tfiles['data_run_G'], "%s/%s" % (dj_cen_dirname, v))
h2d_qcd_cen_data_h = cu.get_from_tfile(
tfiles['data_run_H'], "%s/%s" % (dj_cen_dirname, v))
colour = colours[0]
qcd_cen_kwargs_data = dict(line_color=colour,
line_width=data_line_width,
fill_color=colour,
marker_color=colour,
marker_style=cu.Marker.get(
qgc.QCD_MARKER),
marker_size=0,
label="Runs G+H")
dijet_cen_data_hist_g = qgp.get_projection_plot(
h2d_qcd_cen_data_g, start_val, end_val)
dijet_cen_data_hist_h = qgp.get_projection_plot(
h2d_qcd_cen_data_h, start_val, end_val)
dijet_cen_data_hist_g.Add(dijet_cen_data_hist_h)
dijet_cen_entries.append(
(dijet_cen_data_hist_g, qcd_cen_kwargs_data))
####################
# DIJET FORWARD REGION
####################
h2d_qcd_fwd_data_g = cu.get_from_tfile(
tfiles['data_run_G'], "%s/%s" % (dj_fwd_dirname, v))
h2d_qcd_fwd_data_h = cu.get_from_tfile(
tfiles['data_run_H'], "%s/%s" % (dj_fwd_dirname, v))
qcd_fwd_kwargs_data = dict(line_color=colour,
line_width=data_line_width,
fill_color=colour,
marker_color=colour,
marker_style=cu.Marker.get(
qgc.QCD_MARKER),
marker_size=0,
label="Runs G+H")
dijet_fwd_data_hist_g = qgp.get_projection_plot(
h2d_qcd_fwd_data_g, start_val, end_val)
dijet_fwd_data_hist_h = qgp.get_projection_plot(
h2d_qcd_fwd_data_h, start_val, end_val)
dijet_fwd_data_hist_g.Add(dijet_fwd_data_hist_h)
dijet_fwd_entries.append(
(dijet_fwd_data_hist_g, qcd_fwd_kwargs_data))
# --------------------------------------------------------------
# FOR SUMMED B-F:
# --------------------------------------------------------------
dijet_cen_data_hist_btof, dijet_fwd_data_hist_btof = None, None
runs = ["B", "C", "D", "E", "F"]
for run in runs:
# DIJET CENTRAL REGION
h2d_qcd_cen_data = cu.get_from_tfile(
tfiles['data_run_%s' % run],
"%s/%s" % (dj_cen_dirname, v))
this_dijet_cen_data_hist = qgp.get_projection_plot(
h2d_qcd_cen_data, start_val, end_val)
if dijet_cen_data_hist_btof is None:
dijet_cen_data_hist_btof = this_dijet_cen_data_hist.Clone(
)
else:
dijet_cen_data_hist_btof.Add(this_dijet_cen_data_hist)
# DIJET FORWARD REGION
h2d_qcd_fwd_data = cu.get_from_tfile(
tfiles['data_run_%s' % run], "%s/%s" %
(dj_fwd_dirname, v)) # use already merged jetht+zb
this_dijet_fwd_data_hist = qgp.get_projection_plot(
h2d_qcd_fwd_data, start_val, end_val)
if dijet_fwd_data_hist_btof is None:
dijet_fwd_data_hist_btof = this_dijet_fwd_data_hist.Clone(
)
else:
dijet_fwd_data_hist_btof.Add(this_dijet_fwd_data_hist)
colour = colours[1]
mark = cu.Marker.get('circle')
btof_cen_kwargs_data = dict(line_color=colour,
line_width=data_line_width,
fill_color=colour,
marker_color=colour,
marker_style=mark,
marker_size=msize,
label="Runs %s-%s" %
(runs[0], runs[-1]),
subplot=dijet_cen_data_hist_g)
dijet_cen_entries.append(
(dijet_cen_data_hist_btof, btof_cen_kwargs_data))
btof_fwd_kwargs_data = dict(line_color=colour,
line_width=data_line_width,
fill_color=colour,
marker_color=colour,
marker_style=mark,
marker_size=msize,
label="Runs %s-%s" %
(runs[0], runs[-1]),
subplot=dijet_fwd_data_hist_g)
dijet_fwd_entries.append(
(dijet_fwd_data_hist_btof, btof_fwd_kwargs_data))
# FOR INDIVIDUAL RUN PERIODS:
# runs = ["B", "C", "D", "E", "F"]
# for run, colour, mark in zip(runs, colours[1:], cu.Marker().cycle()):
# ####################
# # DIJET CENTRAL REGION
# ####################
# # JETHT DATA
# h2d_qcd_cen_data = cu.get_from_tfile(tfiles['data_run_%s' % run], "%s/%s" % (dj_cen_dirname, v))
# qcd_cen_kwargs_data = dict(line_color=colour, line_width=data_line_width, fill_color=colour,
# marker_color=colour, marker_style=mark, marker_size=msize,
# label="Run %s" % run,
# subplot=dijet_cen_data_hist_g)
# dijet_cen_data_hist = qgp.get_projection_plot(h2d_qcd_cen_data, start_val, end_val)
# dijet_cen_entries.append((dijet_cen_data_hist, qcd_cen_kwargs_data))
# ####################
# # DIJET FORWARD REGION
# ####################
# # JETHT DATA
# h2d_qcd_fwd_data = cu.get_from_tfile(tfiles['data_run_%s' % run], "%s/%s" % (dj_fwd_dirname, v)) # use already merged jetht+zb
# qcd_fwd_kwargs_data = dict(line_color=colour, line_width=data_line_width, fill_color=colour,
# marker_color=colour, marker_style=mark, marker_size=msize,
# label="Run %s" % run,
# subplot=dijet_fwd_data_hist_g)
# dijet_fwd_data_hist = qgp.get_projection_plot(h2d_qcd_fwd_data, start_val, end_val)
# dijet_fwd_entries.append((dijet_fwd_data_hist, qcd_fwd_kwargs_data))
# ####################
# # Z+JETS REGION
# ####################
# # SINGLE MU DATA
# # h2d_dyj_data = cu.get_from_tfile(os.path.join(root_dir, "uhh2.AnalysisModuleRunner.DATA.Data_SingleMu_Run%s.root" % run), "%s/%s" % (zpj_dirname, v))
# # dy_kwargs_data = dict(line_color=qgc.colour, line_width=data_line_width, fill_color=qgc.colour,
# # marker_color=qgc.colour, marker_style=cu.Marker.get(qgc.DY_MARKER), marker_size=msize,
# # label="SingleMu Run %s" % run)
# # zpj_data_hist = qgp.get_projection_plot(h2d_dyj_data, start_val, end_val)
# # zpj_entries.append((zpj_data_hist, dy_kwargs_data))
#################
# SETUP PLOTTING
#################
rebin = 2
v_lower = v.lower()
if "multiplicity" in v_lower:
rebin = 2
elif "flavour" in v_lower or "thrust" in v_lower:
rebin = 1
elif 'ptd' in v_lower:
rebin = 2
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)
ylim = 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_run_dependent%s" % (gr_append))
plot_dir = os.path.join(
root_dir, "plots_run_dependent_btof%s" % (gr_append))
subplot_title = "Run * / G+H"
subplot_title = "B-F / G+H"
subplot_limits = (0.5, 1.5)
xlabel = ang.name + " (" + ang.lambda_str + ")"
if gr_append is not "":
xlabel = "Groomed " + ang.name + " (" + ang.lambda_str + ")"
# dj central only
dijet_cen_entries = dijet_cen_entries[1:] + dijet_cen_entries[
0:1] # move G+H to last
qgp.do_comparison_plot(
dijet_cen_entries,
"%s/ptBinned/%s_pt%dto%d_dijet_central.%s" %
(plot_dir, v, start_val, end_val, OUTPUT_FMT),
rebin=rebin,
title="%d < p_{T}^{jet} < %d GeV\n%s\n%s" %
(start_val, end_val, jet_str, qgc.Dijet_CEN_LABEL),
xtitle=xlabel,
xlim=xlim,
ylim=ylim,
subplot_type='ratio',
subplot_title=subplot_title,
subplot_limits=subplot_limits)
# dj forward only
dijet_fwd_entries = dijet_fwd_entries[1:] + dijet_fwd_entries[
0:1] # move G+H to last
qgp.do_comparison_plot(
dijet_fwd_entries,
"%s/ptBinned/%s_pt%dto%d_dijet_forward.%s" %
(plot_dir, v, start_val, end_val, OUTPUT_FMT),
rebin=rebin,
title="%d < p_{T}^{jet} < %d GeV\n%s\n%s" %
(start_val, end_val, jet_str, qgc.Dijet_FWD_LABEL),
xtitle=xlabel,
xlim=xlim,
ylim=ylim,
subplot_type='ratio',
subplot_title=subplot_title,
subplot_limits=subplot_limits)
def do_plots(root_dir):
# QG variable plots
pt_bins = qgc.PT_BINS[:]
var_list = qgc.COMMON_VARS
var_prepend = ""
radius, pus = cu.get_jet_config_from_dirname(root_dir)
jet_str = "AK%s PF %s" % (radius.upper(), pus.upper())
for gr_append in ["", "_groomed"]:
if gr_append == "_groomed":
print("Doing groomed plots...")
else:
print("Doing ungroomed plots...")
if gr_append == "":
make_1d_plot(root_dir,
"Dijet_gen/pt_dijet_ave",
jet_str,
gen_only=True)
make_1d_plot(root_dir, "Dijet_tighter/pt_jet", jet_str)
dj_cen_dirname = "Dijet_QG_central_tighter%s" % (gr_append)
dj_fwd_dirname = "Dijet_QG_forward_tighter%s" % (gr_append)
for ang in var_list[:]:
print("...Doing", ang.name)
v = "%s%s_vs_pt" % (var_prepend, ang.var)
dijet_cen_2d_entries = []
dijet_fwd_2d_entries = []
dijet_cen_1d_entries = []
dijet_fwd_1d_entries = []
for pt_ind, (start_val, end_val) in enumerate(pt_bins):
entries = []
dijet_cen_entries = []
dijet_fwd_entries = []
# Get all plots
lw = 2
msize = 1.1
data_line_width = lw
####################
# DIJET CENTRAL REGION
####################
# JETHT/ZEROBIAS DATA
h2d_qcd_cen_data = grab_obj(
os.path.join(root_dir, qgc.JETHT_ZB_FILENAME), "%s/%s" %
(dj_cen_dirname, v)) # use already merged jetht+zb
qcd_cen_kwargs_data = dict(line_color=qgc.JETHT_COLOUR,
line_width=data_line_width,
fill_color=qgc.JETHT_COLOUR,
marker_color=qgc.JETHT_COLOUR,
marker_style=cu.Marker.get(
qgc.QCD_MARKER),
marker_size=msize,
label="Data")
dijet_cen_data_hist = qgp.get_projection_plot(
h2d_qcd_cen_data, start_val, end_val)
entries.append((dijet_cen_data_hist, qcd_cen_kwargs_data))
dijet_cen_entries.append(
(dijet_cen_data_hist, qcd_cen_kwargs_data))
if pt_ind == 0:
dijet_cen_2d_entries.append(
(h2d_qcd_cen_data, qcd_cen_kwargs_data))
# MG+PYTHIA QCD MC
h2d_qcd_cen_mc = grab_obj(
os.path.join(root_dir, qgc.QCD_FILENAME),
"%s/%s" % (dj_cen_dirname, v))
qcd_cen_kwargs_mc = dict(line_color=qgc.QCD_COLOUR,
line_width=lw,
fill_color=qgc.QCD_COLOUR,
marker_color=qgc.QCD_COLOUR,
marker_style=cu.Marker.get(
qgc.QCD_MARKER),
marker_size=0,
label="MG+PY8",
subplot=dijet_cen_data_hist)
# h2d_qcd_cen_mc.Scale(35860)
dijet_mgpy_hist = qgp.get_projection_plot(
h2d_qcd_cen_mc, start_val, end_val)
entries.append((dijet_mgpy_hist, qcd_cen_kwargs_mc))
dijet_cen_entries.append((dijet_mgpy_hist, qcd_cen_kwargs_mc))
if pt_ind == 0:
dijet_cen_2d_entries.append(
(h2d_qcd_cen_mc, qcd_cen_kwargs_mc))
# PYTHIA ONLY
# col = qgc.QCD_COLOURS[2]
# h2d_qcd_cen_mc2 = grab_obj(os.path.join(root_dir, qgc.QCD_PYTHIA_ONLY_FILENAME), "%s/%s" % (dj_cen_dirname, v))
# qcd_cen_kwargs_mc2 = dict(line_color=col, line_width=lw, fill_color=col,
# marker_color=col, marker_style=cu.Marker.get(qgc.QCD_MARKER), marker_size=0,
# label="PY8",
# subplot=dijet_cen_data_hist)
# # h2d_qcd_cen_mc2.Scale(35860)
# entries.append((qgp.get_projection_plot(h2d_qcd_cen_mc2, start_val, end_val), qcd_cen_kwargs_mc2))
# dijet_cen_entries.append((qgp.get_projection_plot(h2d_qcd_cen_mc2, start_val, end_val), qcd_cen_kwargs_mc2))
# if pt_ind == 0:
# dijet_cen_2d_entries.append((h2d_qcd_cen_mc2, qcd_cen_kwargs_mc2))
# HERWIG++ QCD
col2 = qgc.QCD_COLOURS[3]
h2d_qcd_cen_mc3 = grab_obj(
os.path.join(root_dir, qgc.QCD_HERWIG_FILENAME),
"%s/%s" % (dj_cen_dirname, v))
qcd_cen_kwargs_mc3 = dict(line_color=col2,
line_width=lw,
fill_color=col2,
marker_color=col2,
marker_style=cu.Marker.get(
qgc.QCD_MARKER),
marker_size=0,
label="H++",
subplot=dijet_cen_data_hist)
h2d_qcd_cen_mc3.Scale(TOTAL_LUMI)
dijet_hpp_hist = qgp.get_projection_plot(
h2d_qcd_cen_mc3, start_val, end_val)
entries.append((dijet_hpp_hist, qcd_cen_kwargs_mc3))
dijet_cen_entries.append((dijet_hpp_hist, qcd_cen_kwargs_mc3))
if pt_ind == 0:
dijet_cen_2d_entries.append(
(h2d_qcd_cen_mc3, qcd_cen_kwargs_mc3))
# HERWIG++ QCD WITH PT REWEIGHT
col3 = ROOT.kRed
h2d_qcd_cen_mc4 = grab_obj(
os.path.join(
root_dir,
"uhh2.AnalysisModuleRunner.MC.MC_HERWIG_QCD_PtReweight.root"
), "%s/%s" % (dj_cen_dirname, v))
qcd_cen_kwargs_mc4 = dict(line_color=col3,
line_width=lw,
fill_color=col3,
marker_color=col3,
marker_style=cu.Marker.get(
qgc.QCD_MARKER),
marker_size=0,
label="H++ (p_{T} reweighted)",
subplot=dijet_cen_data_hist)
h2d_qcd_cen_mc4.Scale(TOTAL_LUMI)
dijet_hpp_hist_reweight = qgp.get_projection_plot(
h2d_qcd_cen_mc4, start_val, end_val)
entries.append((dijet_hpp_hist_reweight, qcd_cen_kwargs_mc4))
dijet_cen_entries.append(
(dijet_hpp_hist_reweight, qcd_cen_kwargs_mc4))
if pt_ind == 0:
dijet_cen_2d_entries.append(
(h2d_qcd_cen_mc4, qcd_cen_kwargs_mc4))
####################
# DIJET FORWARD REGION
####################
# JETHT/ZEROBIAS DATA
h2d_qcd_fwd_data = grab_obj(
os.path.join(root_dir, qgc.JETHT_ZB_FILENAME), "%s/%s" %
(dj_fwd_dirname, v)) # use already merged jetht+zb
# h2d_zb_data = grab_obj(os.path.join(root_dir, qgc.ZB_FILENAME), "%s/%s" % (dj_cen_dirname, v))
# h2d_zb_data.Scale(1235009.27580634)
# h2d_qcd_cen_data.Add(h2d_zb_data)
qcd_fwd_kwargs_data = dict(line_color=qgc.JETHT_COLOUR,
line_width=data_line_width,
fill_color=qgc.JETHT_COLOUR,
marker_color=qgc.JETHT_COLOUR,
marker_style=cu.Marker.get(
qgc.QCD_MARKER),
marker_size=msize,
label="Data")
dijet_fwd_data_hist = qgp.get_projection_plot(
h2d_qcd_fwd_data, start_val, end_val)
entries.append((dijet_fwd_data_hist, qcd_fwd_kwargs_data))
dijet_fwd_entries.append(
(dijet_fwd_data_hist, qcd_fwd_kwargs_data))
if pt_ind == 0:
dijet_fwd_2d_entries.append(
(h2d_qcd_fwd_data, qcd_fwd_kwargs_data))
# MG+PYTHIA QCD MC
h2d_qcd_fwd_mc = grab_obj(
os.path.join(root_dir, qgc.QCD_FILENAME),
"%s/%s" % (dj_fwd_dirname, v))
qcd_fwd_kwargs_mc = dict(line_color=qgc.QCD_COLOUR,
line_width=lw,
fill_color=qgc.QCD_COLOUR,
marker_color=qgc.QCD_COLOUR,
marker_style=cu.Marker.get(
qgc.QCD_MARKER),
marker_size=0,
label="MG+PY8",
subplot=dijet_fwd_data_hist)
# h2d_qcd_fwd_mc.Scale(35860)
dijet_mgpy_hist = qgp.get_projection_plot(
h2d_qcd_fwd_mc, start_val, end_val)
entries.append((dijet_mgpy_hist, qcd_fwd_kwargs_mc))
dijet_fwd_entries.append((dijet_mgpy_hist, qcd_fwd_kwargs_mc))
if pt_ind == 0:
dijet_fwd_2d_entries.append(
(h2d_qcd_fwd_mc, qcd_fwd_kwargs_mc))
# PYTHIA ONLY
# col = qgc.QCD_COLOURS[2]
# h2d_qcd_fwd_mc2 = grab_obj(os.path.join(root_dir, qgc.QCD_PYTHIA_ONLY_FILENAME), "%s/%s" % (dj_fwd_dirname, v))
# qcd_fwd_kwargs_mc2 = dict(line_color=col, line_width=lw, fill_color=col,
# marker_color=col, marker_style=cu.Marker.get(qgc.QCD_MARKER), marker_size=0,
# label="PY8",
# subplot=dijet_fwd_data_hist)
# # h2d_qcd_fwd_mc2.Scale(35860)
# entries.append((qgp.get_projection_plot(h2d_qcd_fwd_mc2, start_val, end_val), qcd_fwd_kwargs_mc2))
# dijet_fwd_entries.append((qgp.get_projection_plot(h2d_qcd_fwd_mc2, start_val, end_val), qcd_fwd_kwargs_mc2))
# if pt_ind == 0:
# dijet_fwd_2d_entries.append((h2d_qcd_fwd_mc2, qcd_fwd_kwargs_mc2))
# HERWIG++ QCD
col2 = qgc.QCD_COLOURS[3]
h2d_qcd_fwd_mc3 = grab_obj(
os.path.join(root_dir, qgc.QCD_HERWIG_FILENAME),
"%s/%s" % (dj_fwd_dirname, v))
qcd_fwd_kwargs_mc3 = dict(line_color=col2,
line_width=lw,
fill_color=col2,
marker_color=col2,
marker_style=cu.Marker.get(
qgc.QCD_MARKER),
marker_size=0,
label="H++",
subplot=dijet_fwd_data_hist)
h2d_qcd_fwd_mc3.Scale(TOTAL_LUMI)
dijet_hpp_hist = qgp.get_projection_plot(
h2d_qcd_fwd_mc3, start_val, end_val)
entries.append((dijet_hpp_hist, qcd_fwd_kwargs_mc3))
dijet_fwd_entries.append((dijet_hpp_hist, qcd_fwd_kwargs_mc3))
if pt_ind == 0:
dijet_fwd_2d_entries.append(
(h2d_qcd_fwd_mc3, qcd_fwd_kwargs_mc3))
col3 = ROOT.kRed
h2d_qcd_fwd_mc4 = grab_obj(
os.path.join(
root_dir,
"uhh2.AnalysisModuleRunner.MC.MC_HERWIG_QCD_PtReweight.root"
), "%s/%s" % (dj_fwd_dirname, v))
qcd_fwd_kwargs_mc4 = dict(line_color=col3,
line_width=lw,
fill_color=col3,
marker_color=col3,
marker_style=cu.Marker.get(
qgc.QCD_MARKER),
marker_size=0,
label="H++ (p_{T} reweighted)",
subplot=dijet_fwd_data_hist)
h2d_qcd_fwd_mc4.Scale(TOTAL_LUMI)
dijet_hpp_hist_reweight = qgp.get_projection_plot(
h2d_qcd_fwd_mc4, start_val, end_val)
entries.append((dijet_hpp_hist_reweight, qcd_fwd_kwargs_mc4))
dijet_fwd_entries.append(
(dijet_hpp_hist_reweight, qcd_fwd_kwargs_mc4))
if pt_ind == 0:
dijet_fwd_2d_entries.append(
(h2d_qcd_fwd_mc4, qcd_fwd_kwargs_mc4))
dijet_cen_1d_entries.append(dijet_cen_entries)
dijet_fwd_1d_entries.append(dijet_fwd_entries)
#################
# SETUP PLOTTING
#################
rebin = 2
v_lower = v.lower()
if "multiplicity" in v_lower:
rebin = 2
elif "flavour" in v_lower or "thrust" in v_lower:
rebin = 1
elif 'ptd' in v_lower:
rebin = 2
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)
ylim = 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_dijet_vs_qcd_mc_vs_data%s_pt_reweight" %
(gr_append))
subplot_title = "MC / Data"
subplot_limits = (0.5, 1.5)
xlabel = ang.name + " (" + ang.lambda_str + ")"
if gr_append is not "":
xlabel = "Groomed " + ang.name + " (" + ang.lambda_str + ")"
# dj+zpj
# qgp.do_comparison_plot(entries,
# "%s/ptBinned/%s_pt%dto%d.%s" % (plot_dir, v, start_val, end_val, OUTPUT_FMT),
# rebin=rebin,
# title="%d < p_{T}^{jet} < %d GeV\n%s" % (start_val, end_val, jet_str),
# xtitle=ang.name + " (" + ang.lambda_str + ")",
# xlim=xlim, ylim=ylim,
# subplot_type='ratio',
# subplot_title=subplot_title,
# subplot_limits=subplot_limits)
# dj central only
qgp.do_comparison_plot(
dijet_cen_entries,
"%s/ptBinned/%s_pt%dto%d_dijet_central.%s" %
(plot_dir, v, start_val, end_val, OUTPUT_FMT),
rebin=rebin,
title="%d < p_{T}^{jet} < %d GeV\n%s\n%s" %
(start_val, end_val, jet_str, qgc.Dijet_CEN_LABEL),
xtitle=xlabel,
xlim=xlim,
ylim=ylim,
subplot_type='ratio',
subplot_title=subplot_title,
subplot_limits=subplot_limits)
# dj forward only
qgp.do_comparison_plot(
dijet_fwd_entries,
"%s/ptBinned/%s_pt%dto%d_dijet_forward.%s" %
(plot_dir, v, start_val, end_val, OUTPUT_FMT),
rebin=rebin,
title="%d < p_{T}^{jet} < %d GeV\n%s\n%s" %
(start_val, end_val, jet_str, qgc.Dijet_FWD_LABEL),
xtitle=xlabel,
xlim=xlim,
ylim=ylim,
subplot_type='ratio',
subplot_title=subplot_title,
subplot_limits=subplot_limits)
# Do overall summary plots across all pt bins
# ------------------------------------------------------------------
ylim_mean = None
if "width" in v_lower or "ptd" in v_lower:
ylim_mean = (0, 0.4)
elif "thrust" in v_lower:
ylim_mean = (0, 0.5)
elif "multiplicity" in v_lower and "ak4" in root_dir.lower():
ylim_mean = (0, 100)
ylim_mean = (0, 80)
if end_val < 150:
ylim_mean = (0, 50)
ylim_mean = None
ylim_rms = None
# Setup variable names for MPL
marker = ""
if "_" in ang.name or "^" in ang.name:
marker = "$"
var_label = marker + ang.name + marker + " ($%s$)" % ang.lambda_str
if gr_append != "":
var_label = "Groomed " + marker + ang.name + marker + " ($%s$)" % ang.lambda_str
qgp.do_mean_rms_summary_plot(
dijet_cen_1d_entries[:],
pt_bins[:],
"%s/ptBinned/%s_box_dijet_cen_mpl.%s" %
(plot_dir, v, OUTPUT_FMT),
var_label=var_label,
xlim=(50, 2000),
ylim_mean=ylim_mean,
ylim_rms=ylim_rms,
region_title="%s jets in dijet (central)" % (jet_str))
qgp.do_mean_rms_summary_plot(
dijet_fwd_1d_entries[:],
pt_bins[:],
"%s/ptBinned/%s_box_dijet_fwd_mpl.%s" %
(plot_dir, v, OUTPUT_FMT),
var_label=var_label,
xlim=(50, 2000),
ylim_mean=ylim_mean,
ylim_rms=ylim_rms,
region_title="%s jets in dijet (forward)" % (jet_str))
def do_component_plots(mgpythia_dir, pythia_only_dir, plot_dir):
# Do 2D plots for diff ptMin folders
jet_flavs = ["", "g", "q"]
ptmin_vals = [50, 100, 200, 400, 800]
ptmin_vals = [100, 800]
# first the pt vs ones:
plotnames = [
"genjet_pt_vs_constituent_pt", "genjet_pt_vs_constituent_zi",
"genjet_pt_vs_constituent_deta", "genjet_pt_vs_constituent_dphi",
"genjet_pt_vs_constituent_dr"
]
for plotname, ptmin, renorm, logz, flav in product(plotnames, ptmin_vals,
['Y', None],
[True, False],
jet_flavs):
rebin = [1, 1]
ylim = [ptmin, 2000]
dirname = "Dijet_genjet_ptMin_%d" % ptmin
this_hist = os.path.join(dirname, flav + plotname)
log_append = "_logZ" if logz else ""
qgg.do_2D_plot(
grab_obj(os.path.join(mgpythia_dir, qgc.QCD_FILENAME), this_hist),
output_filename=
"%s/constituent_plots/ptMin_%d/%s_mgpythia_norm%s%s.%s" %
(plot_dir, ptmin, flav + plotname, renorm, log_append, OUTPUT_FMT),
renorm_axis=renorm,
title="MG+Pythia",
rebin=rebin,
recolour=True,
ylim=ylim,
logz=logz)
qgg.do_2D_plot(
grab_obj(os.path.join(pythia_only_dir, qgc.QCD_FILENAME),
this_hist),
output_filename=
"%s/constituent_plots/ptMin_%d/%s_pythiaOnly_norm%s%s.%s" %
(plot_dir, ptmin, flav + plotname, renorm, log_append, OUTPUT_FMT),
renorm_axis=renorm,
title="Pythia only",
rebin=rebin,
recolour=True,
ylim=ylim,
logz=logz)
# Now LHA vs X ones
plotnames = ["genjet_LHA_vs_zi", "genjet_LHA_vs_thetai"]
for plotname, ptmin, renorm, logz, flav in product(plotnames, ptmin_vals,
['X', 'Y', None],
[True, False],
jet_flavs):
rebin = [4, 4]
xlim = [0, 0.5] if ("zi" in plotname and renorm != "X") else None
ylim = None
dirname = "Dijet_genjet_ptMin_%d" % ptmin
this_hist = os.path.join(dirname, flav + plotname)
log_append = "_logZ" if logz else ""
qgg.do_2D_plot(
grab_obj(os.path.join(mgpythia_dir, qgc.QCD_FILENAME), this_hist),
output_filename=
"%s/constituent_plots/ptMin_%d/%s_mgpythia_norm%s%s.%s" %
(plot_dir, ptmin, flav + plotname, renorm, log_append, OUTPUT_FMT),
renorm_axis=renorm,
title="MG+Pythia, %s-jet, ptMin = %d GeV" % (flav, ptmin),
rebin=rebin,
recolour=True,
xlim=xlim,
ylim=ylim,
logz=logz)
qgg.do_2D_plot(
grab_obj(os.path.join(pythia_only_dir, qgc.QCD_FILENAME),
this_hist),
output_filename=
"%s/constituent_plots/ptMin_%d/%s_pythiaOnly_norm%s%s.%s" %
(plot_dir, ptmin, flav + plotname, renorm, log_append, OUTPUT_FMT),
renorm_axis=renorm,
title="Pythia only, %s-jet, ptMin = %d GeV" % (flav, ptmin),
rebin=rebin,
recolour=True,
xlim=xlim,
ylim=ylim,
logz=logz)
def do_2D_plot_with_contours(obj,
contour_obj,
output_filename,
renorm_axis=None,
title=None,
rebin=None,
recolour=True,
xlim=None,
ylim=None,
logx=False,
logy=False,
logz=False):
"""Like normal 2D plotter but contour_obj will be plotted using contours"""
if rebin:
obj.Rebin2D(*rebin)
if renorm_axis:
obj_renorm = cu.make_normalised_TH2(obj, renorm_axis, recolour)
else:
obj_renorm = obj
if title:
obj_renorm.SetTitle(title)
canvas = ROOT.TCanvas(ROOT.TUUID().AsString(), "", 800, 800)
canvas.SetTicks(1, 1)
canvas.SetLeftMargin(0.13)
canvas.SetBottomMargin(0.11)
if logx:
canvas.SetLogx(1)
if logy:
canvas.SetLogy(1)
if logz:
canvas.SetLogz(1)
obj_renorm.Draw("COLZ")
if xlim is not None:
obj_renorm.GetXaxis().SetRangeUser(*xlim)
if ylim is not None:
obj_renorm.GetYaxis().SetRangeUser(*ylim)
obj_renorm.GetYaxis().SetTitleOffset(1.7)
obj_renorm.GetXaxis().SetTitleOffset(1.2)
if contour_obj:
contour_obj.Draw("CONT3 SAME")
output_filename = os.path.abspath(output_filename)
odir = os.path.dirname(output_filename)
if not os.path.isdir(odir):
os.makedirs(odir)
canvas.SaveAs(output_filename)
# Do 2D plots for premade jet pt cut objs
jet_pt_vals = [(100, 200), (800, 1000)]
for (jet_pt_min,
jet_pt_max), renorm, logz in product(jet_pt_vals, ['X', 'Y',
None][2:],
[True, False]):
rebin = [1, 1]
xlim = [0, 1]
ylim = [0, 0.05]
dirname = "Dijet_genjet"
jet_type = "g"
plotname = jet_type + "genjet_constituent_zi_vs_constituent_thetai_pt%dto%d" % (
jet_pt_min, jet_pt_max)
this_hist = os.path.join(dirname, plotname)
log_append = "_logZ" if logz else ""
contour_hist = grab_obj(os.path.join(mgpythia_dir, qgc.QCD_FILENAME),
this_hist).Clone("contours")
for xbin in range(1, contour_hist.GetNbinsX() + 1):
for ybin in range(1, contour_hist.GetNbinsY() + 1):
xval = 0.5 * (contour_hist.GetXaxis().GetBinCenter(xbin) +
contour_hist.GetXaxis().GetBinCenter(xbin + 1))
yval = 0.5 * (contour_hist.GetYaxis().GetBinCenter(ybin) +
contour_hist.GetYaxis().GetBinCenter(ybin + 1))
contour_hist.SetBinContent(xbin, ybin,
math.sqrt(xval / 0.4) * yval)
levels = array('d',
[0.001, 0.002, 0.005, 0.01, 0.02, 0.05, 0.1, 0.2, 0.5])
contour_hist.SetContour(len(levels), levels)
contour_hist.SetLineColor(ROOT.kRed)
do_2D_plot_with_contours(
grab_obj(os.path.join(mgpythia_dir, qgc.QCD_FILENAME), this_hist),
contour_hist,
output_filename="%s/constituent_plots/%s_mgpythia_norm%s%s.%s" %
(plot_dir, plotname, renorm, log_append, OUTPUT_FMT),
renorm_axis=renorm,
title="MG+Pythia, %d < p_{T}^{j} < %d GeV" %
(jet_pt_min, jet_pt_max),
rebin=rebin,
recolour=True,
xlim=xlim,
ylim=ylim,
logz=logz)
do_2D_plot_with_contours(
grab_obj(os.path.join(pythia_only_dir, qgc.QCD_FILENAME),
this_hist),
contour_hist,
output_filename="%s/constituent_plots/%s_pythiaOnly_norm%s%s.%s" %
(plot_dir, plotname, renorm, log_append, OUTPUT_FMT),
renorm_axis=renorm,
title="Pythia only, %d < p_{T}^{j} < %d GeV" %
(jet_pt_min, jet_pt_max),
rebin=rebin,
recolour=True,
xlim=xlim,
ylim=ylim,
logz=logz)
# Do 1D projection plots
for (jet_pt_min, jet_pt_max) in jet_pt_vals:
lw = 2
dirname = "Dijet_genjet"
jet_type = "g"
plotname = jet_type + "genjet_constituent_zi_vs_constituent_thetai_pt%dto%d" % (
jet_pt_min, jet_pt_max)
this_hist = os.path.join(dirname, plotname)
# Do projection plots for various zi bins
cut_zi_bins = [(0, 0.001), (0, 0.005),
(0, 0.01), (0, 0.05), (0.05, 0.1), (0, 0.1), (0.1, 0.2),
(0.3, 0.4), (0.4, 0.5), (0.8, 1.0), (0, 1)]
for i, (start_val, end_val) in enumerate(cut_zi_bins):
entries_normal = []
h2d_mgpythia = grab_obj(
os.path.join(mgpythia_dir, qgc.QCD_FILENAME), this_hist)
mgpythia_kwargs = dict(line_color=qgc.QCD_COLOUR,
fill_color=qgc.QCD_COLOUR,
label="MG+Pythia",
line_width=lw)
entries_normal.append(
(qgg.get_projection_plot(h2d_mgpythia, start_val, end_val,
'y'), mgpythia_kwargs))
h2d_pythiaonly = grab_obj(
os.path.join(pythia_only_dir, qgc.QCD_FILENAME), this_hist)
pythiaonly_kwargs = dict(line_color=ROOT.kRed,
fill_color=ROOT.kRed,
label="Pythia only",
line_width=lw)
entries_normal.append(
(qgg.get_projection_plot(h2d_pythiaonly, start_val, end_val,
'y'), pythiaonly_kwargs))
ofilename = jet_type + "genjet_constituent_thetai_binned_zi%gto%g_jetPt%dto%d" % (
start_val, end_val, jet_pt_min, jet_pt_max)
rebin = 5 if end_val <= 0.1 else 2
xlim = None if end_val <= 0.1 else [0, 0.6]
if end_val >= 1:
rebin = 4
xlim = [0, 1.2]
qgg.do_comparison_plot(
entries_normal,
"%s/constituent_plots/%s.%s" %
(plot_dir, ofilename, OUTPUT_FMT),
rebin=rebin,
title="%g < z_{i} < %g, %d < p_{T}^{jet} < %d GeV" %
(start_val, end_val, jet_pt_min, jet_pt_max),
xtitle="#theta_{i}",
xlim=xlim,
ylim=None,
subplot_type="ratio",
subplot_title="#splitline{Ratio wrt}{MG+Pythia}")
# Do projections hists for various theta_i bins
cut_thetai_bins = [(0, 0.01), (0.01, 0.02), (0.02, 0.05), (0.05, 0.10),
(0.1, 0.15), (0.15, 0.2), (0.2, 0.3), (0.3, 0.4),
(0.4, 0.6), (0.6, 0.8), (0.8, 1), (1, 1.5),
(0, 2)][-1:]
deltas = []
delta_components = []
colours = [
ROOT.kBlue, ROOT.kRed, ROOT.kGreen + 2, ROOT.kOrange - 3,
ROOT.kMagenta, ROOT.kAzure + 1
]
for i, (start_val, end_val) in enumerate(cut_thetai_bins[::]):
entries_normal = []
h2d_mgpythia = grab_obj(
os.path.join(mgpythia_dir, qgc.QCD_FILENAME), this_hist)
mgpythia_kwargs = dict(line_color=qgc.QCD_COLOUR,
fill_color=qgc.QCD_COLOUR,
label="MG+Pythia",
line_width=lw)
h_mgpythia = qgg.get_projection_plot(h2d_mgpythia, start_val,
end_val, 'x')
h_mgpythia.Rebin(4)
entries_normal.append(
(h_mgpythia.Clone(ROOT.TUUID().AsString()), mgpythia_kwargs))
h2d_pythiaonly = grab_obj(
os.path.join(pythia_only_dir, qgc.QCD_FILENAME), this_hist)
pythiaonly_kwargs = dict(line_color=ROOT.kRed,
fill_color=ROOT.kRed,
label="Pythia only",
line_width=lw)
h_pythiaonly = qgg.get_projection_plot(h2d_pythiaonly, start_val,
end_val, 'x')
h_pythiaonly.Rebin(4)
entries_normal.append((h_pythiaonly.Clone(ROOT.TUUID().AsString()),
pythiaonly_kwargs))
# rebin = 5 if end_val <= 0.1 else 2
rebin = None
xlim = [0, 0.5] if end_val <= 0.1 else [0, 0.2]
if end_val == 2:
xlim = [0, 0.2]
ofilename = jet_type + "genjet_constituent_zi_binned_thetai%gto%g_jetPt%dto%d" % (
start_val, end_val, jet_pt_min, jet_pt_max)
qgg.do_comparison_plot(
entries_normal,
"%s/constituent_plots/%s.%s" %
(plot_dir, ofilename, OUTPUT_FMT),
rebin=rebin,
title="%g < #theta_{i} < %g, %d < p_{T}^{jet} < %d GeV" %
(start_val, end_val, jet_pt_min, jet_pt_max),
xtitle="z_{i}",
xlim=xlim,
subplot_type="ratio",
subplot_title="#splitline{Ratio wrt}{MG+Pythia}")
ddelta_hist = qgd.get_ddelta_plot(h_mgpythia, h_pythiaonly)
this_colour = colours[i % len(colours)]
line_style = 1 + i // len(colours)
c = Contribution(ddelta_hist,
label="%g-%g" % (start_val, end_val),
line_width=1,
line_style=line_style,
marker_color=this_colour,
line_color=this_colour,
fill_color=this_colour)
delta_components.append(c)
deltas.append(qgd.calculate_delta(ddelta_hist))
p = Plot(delta_components,
what="hist",
ytitle="p.d.f",
xlim=[0, 0.2],
title="%d < p_{T}^{jet} < %d GeV" % (jet_pt_min, jet_pt_max))
p.plot("NOSTACK HISTE")
p.save("%s/constituent_plots/ddelta_thetai_jetPt%dto%d.%s" %
(plot_dir, jet_pt_min, jet_pt_max, OUTPUT_FMT))
gr = qgd.construct_deltas_graph(deltas[::])
c = Contribution(gr, label="BLAH", marker_style=0)
graph_contribs = []
graph_contribs.append(c)
bin_labels = ["{:g} - {:g}".format(*b) for b in cut_thetai_bins]
qgd.do_deltas_plot(graph_contribs,
"%s/constituent_plots/delta_thetai_jetPt%dto%d.%s" %
(plot_dir, jet_pt_min, jet_pt_max, OUTPUT_FMT),
bin_labels=bin_labels,
title="%d < p_{T}^{jet} < %d GeV" %
(jet_pt_min, jet_pt_max),
xtitle="#theta_{i}")
def do_plots(root_dir, title):
# QG variable plots
pt_bins = qgc.PT_BINS[:]
var_list = qgc.COMMON_VARS
var_prepend = ""
radius, pus = cu.get_jet_config_from_dirname(root_dir)
jet_str = "AK%s PF %s" % (radius.upper(), pus.upper())
for gr_append in ["", "_groomed"][:1]:
if gr_append == "_groomed":
print("Doing groomed plots...")
else:
print("Doing ungroomed plots...")
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)
for ang in var_list[:]:
print("...Doing", ang.name)
v = "%s%s_vs_pt" % (var_prepend, ang.var)
zpj_2d_entries = []
dijet_cen_2d_entries = []
dijet_fwd_2d_entries = []
zpj_1d_entries = []
dijet_cen_1d_entries = []
dijet_fwd_1d_entries = []
for pt_ind, (start_val, end_val) in enumerate(pt_bins):
entries = []
zpj_entries = []
dijet_cen_entries = []
dijet_fwd_entries = []
# Get all plots
lw = 2
msize = 1.1
data_line_width = lw
mc_msize = 1E-3 # small enough to not be seen but not 0 - otherwise the horizontal lines on error bars don't get drawn
mgpy_label = "MG5+Pythia8"
hpp_label = "Herwig++"
####################
# Z+JETS REGION
####################
# TODO: add these
# SINGLE MU DATA
# if os.path.isfile(os.path.join(root_dir, qgc.SINGLE_MU_FILENAME)):
# h2d_dyj_data = grab_obj(os.path.join(root_dir, qgc.SINGLE_MU_FILENAME), "%s/%s" % (zpj_dirname, v))
# dy_kwargs_data = dict(line_color=qgc.SINGLE_MU_COLOUR, line_width=data_line_width, fill_color=qgc.SINGLE_MU_COLOUR,
# marker_color=qgc.SINGLE_MU_COLOUR, marker_style=cu.Marker.get(qgc.DY_MARKER), marker_size=msize*0.7,
# label="Data")
# zpj_data_hist = qgp.get_projection_plot(h2d_dyj_data, start_val, end_val)
# entries.append((zpj_data_hist, dy_kwargs_data))
# zpj_entries.append((zpj_data_hist, dy_kwargs_data))
# if pt_ind == 0:
# zpj_2d_entries.append((h2d_dyj_data, dy_kwargs_data))
# # PYTHIA DY MC
# if os.path.isfile(os.path.join(root_dir, qgc.DY_FILENAME)):
# h2d_dyj_mc = grab_obj(os.path.join(root_dir, qgc.DY_FILENAME), "%s/%s" % (zpj_dirname, v))
# dy_kwargs_mc = dict(line_color=qgc.DY_COLOUR, line_width=lw, fill_color=qgc.DY_COLOUR,
# marker_color=qgc.DY_COLOUR, marker_style=cu.Marker.get(qgc.DY_MARKER), marker_size=mc_msize,
# label=mgpy_label,
# subplot=zpj_data_hist)
# entries.append((qgp.get_projection_plot(h2d_dyj_mc, start_val, end_val), dy_kwargs_mc))
# zpj_entries.append((qgp.get_projection_plot(h2d_dyj_mc, start_val, end_val), dy_kwargs_mc))
# if pt_ind == 0:
# zpj_2d_entries.append((h2d_dyj_mc, dy_kwargs_mc))
# # HERWIG++ DY
# if os.path.isfile(os.path.join(root_dir, qgc.DY_HERWIG_FILENAME)):
# h2d_dyj_mc_hpp = grab_obj(os.path.join(root_dir, qgc.DY_HERWIG_FILENAME), "%s/%s" % (zpj_dirname, v))
# col_hpp = qgc.DY_COLOURS[2]
# dy_kwargs_mc_hpp = dict(line_color=col_hpp, line_width=lw, fill_color=col_hpp,
# marker_color=col_hpp, marker_style=cu.Marker.get(qgc.DY_MARKER), marker_size=mc_msize,
# label=hpp_label,
# subplot=zpj_data_hist)
# entries.append((qgp.get_projection_plot(h2d_dyj_mc_hpp, start_val, end_val), dy_kwargs_mc_hpp))
# zpj_entries.append((qgp.get_projection_plot(h2d_dyj_mc_hpp, start_val, end_val), dy_kwargs_mc_hpp))
# if pt_ind == 0:
# zpj_2d_entries.append((h2d_dyj_mc_hpp, dy_kwargs_mc_hpp))
# MG+HERWIG++ DY
# if end_val < 151:
# h2d_dyj_mc3 = grab_obj(os.path.join(root_dir, qgc.DY_MG_HERWIG_FILENAME), "%s/%s" % (zpj_dirname, v))
# col4 = qgc.DY_COLOURS[3]
# dy_kwargs_mc3 = dict(line_color=col4, line_width=lw, fill_color=col4,
# marker_color=col4, marker_style=cu.Marker.get(qgc.DY_MARKER), marker_size=0,
# label="MG+Herwig++",
# subplot=zpj_data_hist)
# entries.append((qgp.get_projection_plot(h2d_dyj_mc3, start_val, end_val), dy_kwargs_mc3))
# zpj_entries.append((qgp.get_projection_plot(h2d_dyj_mc3, start_val, end_val), dy_kwargs_mc3))
# if pt_ind == 0:
# zpj_2d_entries.append((h2d_dyj_mc3, dy_kwargs_mc3))
# else:
# zpj_entries.append(None)
####################
# DIJET CENTRAL REGION
####################
# JETHT/ZEROBIAS DATA
if os.path.isfile(os.path.join(root_dir,
qgc.JETHT_ZB_FILENAME)):
h2d_qcd_cen_data = grab_obj(
os.path.join(root_dir,
qgc.JETHT_ZB_FILENAME), "%s/%s" %
(dj_cen_dirname, v)) # use already merged jetht+zb
qcd_cen_kwargs_data = dict(line_color=qgc.JETHT_COLOUR,
line_width=data_line_width,
fill_color=qgc.JETHT_COLOUR,
marker_color=qgc.JETHT_COLOUR,
marker_style=cu.Marker.get(
qgc.QCD_MARKER),
marker_size=msize,
label="Data")
dijet_cen_data_hist = qgp.get_projection_plot(
h2d_qcd_cen_data, start_val, end_val)
entries.append((dijet_cen_data_hist, qcd_cen_kwargs_data))
dijet_cen_entries.append(
(dijet_cen_data_hist, qcd_cen_kwargs_data))
if pt_ind == 0:
dijet_cen_2d_entries.append(
(h2d_qcd_cen_data, qcd_cen_kwargs_data))
# MG+PYTHIA QCD MC
if os.path.isfile(os.path.join(root_dir, qgc.QCD_FILENAME)):
h2d_qcd_cen_mc = grab_obj(
os.path.join(root_dir, qgc.QCD_FILENAME),
"%s/%s" % (dj_cen_dirname, v))
qcd_cen_kwargs_mc = dict(
line_color=qgc.QCD_COLOUR,
line_width=lw,
fill_color=qgc.QCD_COLOUR,
marker_color=qgc.QCD_COLOUR,
marker_style=cu.Marker.get(qgc.QCD_MARKER),
marker_size=mc_msize,
label=mgpy_label + "\n[NNPDF30_lo_as_0130, default]",
subplot=dijet_cen_data_hist)
dijet_mgpy_hist = qgp.get_projection_plot(
h2d_qcd_cen_mc, start_val, end_val)
entries.append((dijet_mgpy_hist, qcd_cen_kwargs_mc))
dijet_cen_entries.append(
(dijet_mgpy_hist, qcd_cen_kwargs_mc))
if pt_ind == 0:
dijet_cen_2d_entries.append(
(h2d_qcd_cen_mc, qcd_cen_kwargs_mc))
# Add NNPDF30_lo_as_0118
fname = "uhh2.AnalysisModuleRunner.MC.MC_QCD_NNPDF30_lo_as_0118.root"
if os.path.isfile(os.path.join(root_dir, fname)):
h2d_qcd_cen_mc_pdf2 = grab_obj(
os.path.join(root_dir, fname),
"%s/%s" % (dj_cen_dirname, v))
col = qgc.QCD_COLOURS[4]
qcd_cen_kwargs_mc2 = dict(
line_color=col,
line_width=lw,
fill_color=col,
marker_color=col,
marker_style=cu.Marker.get(qgc.QCD_MARKER),
marker_size=mc_msize,
label=mgpy_label + "\n[NNPDF30_lo_as_0118]",
subplot=dijet_cen_data_hist)
dijet_mgpy_hist2 = qgp.get_projection_plot(
h2d_qcd_cen_mc_pdf2, start_val, end_val)
entries.append((dijet_mgpy_hist2, qcd_cen_kwargs_mc2))
dijet_cen_entries.append(
(dijet_mgpy_hist2, qcd_cen_kwargs_mc2))
if pt_ind == 0:
dijet_cen_2d_entries.append(
(h2d_qcd_cen_mc_pdf2, qcd_cen_kwargs_mc2))
# Add HERAPDF20_LO_EIG
fname = "uhh2.AnalysisModuleRunner.MC.MC_QCD_HERAPDF20_LO_EIG.root"
if os.path.isfile(os.path.join(root_dir, fname)):
h2d_qcd_cen_mc_pdf3 = grab_obj(
os.path.join(root_dir, fname),
"%s/%s" % (dj_cen_dirname, v))
col = qgc.QCD_COLOURS[5]
qcd_cen_kwargs_mc3 = dict(
line_color=col,
line_width=lw,
fill_color=col,
marker_color=col,
marker_style=cu.Marker.get(qgc.QCD_MARKER),
marker_size=mc_msize,
label=mgpy_label + "\n[HERAPDF20_LO_EIG]",
subplot=dijet_cen_data_hist)
dijet_mgpy_hist3 = qgp.get_projection_plot(
h2d_qcd_cen_mc_pdf3, start_val, end_val)
entries.append((dijet_mgpy_hist3, qcd_cen_kwargs_mc3))
dijet_cen_entries.append(
(dijet_mgpy_hist3, qcd_cen_kwargs_mc3))
if pt_ind == 0:
dijet_cen_2d_entries.append(
(h2d_qcd_cen_mc_pdf3, qcd_cen_kwargs_mc3))
# Add CT14lo
fname = "uhh2.AnalysisModuleRunner.MC.MC_QCD_CT14lo.root"
if os.path.isfile(os.path.join(root_dir, fname)):
h2d_qcd_cen_mc_pdf4 = grab_obj(
os.path.join(root_dir, fname),
"%s/%s" % (dj_cen_dirname, v))
col = qgc.QCD_COLOURS[6]
qcd_cen_kwargs_mc4 = dict(line_color=col,
line_width=lw,
fill_color=col,
marker_color=col,
marker_style=cu.Marker.get(
qgc.QCD_MARKER),
marker_size=mc_msize,
label=mgpy_label + "\n[CT14lo]",
subplot=dijet_cen_data_hist)
dijet_mgpy_hist4 = qgp.get_projection_plot(
h2d_qcd_cen_mc_pdf4, start_val, end_val)
entries.append((dijet_mgpy_hist4, qcd_cen_kwargs_mc4))
dijet_cen_entries.append(
(dijet_mgpy_hist4, qcd_cen_kwargs_mc4))
if pt_ind == 0:
dijet_cen_2d_entries.append(
(h2d_qcd_cen_mc_pdf4, qcd_cen_kwargs_mc4))
# PYTHIA ONLY
# if os.path.isfile(os.path.join(root_dir, qgc.QCD_PYTHIA_ONLY_FILENAME)):
# col = qgc.QCD_COLOURS[2]
# h2d_qcd_cen_mc2 = grab_obj(os.path.join(root_dir, qgc.QCD_PYTHIA_ONLY_FILENAME), "%s/%s" % (dj_cen_dirname, v))
# qcd_cen_kwargs_mc2 = dict(line_color=col, line_width=lw, fill_color=col,
# marker_color=col, marker_style=cu.Marker.get(qgc.QCD_MARKER), marker_size=mc_msize,
# label="Pythia8",
# subplot=dijet_cen_data_hist)
# entries.append((qgp.get_projection_plot(h2d_qcd_cen_mc2, start_val, end_val), qcd_cen_kwargs_mc2))
# dijet_cen_entries.append((qgp.get_projection_plot(h2d_qcd_cen_mc2, start_val, end_val), qcd_cen_kwargs_mc2))
# if pt_ind == 0:
# dijet_cen_2d_entries.append((h2d_qcd_cen_mc2, qcd_cen_kwargs_mc2))
# HERWIG++ QCD
if os.path.isfile(
os.path.join(root_dir, qgc.QCD_HERWIG_FILENAME)):
col_hpp = qgc.QCD_COLOURS[3]
h2d_qcd_cen_mc_hpp = grab_obj(
os.path.join(root_dir, qgc.QCD_HERWIG_FILENAME),
"%s/%s" % (dj_cen_dirname, v))
qcd_cen_kwargs_mc_hpp = dict(line_color=col_hpp,
line_width=lw,
fill_color=col_hpp,
marker_color=col_hpp,
marker_style=cu.Marker.get(
qgc.QCD_MARKER),
marker_size=mc_msize,
label=hpp_label,
subplot=dijet_cen_data_hist)
dijet_hpp_hist = qgp.get_projection_plot(
h2d_qcd_cen_mc_hpp, start_val, end_val)
entries.append((dijet_hpp_hist, qcd_cen_kwargs_mc_hpp))
dijet_cen_entries.append(
(dijet_hpp_hist, qcd_cen_kwargs_mc_hpp))
if pt_ind == 0:
dijet_cen_2d_entries.append(
(h2d_qcd_cen_mc_hpp, qcd_cen_kwargs_mc_hpp))
####################
# DIJET FORWARD REGION
####################
# JETHT/ZEROBIAS DATA
if os.path.isfile(os.path.join(root_dir,
qgc.JETHT_ZB_FILENAME)):
h2d_qcd_fwd_data = grab_obj(
os.path.join(root_dir,
qgc.JETHT_ZB_FILENAME), "%s/%s" %
(dj_fwd_dirname, v)) # use already merged jetht+zb
qcd_fwd_kwargs_data = dict(
line_color=qgc.JETHT_COLOUR,
line_width=data_line_width,
fill_color=qgc.JETHT_COLOUR,
marker_color=qgc.JETHT_COLOUR,
marker_style=cu.Marker.get('triangleDown'),
marker_size=msize,
label="Data")
dijet_fwd_data_hist = qgp.get_projection_plot(
h2d_qcd_fwd_data, start_val, end_val)
entries.append((dijet_fwd_data_hist, qcd_fwd_kwargs_data))
dijet_fwd_entries.append(
(dijet_fwd_data_hist, qcd_fwd_kwargs_data))
if pt_ind == 0:
dijet_fwd_2d_entries.append(
(h2d_qcd_fwd_data, qcd_fwd_kwargs_data))
# MG+PYTHIA QCD MC
if os.path.isfile(os.path.join(root_dir, qgc.QCD_FILENAME)):
h2d_qcd_fwd_mc = grab_obj(
os.path.join(root_dir, qgc.QCD_FILENAME),
"%s/%s" % (dj_fwd_dirname, v))
qcd_fwd_kwargs_mc = dict(
line_color=qgc.QCD_COLOUR,
line_width=lw,
fill_color=qgc.QCD_COLOUR,
marker_color=qgc.QCD_COLOUR,
marker_style=cu.Marker.get(qgc.QCD_MARKER),
marker_size=mc_msize,
label=mgpy_label + "\n[NNPDF30_lo_as_0130, default]",
subplot=dijet_fwd_data_hist)
dijet_mgpy_hist = qgp.get_projection_plot(
h2d_qcd_fwd_mc, start_val, end_val)
entries.append((dijet_mgpy_hist, qcd_fwd_kwargs_mc))
dijet_fwd_entries.append(
(dijet_mgpy_hist, qcd_fwd_kwargs_mc))
if pt_ind == 0:
dijet_fwd_2d_entries.append(
(h2d_qcd_fwd_mc, qcd_fwd_kwargs_mc))
# Add NNPDF30_lo_as_0118
fname = "uhh2.AnalysisModuleRunner.MC.MC_QCD_NNPDF30_lo_as_0118.root"
if os.path.isfile(os.path.join(root_dir, fname)):
h2d_qcd_fwd_mc_pdf2 = grab_obj(
os.path.join(root_dir, fname),
"%s/%s" % (dj_fwd_dirname, v))
col = qgc.QCD_COLOURS[4]
qcd_fwd_kwargs_mc2 = dict(
line_color=col,
line_width=lw,
fill_color=col,
marker_color=col,
marker_style=cu.Marker.get(qgc.QCD_MARKER),
marker_size=mc_msize,
label=mgpy_label + "\n[NNPDF30_lo_as_0118]",
subplot=dijet_fwd_data_hist)
dijet_mgpy_hist2 = qgp.get_projection_plot(
h2d_qcd_fwd_mc_pdf2, start_val, end_val)
entries.append((dijet_mgpy_hist2, qcd_fwd_kwargs_mc2))
dijet_fwd_entries.append(
(dijet_mgpy_hist2, qcd_fwd_kwargs_mc2))
if pt_ind == 0:
dijet_fwd_2d_entries.append(
(h2d_qcd_fwd_mc_pdf2, qcd_fwd_kwargs_mc2))
# Add HERAPDF20_LO_EIG
fname = "uhh2.AnalysisModuleRunner.MC.MC_QCD_HERAPDF20_LO_EIG.root"
if os.path.isfile(os.path.join(root_dir, fname)):
h2d_qcd_fwd_mc_pdf3 = grab_obj(
os.path.join(root_dir, fname),
"%s/%s" % (dj_fwd_dirname, v))
col = qgc.QCD_COLOURS[5]
qcd_fwd_kwargs_mc3 = dict(
line_color=col,
line_width=lw,
fill_color=col,
marker_color=col,
marker_style=cu.Marker.get(qgc.QCD_MARKER),
marker_size=mc_msize,
label=mgpy_label + "\n[HERAPDF20_LO_EIG]",
subplot=dijet_fwd_data_hist)
dijet_mgpy_hist3 = qgp.get_projection_plot(
h2d_qcd_fwd_mc_pdf3, start_val, end_val)
entries.append((dijet_mgpy_hist3, qcd_fwd_kwargs_mc3))
dijet_fwd_entries.append(
(dijet_mgpy_hist3, qcd_fwd_kwargs_mc3))
if pt_ind == 0:
dijet_fwd_2d_entries.append(
(h2d_qcd_fwd_mc_pdf3, qcd_fwd_kwargs_mc3))
# Add CT14lo
fname = "uhh2.AnalysisModuleRunner.MC.MC_QCD_CT14lo.root"
if os.path.isfile(os.path.join(root_dir, fname)):
h2d_qcd_fwd_mc_pdf4 = grab_obj(
os.path.join(root_dir, fname),
"%s/%s" % (dj_fwd_dirname, v))
col = qgc.QCD_COLOURS[6]
qcd_fwd_kwargs_mc4 = dict(line_color=col,
line_width=lw,
fill_color=col,
marker_color=col,
marker_style=cu.Marker.get(
qgc.QCD_MARKER),
marker_size=mc_msize,
label=mgpy_label + "\n[CT14lo]",
subplot=dijet_fwd_data_hist)
dijet_mgpy_hist4 = qgp.get_projection_plot(
h2d_qcd_fwd_mc_pdf4, start_val, end_val)
entries.append((dijet_mgpy_hist4, qcd_fwd_kwargs_mc4))
dijet_fwd_entries.append(
(dijet_mgpy_hist4, qcd_fwd_kwargs_mc4))
if pt_ind == 0:
dijet_fwd_2d_entries.append(
(h2d_qcd_fwd_mc_pdf4, qcd_fwd_kwargs_mc4))
# PYTHIA ONLY
# if os.path.isfile(os.path.join(root_dir, qgc.QCD_PYTHIA_ONLY_FILENAME)):
# col = qgc.QCD_COLOURS[2]
# h2d_qcd_fwd_mc2 = grab_obj(os.path.join(root_dir, qgc.QCD_PYTHIA_ONLY_FILENAME), "%s/%s" % (dj_fwd_dirname, v))
# qcd_fwd_kwargs_mc2 = dict(line_color=col, line_width=lw, fill_color=col,
# marker_color=col, marker_style=cu.Marker.get(qgc.QCD_MARKER), marker_size=mc_msize,
# label="Pythia8",
# subplot=dijet_fwd_data_hist)
# entries.append((qgp.get_projection_plot(h2d_qcd_fwd_mc2, start_val, end_val), qcd_fwd_kwargs_mc2))
# dijet_fwd_entries.append((qgp.get_projection_plot(h2d_qcd_fwd_mc2, start_val, end_val), qcd_fwd_kwargs_mc2))
# if pt_ind == 0:
# dijet_fwd_2d_entries.append((h2d_qcd_fwd_mc2, qcd_fwd_kwargs_mc2))
# HERWIG++ QCD
if os.path.isfile(
os.path.join(root_dir, qgc.QCD_HERWIG_FILENAME)):
col_hpp = qgc.QCD_COLOURS[3]
h2d_qcd_fwd_mc_hpp = grab_obj(
os.path.join(root_dir, qgc.QCD_HERWIG_FILENAME),
"%s/%s" % (dj_fwd_dirname, v))
qcd_fwd_kwargs_mc_hpp = dict(line_color=col_hpp,
line_width=lw,
fill_color=col_hpp,
marker_color=col_hpp,
marker_style=cu.Marker.get(
qgc.QCD_MARKER),
marker_size=mc_msize,
label=hpp_label,
subplot=dijet_fwd_data_hist)
dijet_hpp_hist = qgp.get_projection_plot(
h2d_qcd_fwd_mc_hpp, start_val, end_val)
entries.append((dijet_hpp_hist, qcd_fwd_kwargs_mc_hpp))
dijet_fwd_entries.append(
(dijet_hpp_hist, qcd_fwd_kwargs_mc_hpp))
if pt_ind == 0:
dijet_fwd_2d_entries.append(
(h2d_qcd_fwd_mc_hpp, qcd_fwd_kwargs_mc_hpp))
zpj_1d_entries.append(zpj_entries)
dijet_cen_1d_entries.append(dijet_cen_entries)
dijet_fwd_1d_entries.append(dijet_fwd_entries)
#################
# SETUP PLOTTING
#################
rebin = 2
v_lower = v.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_lambda_mc_vs_data%s_pdf_compare" % (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"
"{bin_edge_low:g} < {pt_str} < {bin_edge_high:g} GeV"
).format(jet_algo=jet_str,
region_label=region_str,
pt_str=pt_var_str,
bin_edge_low=start_val,
bin_edge_high=end_val))
if title is not None:
s = "%s\n%s" % (s, title)
return s
has_data = True
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, v, 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=qgp.calc_auto_xlim([
d[0] for d in dijet_cen_entries
]) if auto_xlim else xlim,
ylim=ylim,
data_first=has_data,
mean_rel_error=0.4,
subplot_type='ratio',
subplot_title=subplot_title,
subplot_limits=subplot_limits)
# 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, v, 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=qgp.calc_auto_xlim([
d[0] for d in dijet_fwd_entries
]) if auto_xlim else xlim,
ylim=ylim,
data_first=has_data,
mean_rel_error=0.4,
subplot_type='ratio',
subplot_title=subplot_title,
subplot_limits=subplot_limits)
# 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, v, 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='ratio',
subplot_title=subplot_title,
subplot_limits=subplot_limits)
# Do overall summary plots across all pt bins
# ------------------------------------------------------------------
ylim_mean = None
if "width" in v_lower or "ptd" in v_lower:
ylim_mean = (0, 0.4)
elif "thrust" in v_lower:
ylim_mean = (0, 0.5)
elif "multiplicity" in v_lower and "ak4" in root_dir.lower():
ylim_mean = (0, 100)
ylim_mean = (0, 80)
if end_val < 150:
ylim_mean = (0, 50)
ylim_mean = None
ylim_rms = None
# Setup variable names for MPL
marker = ""
if "_" in ang.name or "^" in ang.name:
marker = "$"
var_label = marker + ang.name + marker + " ($%s$)" % ang.lambda_str
if gr_append != "":
var_label = "Groomed " + marker + ang.name + marker + " ($%s$)" % ang.lambda_str
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_1D_plot(hists,
components_styles_dicts,
output_filename,
do_ratio=True,
logx=False,
logy=False,
normalise_hists=True,
title="",
xtitle=None,
mean_rel_error=0.4,
data_first=True,
show_integrals=False,
lumi=cu.get_lumi_str(do_dijet=False, do_zpj=True)):
if (len(hists) != len(components_styles_dicts)):
raise RuntimeError("# hists != # components_styles_dicts (%d vs %d)" %
(len(hists), len(components_styles_dicts)))
if len(hists) == 0:
return
# Ignore if all empty objs
total_entries = sum(h.GetEntries() for h in hists)
if total_entries == 0:
print("WARNING: all plots have 0 entries")
return
do_ratio = (do_ratio and len(hists) > 1)
entries = []
components_styles_dicts = deepcopy(components_styles_dicts)
for h, csd in zip(hists, components_styles_dicts):
if show_integrals:
csd['label'] += "\nIntegral = {:.4g}".format(h.Integral())
entries.append((h.Clone(cu.get_unique_str()), csd))
# print("Auto y limits:", min_val, max_val)
ylim = None
# if not normalise_hists:
# min_val, min_bin, max_val, max_bin = cu.get_min_max_bin_contents_multiple_hists(hists)
# if logy:
# ylim = [0.5*min_val, 50*max_val]
# else:
# # ylim = [0.5*min_val, 1.5*max_val]
# ylim = [0, 1.5*max_val]
xlim = "auto" # Auto calc x limits to avoid lots of empty bins
draw_opt = "NOSTACK HIST E1"
subplot_title = "Simulation / Data"
subplot_limits = (0, 2) if logy else (0.5, 1.5)
# subplot_limits = [0.5, None]
subplot_limits = None
qgp.do_comparison_plot(
entries,
output_filename,
# rebin=rebin,
normalise_hist=normalise_hists,
draw_opt=draw_opt,
title=title,
xtitle=xtitle,
xlim=xlim,
ylim=ylim,
logx=logx,
logy=logy,
mean_rel_error=mean_rel_error,
data_first=data_first,
subplot_type='ratio' if do_ratio else None,
subplot_title=subplot_title,
subplot=entries[0][0] if do_ratio else None,
subplot_limits=subplot_limits,
lumi=lumi)
subplot_title = "Nominal / No SF"
subplot_limits = (0.5, 1.5)
xlabel = ang.name + " (" + ang.lambda_str + ")"
if gr_append is not "":
xlabel = "Groomed " + ang.name + " (" + ang.lambda_str + ")"
# dj central only
qgp.do_comparison_plot(
dijet_cen_no_vs_nominal_sf_entries,
"%s/ptBinned/%s_pt%dto%d_dijet_central.%s" %
(plot_dir, v, start_val, end_val, OUTPUT_FMT),
rebin=rebin,
title="%d < p_{T}^{jet} < %d GeV\n%s\n%s" %
(start_val, end_val, jet_str, qgc.Dijet_CEN_LABEL),
xtitle=xlabel,
xlim=xlim,
ylim=ylim,
has_data=False,
subplot_type='ratio',
subplot_title=subplot_title,
subplot_limits=subplot_limits)
# dj forward only
qgp.do_comparison_plot(
dijet_fwd_no_vs_nominal_sf_entries,
"%s/ptBinned/%s_pt%dto%d_dijet_forward.%s" %
(plot_dir, v, start_val, end_val, OUTPUT_FMT),
rebin=rebin,
title="%d < p_{T}^{jet} < %d GeV\n%s\n%s" %
(start_val, end_val, jet_str, qgc.Dijet_FWD_LABEL),
def do_wrong_plots(root_dir,
var_prepend="",
plot_dir="wrong_flavs",
zpj_dirname="ZPlusJets_QG",
dj_dirname="Dijet_QG",
pt_bins=None,
title=""):
"""Plot all the sample/selection/flavour combinations to check distributions indep of sample"""
pt_bins = pt_bins or qgc.THEORY_PT_BINS
plot_vars = [
'jet_LHA', 'jet_pTD', 'jet_width', 'jet_thrust', 'jet_multiplicity'
]
if "puppi" in root_dir.lower():
plot_vars.append('jet_puppiMultiplicity')
for v in plot_vars:
v = "%s%s_vs_pt" % (var_prepend, v)
h2d_dyj_chs = grab_obj(os.path.join(root_dir, qgc.DY_FILENAME),
"%s/q%s" % (zpj_dirname, v))
h2d_dyj_wrong_chs = grab_obj(os.path.join(root_dir, qgc.DY_FILENAME),
"%s/g%s" % (zpj_dirname, v))
h2d_dyj_qcd_chs = grab_obj(os.path.join(root_dir, qgc.DY_FILENAME),
"%s/q%s" % (dj_dirname, v))
h2d_dyj_qcd_wrong_chs = grab_obj(
os.path.join(root_dir, qgc.DY_FILENAME),
"%s/g%s" % (dj_dirname, v))
h2d_qcd_chs = grab_obj(os.path.join(root_dir, qgc.QCD_FILENAME),
"%s/g%s" % (dj_dirname, v))
h2d_qcd_wrong_chs = grab_obj(os.path.join(root_dir, qgc.QCD_FILENAME),
"%s/q%s" % (dj_dirname, v))
lw = 1
dy_kwargs_chs = dict(line_color=qgc.DY_COLOUR,
fill_color=qgc.DY_COLOUR,
label=qgc.DY_ZpJ_QFLAV_LABEL,
line_width=lw,
marker_style=20,
marker_color=qgc.DY_COLOUR)
dy_kwargs_wrong_chs = dict(line_color=qgc.DY_COLOUR + 4,
fill_color=qgc.DY_COLOUR + 4,
label=qgc.DY_ZpJ_GFLAV_LABEL,
line_width=lw,
line_style=1,
marker_style=21,
marker_color=qgc.DY_COLOUR + 4)
dy_kwargs_qcd_chs = dict(line_color=ROOT.kGreen + 2,
fill_color=ROOT.kGreen + 2,
label=qgc.DY_Dijet_QFLAV_LABEL,
line_width=lw,
line_style=1,
marker_style=22,
marker_color=ROOT.kGreen + 2)
dy_kwargs_qcd_wrong_chs = dict(line_color=ROOT.kOrange - 1,
fill_color=ROOT.kOrange - 1,
label=qgc.DY_Dijet_GFLAV_LABEL,
line_width=lw,
line_style=1,
marker_style=23,
marker_color=ROOT.kOrange - 1)
qcd_kwargs_chs = dict(line_color=qgc.QCD_COLOUR,
fill_color=qgc.QCD_COLOUR,
label=qgc.QCD_Dijet_GFLAV_LABEL,
line_width=lw,
marker_style=25,
marker_color=qgc.QCD_COLOUR)
qcd_kwargs_wrong_chs = dict(line_color=ROOT.kRed,
fill_color=ROOT.kRed,
label=qgc.QCD_Dijet_QFLAV_LABEL,
line_width=lw,
line_style=1,
marker_style=24,
marker_color=ROOT.kRed)
rebin = 2
xlim = None
if "thrust" in v:
rebin = 1
xlim = (0, 0.5)
if "multiplicity" in v.lower():
rebin = 2
xlim = (0, 100)
for (start_val, end_val) in pt_bins:
entries = [
(qgg.get_projection_plot(h2d_dyj_chs, start_val,
end_val), dy_kwargs_chs),
(qgg.get_projection_plot(h2d_dyj_wrong_chs, start_val,
end_val), dy_kwargs_wrong_chs),
# (qgg.get_projection_plot(h2d_dyj_qcd_chs, start_val, end_val), dy_kwargs_qcd_chs),
# (qgg.get_projection_plot(h2d_dyj_qcd_wrong_chs, start_val, end_val), dy_kwargs_qcd_wrong_chs),
(qgg.get_projection_plot(h2d_qcd_wrong_chs, start_val,
end_val), qcd_kwargs_wrong_chs),
(qgg.get_projection_plot(h2d_qcd_chs, start_val,
end_val), qcd_kwargs_chs),
]
this_title = "%d < p_{T}^{jet} < %d GeV" % (start_val, end_val)
if title != "":
this_title += ", %s" % title
qgg.do_comparison_plot(
entries,
"%s/%s/%s_pt%dto%d_flavMatched.%s" %
(root_dir, plot_dir, v, start_val, end_val, OUTPUT_FMT),
rebin=rebin,
title=this_title,
xlim=xlim)
def do_plots(root_dir, title):
# QG variable plots
pt_bins = qgc.PT_BINS[:]
print(pt_bins)
var_list = qgc.COMMON_VARS
var_prepend = ""
radius, pus = cu.get_jet_config_from_dirname(root_dir)
jet_str = "AK%s PF %s" % (radius.upper(), pus.upper())
if radius == "8":
pt_bins = qgc.PT_BINS[2:]
print(pt_bins)
single_mu_tfile = cu.TFileCacher(os.path.join(root_dir, qgc.SINGLE_MU_FILENAME))
dy_tfile = cu.TFileCacher(os.path.join(root_dir, qgc.DY_FILENAME))
dy_hpp_tfile = cu.TFileCacher(os.path.join(root_dir, qgc.DY_HERWIG_FILENAME))
jetht_zb_tfile = cu.TFileCacher(os.path.join(root_dir, qgc.JETHT_ZB_FILENAME))
qcd_tfile = cu.TFileCacher(os.path.join(root_dir, qgc.QCD_FILENAME))
qcd_hpp_tfile = cu.TFileCacher(os.path.join(root_dir, qgc.QCD_HERWIG_FILENAME))
for gr_append in ["", "_groomed"]:
if gr_append == "_groomed":
print("Doing groomed plots...")
else:
print("Doing ungroomed plots...")
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)
for ang in var_list[:]:
print("...Doing", ang.name)
v = "%s%s_vs_pt" % (var_prepend, ang.var)
zpj_2d_entries = []
dijet_cen_2d_entries = []
dijet_fwd_2d_entries = []
zpj_1d_entries = []
dijet_cen_1d_entries = []
dijet_fwd_1d_entries = []
for pt_ind, (start_val, end_val) in enumerate(pt_bins):
entries = []
zpj_entries = []
dijet_cen_entries = []
dijet_fwd_entries = []
# Get all plots
lw = 2
msize = 1.1
data_line_width = lw
mc_msize = 1E-3 # small enough to not be seen but not 0 - otherwise the horizontal lines on error bars don't get drawn
mgpy_label = "MG5+Pythia8"
hpp_label = "Herwig++"
####################
# Z+JETS REGION
####################
# SINGLE MU DATA
if single_mu_tfile:
h2d_dyj_data = single_mu_tfile.get("%s/%s" % (zpj_dirname, v))
dy_kwargs_data = dict(line_color=qgc.SINGLE_MU_COLOUR, line_width=data_line_width, fill_color=qgc.SINGLE_MU_COLOUR,
marker_color=qgc.SINGLE_MU_COLOUR, marker_style=cu.Marker.get(qgc.DY_MARKER), marker_size=msize*0.7,
label="Data")
zpj_data_hist = qgp.get_projection_plot(h2d_dyj_data, start_val, end_val)
entries.append((zpj_data_hist, dy_kwargs_data))
zpj_entries.append((zpj_data_hist, dy_kwargs_data))
if pt_ind == 0:
zpj_2d_entries.append((h2d_dyj_data, dy_kwargs_data))
# PYTHIA DY MC
if dy_tfile:
h2d_dyj_mc = dy_tfile.get("%s/%s" % (zpj_dirname, v))
dy_kwargs_mc = dict(line_color=qgc.DY_COLOUR, line_width=lw, fill_color=qgc.DY_COLOUR,
marker_color=qgc.DY_COLOUR, marker_style=cu.Marker.get(qgc.DY_MARKER), marker_size=mc_msize,
label=mgpy_label,
subplot=zpj_data_hist)
entries.append((qgp.get_projection_plot(h2d_dyj_mc, start_val, end_val), dy_kwargs_mc))
zpj_entries.append((qgp.get_projection_plot(h2d_dyj_mc, start_val, end_val), dy_kwargs_mc))
if pt_ind == 0:
zpj_2d_entries.append((h2d_dyj_mc, dy_kwargs_mc))
# HERWIG++ DY
if dy_hpp_tfile:
h2d_dyj_mc_hpp = dy_hpp_tfile.get("%s/%s" % (zpj_dirname, v))
col_hpp = qgc.DY_COLOURS[2]
dy_kwargs_mc_hpp = dict(line_color=col_hpp, line_width=lw, fill_color=col_hpp,
marker_color=col_hpp, marker_style=cu.Marker.get(qgc.DY_MARKER), marker_size=mc_msize,
label=hpp_label,
subplot=zpj_data_hist)
entries.append((qgp.get_projection_plot(h2d_dyj_mc_hpp, start_val, end_val), dy_kwargs_mc_hpp))
zpj_entries.append((qgp.get_projection_plot(h2d_dyj_mc_hpp, start_val, end_val), dy_kwargs_mc_hpp))
if pt_ind == 0:
zpj_2d_entries.append((h2d_dyj_mc_hpp, dy_kwargs_mc_hpp))
# MG+HERWIG++ DY
# if end_val < 151:
# h2d_dyj_mc3 = get("%s/%s" % (zpj_dirname, v))
# col4 = qgc.DY_COLOURS[3]
# dy_kwargs_mc3 = dict(line_color=col4, line_width=lw, fill_color=col4,
# marker_color=col4, marker_style=cu.Marker.get(qgc.DY_MARKER), marker_size=0,
# label="MG+Herwig++",
# subplot=zpj_data_hist)
# entries.append((qgp.get_projection_plot(h2d_dyj_mc3, start_val, end_val), dy_kwargs_mc3))
# zpj_entries.append((qgp.get_projection_plot(h2d_dyj_mc3, start_val, end_val), dy_kwargs_mc3))
# if pt_ind == 0:
# zpj_2d_entries.append((h2d_dyj_mc3, dy_kwargs_mc3))
# else:
# zpj_entries.append(None)
####################
# DIJET CENTRAL REGION
####################
# JETHT/ZEROBIAS DATA
if jetht_zb_tfile:
h2d_qcd_cen_data = jetht_zb_tfile.get("%s/%s" % (dj_cen_dirname, v)) # use already merged jetht+zb
qcd_cen_kwargs_data = dict(line_color=qgc.JETHT_COLOUR, line_width=data_line_width, fill_color=qgc.JETHT_COLOUR,
marker_color=qgc.JETHT_COLOUR, marker_style=cu.Marker.get(qgc.QCD_MARKER), marker_size=msize,
label="Data")
dijet_cen_data_hist = qgp.get_projection_plot(h2d_qcd_cen_data, start_val, end_val)
entries.append((dijet_cen_data_hist, qcd_cen_kwargs_data))
dijet_cen_entries.append((dijet_cen_data_hist, qcd_cen_kwargs_data))
if pt_ind == 0:
dijet_cen_2d_entries.append((h2d_qcd_cen_data, qcd_cen_kwargs_data))
# MG+PYTHIA QCD MC
if qcd_tfile:
h2d_qcd_cen_mc = qcd_tfile.get("%s/%s" % (dj_cen_dirname, v))
qcd_cen_kwargs_mc = dict(line_color=qgc.QCD_COLOUR, line_width=lw, fill_color=qgc.QCD_COLOUR,
marker_color=qgc.QCD_COLOUR, marker_style=cu.Marker.get(qgc.QCD_MARKER), marker_size=mc_msize,
label=mgpy_label,
subplot=dijet_cen_data_hist)
dijet_mgpy_hist = qgp.get_projection_plot(h2d_qcd_cen_mc, start_val, end_val)
entries.append((dijet_mgpy_hist, qcd_cen_kwargs_mc))
dijet_cen_entries.append((dijet_mgpy_hist, qcd_cen_kwargs_mc))
if pt_ind == 0:
dijet_cen_2d_entries.append((h2d_qcd_cen_mc, qcd_cen_kwargs_mc))
# PYTHIA ONLY
# if qcd_py_tfile:
# col = qgc.QCD_COLOURS[2]
# h2d_qcd_cen_mc2 = qcd_py_tfile.get("%s/%s" % (dj_cen_dirname, v))
# qcd_cen_kwargs_mc2 = dict(line_color=col, line_width=lw, fill_color=col,
# marker_color=col, marker_style=cu.Marker.get(qgc.QCD_MARKER), marker_size=mc_msize,
# label="Pythia8",
# subplot=dijet_cen_data_hist)
# entries.append((qgp.get_projection_plot(h2d_qcd_cen_mc2, start_val, end_val), qcd_cen_kwargs_mc2))
# dijet_cen_entries.append((qgp.get_projection_plot(h2d_qcd_cen_mc2, start_val, end_val), qcd_cen_kwargs_mc2))
# if pt_ind == 0:
# dijet_cen_2d_entries.append((h2d_qcd_cen_mc2, qcd_cen_kwargs_mc2))
# HERWIG++ QCD
if qcd_hpp_tfile:
h2d_qcd_cen_mc_hpp = qcd_hpp_tfile.get("%s/%s" % (dj_cen_dirname, v))
qcd_cen_kwargs_mc_hpp = dict(line_color=qgc.HERWIGPP_QCD_COLOUR, line_width=lw, fill_color=qgc.HERWIGPP_QCD_COLOUR,
marker_color=qgc.HERWIGPP_QCD_COLOUR, marker_style=cu.Marker.get(qgc.QCD_MARKER), marker_size=mc_msize,
label=hpp_label,
subplot=dijet_cen_data_hist)
dijet_hpp_hist = qgp.get_projection_plot(h2d_qcd_cen_mc_hpp, start_val, end_val)
entries.append((dijet_hpp_hist, qcd_cen_kwargs_mc_hpp))
dijet_cen_entries.append((dijet_hpp_hist, qcd_cen_kwargs_mc_hpp))
if pt_ind == 0:
dijet_cen_2d_entries.append((h2d_qcd_cen_mc_hpp, qcd_cen_kwargs_mc_hpp))
####################
# DIJET FORWARD REGION
####################
# JETHT/ZEROBIAS DATA
if jetht_zb_tfile:
h2d_qcd_fwd_data = jetht_zb_tfile.get("%s/%s" % (dj_fwd_dirname, v)) # use already merged jetht+zb
qcd_fwd_kwargs_data = dict(line_color=qgc.JETHT_COLOUR, line_width=data_line_width, fill_color=qgc.JETHT_COLOUR,
marker_color=qgc.JETHT_COLOUR, marker_style=cu.Marker.get('triangleDown'), marker_size=msize,
label="Data")
dijet_fwd_data_hist = qgp.get_projection_plot(h2d_qcd_fwd_data, start_val, end_val)
entries.append((dijet_fwd_data_hist, qcd_fwd_kwargs_data))
dijet_fwd_entries.append((dijet_fwd_data_hist, qcd_fwd_kwargs_data))
if pt_ind == 0:
dijet_fwd_2d_entries.append((h2d_qcd_fwd_data, qcd_fwd_kwargs_data))
# MG+PYTHIA QCD MC
if qcd_tfile:
h2d_qcd_fwd_mc = qcd_tfile.get("%s/%s" % (dj_fwd_dirname, v))
qcd_fwd_kwargs_mc = dict(line_color=qgc.QCD_COLOUR, line_width=lw, fill_color=qgc.QCD_COLOUR,
marker_color=qgc.QCD_COLOUR, marker_style=cu.Marker.get(qgc.QCD_MARKER), marker_size=mc_msize,
label=mgpy_label,
subplot=dijet_fwd_data_hist)
dijet_mgpy_hist = qgp.get_projection_plot(h2d_qcd_fwd_mc, start_val, end_val)
entries.append((dijet_mgpy_hist, qcd_fwd_kwargs_mc))
dijet_fwd_entries.append((dijet_mgpy_hist, qcd_fwd_kwargs_mc))
if pt_ind == 0:
dijet_fwd_2d_entries.append((h2d_qcd_fwd_mc, qcd_fwd_kwargs_mc))
# PYTHIA ONLY
# if qcd_py_tfile:
# col = qgc.QCD_COLOURS[2]
# h2d_qcd_fwd_mc2 = qcd_py_tfile.get("%s/%s" % (dj_fwd_dirname, v))
# qcd_fwd_kwargs_mc2 = dict(line_color=col, line_width=lw, fill_color=col,
# marker_color=col, marker_style=cu.Marker.get(qgc.QCD_MARKER), marker_size=mc_msize,
# label="Pythia8",
# subplot=dijet_fwd_data_hist)
# entries.append((qgp.get_projection_plot(h2d_qcd_fwd_mc2, start_val, end_val), qcd_fwd_kwargs_mc2))
# dijet_fwd_entries.append((qgp.get_projection_plot(h2d_qcd_fwd_mc2, start_val, end_val), qcd_fwd_kwargs_mc2))
# if pt_ind == 0:
# dijet_fwd_2d_entries.append((h2d_qcd_fwd_mc2, qcd_fwd_kwargs_mc2))
# HERWIG++ QCD
if qcd_hpp_tfile:
h2d_qcd_fwd_mc_hpp = qcd_hpp_tfile.get("%s/%s" % (dj_fwd_dirname, v))
qcd_fwd_kwargs_mc_hpp = dict(line_color=qgc.HERWIGPP_QCD_COLOUR, line_width=lw, fill_color=qgc.HERWIGPP_QCD_COLOUR,
marker_color=qgc.HERWIGPP_QCD_COLOUR, marker_style=cu.Marker.get(qgc.QCD_MARKER), marker_size=mc_msize,
label=hpp_label,
subplot=dijet_fwd_data_hist)
dijet_hpp_hist = qgp.get_projection_plot(h2d_qcd_fwd_mc_hpp, start_val, end_val)
entries.append((dijet_hpp_hist, qcd_fwd_kwargs_mc_hpp))
dijet_fwd_entries.append((dijet_hpp_hist, qcd_fwd_kwargs_mc_hpp))
if pt_ind == 0:
dijet_fwd_2d_entries.append((h2d_qcd_fwd_mc_hpp, qcd_fwd_kwargs_mc_hpp))
zpj_1d_entries.append(zpj_entries)
dijet_cen_1d_entries.append(dijet_cen_entries)
dijet_fwd_1d_entries.append(dijet_fwd_entries)
#################
# SETUP PLOTTING
#################
rebin = 2
v_lower = v.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_lambda_mc_vs_data%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"
"{bin_edge_low:g} < {pt_str} < {bin_edge_high:g} GeV")
.format(
jet_algo=jet_str,
region_label=region_str,
pt_str=pt_var_str,
bin_edge_low=start_val,
bin_edge_high=end_val))
if title is not None:
s = "%s\n%s" % (s, title)
return s
has_data = True
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, v, 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='ratio',
subplot_title=subplot_title,
subplot_limits=subplot_limits,
lumi=cu.get_lumi_str(do_dijet=True, do_zpj=False))
# 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, v, 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='ratio',
subplot_title=subplot_title,
subplot_limits=subplot_limits,
lumi=cu.get_lumi_str(do_dijet=True, do_zpj=False))
# 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, v, 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='ratio',
subplot_title=subplot_title,
subplot_limits=subplot_limits,
lumi=cu.get_lumi_str(do_dijet=False, do_zpj=True))
# Do overall summary plots across all pt bins
# ------------------------------------------------------------------
ylim_mean = None
if "width" in v_lower or "ptd" in v_lower:
ylim_mean = (0, 0.4)
elif"thrust" in v_lower:
ylim_mean = (0, 0.5)
elif "multiplicity" in v_lower and "ak4" in root_dir.lower():
ylim_mean = (0, 100)
ylim_mean = (0, 80)
if end_val < 150:
ylim_mean = (0, 50)
ylim_mean=None
ylim_rms=None
# Setup variable names for MPL
marker = ""
if "_" in ang.name or "^" in ang.name:
marker = "$"
var_label = marker + ang.name + marker + " ($%s$)" % ang.lambda_str
if gr_append != "":
var_label = "Groomed " + marker + ang.name + marker + " ($%s$)" % ang.lambda_str
# construct a dataframe from the hists
# df = construct_dataframe_from_hists(dijet_cen_entries=dijet_cen_1d_entries,
# dijet_fwd_entries=dijet_fwd_entries,
# zpj_entries=zpj_entries)
# pt_low = 88 if "8" in radius else 50
pt_low = pt_bins[0][0]
qgp.do_mean_rms_summary_plot(dijet_cen_1d_entries,
pt_bins,
"%s/ptBinned/%s_box_dijet_cen_mpl.%s" % (plot_dir, v, OUTPUT_FMT),
var_label=var_label,
xlim=(pt_low, 4000),
ylim_mean=ylim_mean,
ylim_rms=ylim_rms,
region_title="%s jets in %s" % (jet_str, qgc.Dijet_CEN_LABEL.lower()))
qgp.do_mean_rms_summary_plot(dijet_fwd_1d_entries,
pt_bins,
"%s/ptBinned/%s_box_dijet_fwd_mpl.%s" % (plot_dir, v, OUTPUT_FMT),
var_label=var_label,
xlim=(pt_low, 4000),
ylim_mean=ylim_mean,
ylim_rms=ylim_rms,
region_title="%s jets in %s" % (jet_str, qgc.Dijet_FWD_LABEL.lower()))
# zpj_1d_entries[i][j] is the jth sample in the ith pt bin
qgp.do_mean_rms_summary_plot(zpj_1d_entries,
pt_bins,
"%s/ptBinned/%s_box_zpj_mpl.%s" % (plot_dir, v, OUTPUT_FMT),
var_label=var_label,
xlim=(pt_low, 800),
ylim_mean=ylim_mean,
ylim_rms=ylim_rms,
region_title="%s jets in %s" % (jet_str, qgc.ZpJ_LABEL))
def do_plots(root_dir):
# QG variable plots
pt_bins = qgc.PT_BINS[:]
var_list = qgc.COMMON_VARS
var_prepend = ""
radius, pus = cu.get_jet_config_from_dirname(root_dir)
jet_str = "AK%s PF %s" % (radius.upper(), pus.upper())
for gr_append in ["", "_groomed"]:
if gr_append == "_groomed":
print("Doing groomed plots...")
else:
print("Doing ungroomed plots...")
# do a pt plot just for sanity
if gr_append == "":
make_1d_plot(root_dir, "ZPlusJets_gen/pt_jet1", jet_str, gen_only=True)
make_1d_plot(root_dir, "ZPlusJets_gen/pt_mumu", jet_str, gen_only=True)
make_1d_plot(root_dir, "ZPlusJets/pt_jet1", jet_str)
make_1d_plot(root_dir, "ZPlusJets/pt_mumu", jet_str)
continue
zpj_dirname = "ZPlusJets_QG%s" % (gr_append)
for ang in var_list[:]:
print("...Doing", ang.name)
v = "%s%s_vs_pt" % (var_prepend, ang.var)
zpj_2d_entries = []
zpj_1d_entries = []
for pt_ind, (start_val, end_val) in enumerate(pt_bins):
entries = []
zpj_entries = []
# Get all plots
lw = 2
msize = 1.1
data_line_width = 0
####################
# Z+JETS REGION
####################
# SINGLE MU DATA
h2d_dyj_data = grab_obj(os.path.join(root_dir, qgc.SINGLE_MU_FILENAME), "%s/%s" % (zpj_dirname, v))
dy_kwargs_data = dict(line_color=qgc.SINGLE_MU_COLOUR, line_width=data_line_width, fill_color=qgc.SINGLE_MU_COLOUR,
marker_color=qgc.SINGLE_MU_COLOUR, marker_style=cu.Marker.get(qgc.DY_MARKER), marker_size=msize,
label="Data")
zpj_data_hist = qgp.get_projection_plot(h2d_dyj_data, start_val, end_val)
entries.append((zpj_data_hist, dy_kwargs_data))
zpj_entries.append((zpj_data_hist, dy_kwargs_data))
if pt_ind == 0:
zpj_2d_entries.append((h2d_dyj_data, dy_kwargs_data))
# PYTHIA DY MC WITH k FACTORS
h2d_dyj_mc = grab_obj(os.path.join(root_dir, qgc.DY_FILENAME), "%s/%s" % (zpj_dirname, v))
dy_kwargs_mc = dict(line_color=qgc.DY_COLOUR, line_width=lw, fill_color=qgc.DY_COLOUR,
marker_color=qgc.DY_COLOUR, marker_style=cu.Marker.get(qgc.DY_MARKER), marker_size=0,
label="MG+PY8 (w/ k-factor)",
subplot=zpj_data_hist)
entries.append((qgp.get_projection_plot(h2d_dyj_mc, start_val, end_val), dy_kwargs_mc))
zpj_entries.append((qgp.get_projection_plot(h2d_dyj_mc, start_val, end_val), dy_kwargs_mc))
if pt_ind == 0:
zpj_2d_entries.append((h2d_dyj_mc, dy_kwargs_mc))
# WIHTOUT K FACTORS
h2d_dyj_mc_noWeight = grab_obj(os.path.join(root_dir, "uhh2.AnalysisModuleRunner.MC.MC_DYJetsToLL_noZReweight.root"), "%s/%s" % (zpj_dirname, v))
dy_kwargs_mc_noWeight = dict(line_color=qgc.DY_COLOURS[0], line_width=lw, fill_color=qgc.DY_COLOURS[0], line_style=2,
marker_color=qgc.DY_COLOURS[0], marker_style=cu.Marker.get(qgc.DY_MARKER), marker_size=0,
label="MG+PY8 (w/out k-factor)",
subplot=zpj_data_hist)
entries.append((qgp.get_projection_plot(h2d_dyj_mc_noWeight, start_val, end_val), dy_kwargs_mc_noWeight))
zpj_entries.append((qgp.get_projection_plot(h2d_dyj_mc_noWeight, start_val, end_val), dy_kwargs_mc_noWeight))
if pt_ind == 0:
zpj_2d_entries.append((h2d_dyj_mc_noWeight, dy_kwargs_mc_noWeight))
# HERWIG++ DY
# if end_val < 255:
# h2d_dyj_mc2 = grab_obj(os.path.join(root_dir, qgc.DY_HERWIG_FILENAME), "%s/%s" % (zpj_dirname, v))
# col3 = qgc.DY_COLOURS[2]
# dy_kwargs_mc2 = dict(line_color=col3, line_width=lw, fill_color=col3,
# marker_color=col3, marker_style=cu.Marker.get(qgc.DY_MARKER), marker_size=0,
# label="H++",
# subplot=zpj_data_hist)
# entries.append((qgp.get_projection_plot(h2d_dyj_mc2, start_val, end_val), dy_kwargs_mc2))
# zpj_entries.append((qgp.get_projection_plot(h2d_dyj_mc2, start_val, end_val), dy_kwargs_mc2))
# if pt_ind == 0:
# zpj_2d_entries.append((h2d_dyj_mc2, dy_kwargs_mc2))
# else:
# zpj_entries.append(None)
# MG+HERWIG++ DY
# if end_val < 151:
# h2d_dyj_mc3 = grab_obj(os.path.join(root_dir, qgc.DY_MG_HERWIG_FILENAME), "%s/%s" % (zpj_dirname, v))
# col4 = qgc.DY_COLOURS[3]
# dy_kwargs_mc3 = dict(line_color=col4, line_width=lw, fill_color=col4,
# marker_color=col4, marker_style=cu.Marker.get(qgc.DY_MARKER), marker_size=0,
# label="MG+H++",
# subplot=zpj_data_hist)
# entries.append((qgp.get_projection_plot(h2d_dyj_mc3, start_val, end_val), dy_kwargs_mc3))
# zpj_entries.append((qgp.get_projection_plot(h2d_dyj_mc3, start_val, end_val), dy_kwargs_mc3))
# if pt_ind == 0:
# zpj_2d_entries.append((h2d_dyj_mc3, dy_kwargs_mc3))
# else:
# zpj_entries.append(None)
zpj_1d_entries.append(zpj_entries)
#################
# SETUP PLOTTING
#################
rebin = 2
v_lower = v.lower()
if "multiplicity" in v_lower:
rebin = 2
elif "flavour" in v_lower or "thrust" in v_lower:
rebin = 1
elif 'ptd' in v_lower:
rebin = 2
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)
ylim = 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_dy_vs_qcd_mc_vs_data%s_z_reweight" % (gr_append))
subplot_title = "MC / Data"
subplot_limits = (0.5, 1.5)
xlabel = ang.name + " (" + ang.lambda_str + ")"
if gr_append is not "":
xlabel = "Groomed " + ang.name + " (" + ang.lambda_str + ")"
# zpj only
qgp.do_comparison_plot(zpj_entries,
"%s/ptBinned/%s_pt%dto%d_zpj.%s" % (plot_dir, v, start_val, end_val, OUTPUT_FMT),
rebin=rebin,
title="%d < p_{T}^{jet} < %d GeV\n%s\n%s" % (start_val, end_val, jet_str, qgc.ZpJ_LABEL),
xtitle=xlabel,
xlim=xlim,
ylim=ylim,
subplot_type='ratio',
subplot_title=subplot_title,
subplot_limits=subplot_limits)
# Do overall summary plots across all pt bins
# ------------------------------------------------------------------
ylim_mean = None
if "width" in v_lower or "ptd" in v_lower:
ylim_mean = (0, 0.4)
elif"thrust" in v_lower:
ylim_mean = (0, 0.5)
elif "multiplicity" in v_lower and "ak4" in root_dir.lower():
ylim_mean = (0, 100)
ylim_mean = (0, 80)
if end_val < 150:
ylim_mean = (0, 50)
ylim_mean=None
ylim_rms=None
# Setup variable names for MPL
marker = ""
if "_" in ang.name or "^" in ang.name:
marker = "$"
var_label = marker + ang.name + marker + " ($%s$)" % ang.lambda_str
if gr_append != "":
var_label = "Groomed " + marker + ang.name + marker + " ($%s$)" % ang.lambda_str
# zpj_1d_entries[i][j] is the jth sample in the ith pt bin
qgp.do_mean_rms_summary_plot(zpj_1d_entries[:],
pt_bins[:],
"%s/ptBinned/%s_box_zpj_mpl.%s" % (plot_dir, v, OUTPUT_FMT),
var_label=var_label,
xlim=(50, 614),
ylim_mean=ylim_mean,
ylim_rms=ylim_rms,
region_title="%s jets in %s" % (jet_str, qgc.ZpJ_LABEL))
def do_gen_reco_comparison_plots(root_dir,
var_list=None,
gen_var_prepend="gen",
reco_var_prepend="",
plot_dir="plot_reco_gen",
zpj_reco_dirname=qgc.ZPJ_RECOJET_RDIR,
dj_reco_dirname=qgc.DJ_RECOJET_RDIR,
zpj_gen_dirname=qgc.ZPJ_GENJET_RDIR,
dj_gen_dirname=qgc.DJ_GENJET_RDIR,
pt_bins=qgc.THEORY_PT_BINS,
subplot_type=None):
var_list = var_list or qgc.COMMON_VARS
for ang in var_list:
v_reco = "%s%s_vs_pt" % (reco_var_prepend, ang.var)
v_gen = "%s%s_vs_pt" % (gen_var_prepend, ang.var)
h2d_dyj_reco = grab_obj(os.path.join(root_dir, qgc.DY_FILENAME),
"%s/%s" % (zpj_reco_dirname, v_reco))
h2d_qcd_reco = grab_obj(os.path.join(root_dir, qgc.QCD_FILENAME),
"%s/%s" % (dj_reco_dirname, v_reco))
h2d_dyj_gen = grab_obj(os.path.join(root_dir, qgc.DY_FILENAME),
"%s/%s" % (zpj_gen_dirname, v_gen))
h2d_qcd_gen = grab_obj(os.path.join(root_dir, qgc.QCD_FILENAME),
"%s/%s" % (dj_gen_dirname, v_gen))
if "flavour" not in v_reco:
h2d_dyj_reco_q = grab_obj(os.path.join(root_dir, qgc.DY_FILENAME),
"%s/q%s" % (zpj_reco_dirname, v_reco))
h2d_qcd_reco_g = grab_obj(os.path.join(root_dir, qgc.QCD_FILENAME),
"%s/g%s" % (dj_reco_dirname, v_reco))
h2d_dyj_gen_q = grab_obj(os.path.join(root_dir, qgc.DY_FILENAME),
"%s/q%s" % (zpj_gen_dirname, v_gen))
h2d_qcd_gen_g = grab_obj(os.path.join(root_dir, qgc.QCD_FILENAME),
"%s/g%s" % (dj_gen_dirname, v_gen))
for (start_val, end_val) in pt_bins:
lw = 2
dy_reco_kwargs = dict(line_color=qgc.DY_COLOUR,
fill_color=qgc.DY_COLOUR,
label=qgc.DY_ZpJ_LABEL + " [RecoJet]",
line_width=lw)
qcd_reco_kwargs = dict(line_color=qgc.QCD_COLOUR,
fill_color=qgc.QCD_COLOUR,
label=qgc.QCD_Dijet_LABEL + " [RecoJet]",
line_width=lw)
dy_gen_kwargs = dict(line_color=qgc.DY_COLOUR,
fill_color=qgc.DY_COLOUR,
label=qgc.DY_ZpJ_LABEL + " [GenJet]",
line_width=lw,
line_style=2)
qcd_gen_kwargs = dict(line_color=qgc.QCD_COLOUR,
fill_color=qgc.QCD_COLOUR,
label=qgc.QCD_Dijet_LABEL + " [GenJet]",
line_width=lw,
line_style=2)
entries = [(qgg.get_projection_plot(h2d_dyj_reco, start_val,
end_val), dy_reco_kwargs),
(qgg.get_projection_plot(h2d_qcd_reco, start_val,
end_val), qcd_reco_kwargs),
(qgg.get_projection_plot(h2d_dyj_gen, start_val,
end_val), dy_gen_kwargs),
(qgg.get_projection_plot(h2d_qcd_gen, start_val,
end_val), qcd_gen_kwargs)]
rebin = 2
xlim = None
ylim = None
if "flavour" in v_reco:
rebin = 1
ylim = (0, 1)
if "thrust" in v_reco:
xlim = (0, 0.5)
qgg.do_comparison_plot(
entries,
"%s/%s/%s_pt%dto%d.%s" %
(root_dir, plot_dir, ang.var, start_val, end_val, OUTPUT_FMT),
rebin=rebin,
title="%d < p_{T}^{jet} < %d GeV" % (start_val, end_val),
xtitle=ang.name + " (" + ang.lambda_str + ")",
xlim=xlim,
ylim=ylim,
subplot_type=subplot_type)
# Do flavour-tagged comparison
if "flavour" in v_reco:
continue
dy_reco_kwargs['label'] = qgc.DY_ZpJ_QFLAV_LABEL + " [RecoJet]"
qcd_reco_kwargs['label'] = qgc.QCD_Dijet_GFLAV_LABEL + " [RecoJet]"
dy_gen_kwargs['label'] = qgc.DY_ZpJ_QFLAV_LABEL + " [GenJet]"
qcd_gen_kwargs['label'] = qgc.QCD_Dijet_GFLAV_LABEL + " [GenJet]"
entries = [(qgg.get_projection_plot(h2d_dyj_reco_q, start_val,
end_val), dy_reco_kwargs),
(qgg.get_projection_plot(h2d_qcd_reco_g, start_val,
end_val), qcd_reco_kwargs),
(qgg.get_projection_plot(h2d_dyj_gen_q, start_val,
end_val), dy_gen_kwargs),
(qgg.get_projection_plot(h2d_qcd_gen_g, start_val,
end_val), qcd_gen_kwargs)]
qgg.do_comparison_plot(
entries,
"%s/%s/%s_flavMatched_pt%dto%d.%s" %
(root_dir, plot_dir, ang.var, start_val, end_val, OUTPUT_FMT),
rebin=rebin,
title="%d < p_{T}^{jet} < %d GeV" % (start_val, end_val),
xtitle=ang.name + " (" + ang.lambda_str + ")",
xlim=xlim,
ylim=ylim,
subplot_type=subplot_type)