def do_mc_pt_comparison_plot(dirname_label_pairs, output_filename,
qcd_filename, **plot_kwargs):
# qcd_files = [cu.open_root_file(os.path.join(dl[0], qgc.QCD_FILENAME)) for dl in dirname_label_pairs]
qcd_files = [
cu.open_root_file(os.path.join(dl[0], qgc.QCD_PYTHIA_ONLY_FILENAME))
for dl in dirname_label_pairs
]
histname = "Dijet_tighter/pt_jet1"
qcd_hists = [cu.get_from_tfile(qf, histname) for qf in qcd_files]
N = len(dirname_label_pairs)
conts = [
Contribution(qcd_hists[i],
label=lab,
marker_color=cu.get_colour_seq(i, N),
line_color=cu.get_colour_seq(i, N),
line_style=(i % 3) + 1,
line_width=2,
rebin_hist=1,
subplot=qcd_hists[0] if i != 0 else None)
for i, (d, lab) in enumerate(dirname_label_pairs)
]
plot = Plot(conts,
what='hist',
ytitle="N",
subplot_limits=(0.5, 1.5),
subplot_type="ratio",
subplot_title="* / %s" % (dirname_label_pairs[0][1]),
**plot_kwargs)
plot.y_padding_max_log = 500
plot.legend.SetY1(0.7)
plot.plot("NOSTACK HIST E")
plot.set_logx(do_more_labels=False)
plot.set_logy(do_more_labels=False)
plot.save(output_filename)
def do_jet_pt_rel_error_with_var_cuts(histname, cuts, input_filename, output_filename):
ROOT.gStyle.SetPalette(palette_1D)
tf = cu.open_root_file(input_filename)
h3d = cu.get_from_tfile(tf, histname)
if h3d.GetEntries() == 0:
return
pt_hists = []
for cut in cuts:
max_bin = h3d.GetZaxis().FindFixBin(cut)
# print("cut:", cut, "bin:", max_bin)
h = h3d.ProjectionY("pt_var_lt_%g" % cut, 0, -1, 0, max_bin, "e")
h2 = h.Clone()
h2.Rebin(2)
if h.GetEntries() > 0:
h3 = qgp.hist_divide_bin_width(h2)
# convert bin contents to bin error/bin contents
for ibin in range(1, h2.GetNbinsX()+1):
if h3.GetBinContent(ibin) == 0:
continue
h3.SetBinContent(ibin, h3.GetBinError(ibin) / h3.GetBinContent(ibin))
h3.SetBinError(ibin, 0)
pt_hists.append(h3)
line_styles = [1, 2, 3]
n_line_styles = len(line_styles)
conts = [Contribution(h, label=" < %g" % cut,
line_color=cu.get_colour_seq(ind, len(cuts)),
line_style=line_styles[ind % n_line_styles],
line_width=2,
marker_color=cu.get_colour_seq(ind, len(cuts)),
subplot=pt_hists[-1])
for ind, (h, cut) in enumerate(zip(pt_hists, cuts))]
jet_str = pt_genjet_str if "_vs_pt_genjet_vs_" in histname else pt_str
weight_str = "(unweighted)" if "unweighted" in histname else "(weighted)"
ratio_lims = (0.98, 1.02) if "unweighted" in histname else None
plot = Plot(conts, what='hist',
title='%s for cuts on %s %s' % (jet_str, get_var_str(histname), weight_str),
xtitle=None,
ytitle='Relative error',
# xlim=None, ylim=None,
legend=True,
subplot_type='ratio',
subplot_title='* / var < %g' % cuts[-1],
subplot_limits=ratio_lims,
has_data=False)
plot.y_padding_max_log = 200
plot.subplot_maximum_ceil = 2
plot.subplot_maximum_floor = 1.02
plot.subplot_minimum_ceil = 0.98
plot.legend.SetY1(0.7)
plot.legend.SetY2(0.89)
plot.legend.SetX1(0.78)
plot.legend.SetX2(0.88)
plot.plot("NOSTACK HISTE", "NOSTACK HIST")
plot.set_logx(True, do_more_labels=True)
plot.set_logy(True, do_more_labels=False)
plot.save(output_filename)
def do_pthat_comparison_plot(dirname_label_pairs, output_filename,
**plot_kwargs):
qcd_files = [
cu.open_root_file(os.path.join(dl[0], qgc.QCD_PYTHIA_ONLY_FILENAME))
for dl in dirname_label_pairs
]
histname = "Dijet_gen/ptHat"
qcd_hists = [cu.get_from_tfile(qf, histname) for qf in qcd_files]
N = len(dirname_label_pairs)
pthat_rebin = array('d', [
15, 30, 50, 80, 120, 170, 300, 470, 600, 800, 1000, 1400, 1800, 2400,
3200, 5000
])
nbins = len(pthat_rebin) - 1
qcd_hists = [
h.Rebin(nbins, cu.get_unique_str(), pthat_rebin) for h in qcd_hists
]
conts = [
Contribution(qcd_hists[i],
label=lab,
marker_color=cu.get_colour_seq(i, N),
line_color=cu.get_colour_seq(i, N),
line_style=i + 1,
line_width=2,
subplot=qcd_hists[0] if i != 0 else None)
for i, (d, lab) in enumerate(dirname_label_pairs)
]
plot = Plot(conts,
what='hist',
ytitle="N",
subplot_limits=(0.75, 1.25),
subplot_type="ratio",
subplot_title="* / %s" % (dirname_label_pairs[0][1]),
**plot_kwargs)
plot.y_padding_max_log = 500
plot.legend.SetY1(0.7)
plot.plot("NOSTACK HIST E")
plot.set_logx(do_more_labels=False)
plot.set_logy(do_more_labels=False)
plot.save(output_filename)
def do_genht_comparison_plot(dirname_label_pairs, output_filename,
**plot_kwargs):
"""Like do_genht but for multiple samples"""
qcd_files = [
cu.open_root_file(os.path.join(dl[0], qgc.QCD_FILENAME))
for dl in dirname_label_pairs
]
histname = "Dijet_gen/gen_ht"
qcd_hists = [cu.get_from_tfile(qf, histname) for qf in qcd_files]
N = len(dirname_label_pairs)
conts = [
Contribution(qcd_hists[i],
label=lab,
marker_color=cu.get_colour_seq(i, N),
line_color=cu.get_colour_seq(i, N),
line_style=i + 1,
line_width=2,
subplot=qcd_hists[0] if i != 0 else None)
for i, (d, lab) in enumerate(dirname_label_pairs)
]
plot = Plot(
conts,
what='hist',
ytitle="N",
# subplot_limits=(0.75, 1.25),
subplot_type="ratio",
subplot_title="* / %s" % (dirname_label_pairs[0][1]),
ylim=[1E6, None],
**plot_kwargs)
plot.y_padding_max_log = 500
plot.legend.SetY1(0.7)
plot.subplot_maximum_ceil = 5
plot.plot("NOSTACK HIST E")
plot.set_logx(do_more_labels=False)
plot.set_logy(do_more_labels=False)
plot.save(output_filename)
def do_jet_pt_with_var_cuts(histname, cuts, input_filename, output_filename):
ROOT.gStyle.SetPalette(palette_1D)
total = len(cuts) - 1 + .1 # slight offset to not hit the maximum or minimum
# if len(cuts) <= 3:
# ROOT.gStyle.SetPalette(ROOT.kCool)
# num_colours = ROOT.TColor.GetPalette().fN - 1
# print('num_colours:', num_colours)
# for index in range(len(cuts)):
# print(num_colours, index, len(cuts), index / len(cuts), num_colours * index / total)
# print(index, ROOT.TColor.GetColorPalette(int(num_colours * 1. * index / total)))
tf = cu.open_root_file(input_filename)
h3d = cu.get_from_tfile(tf, histname)
if h3d.GetEntries() == 0:
return
pt_hists = []
for cut in cuts:
max_bin = h3d.GetZaxis().FindFixBin(cut)
# print("cut:", cut, "bin:", max_bin)
h = h3d.ProjectionY("pt_var_lt_%g" % cut, 0, -1, 0, max_bin, "e")
h2 = h.Clone()
h2.Rebin(2)
if h.GetEntries() > 0:
h3 = qgp.hist_divide_bin_width(h2)
pt_hists.append(h3)
line_styles = [1, 2, 3]
if len(cuts) <= 3:
line_styles = [1]
n_line_styles = len(line_styles)
ref_ind = 0
conts = [Contribution(h, label=" < %g" % cut,
line_color=cu.get_colour_seq(ind, total),
line_style=line_styles[ind % n_line_styles],
line_width=2,
marker_color=cu.get_colour_seq(ind, total),
subplot=pt_hists[ref_ind] if ind != ref_ind else None)
for ind, (h, cut) in enumerate(zip(pt_hists, cuts))]
jet_str = pt_genjet_str if "_vs_pt_genjet_vs_" in histname else pt_str
weight_str = "(unweighted)" if "unweighted" in histname else "(weighted)"
ratio_lims = (0.5, 2.5)
ratio_lims = (0.5, 1.1)
plot = Plot(conts, what='hist',
title='%s for cuts on %s %s' % (jet_str, get_var_str(histname), weight_str),
xtitle=None,
ytitle='N',
# xlim=None, ylim=None,
legend=True,
subplot_type='ratio',
subplot_title='* / var < %g' % cuts[ref_ind],
subplot_limits=ratio_lims,
has_data=False)
plot.y_padding_max_log = 200
plot.subplot_maximum_ceil = 4
plot.subplot_maximum_floor = 1.02
plot.subplot_minimum_ceil = 0.98
plot.legend.SetY1(0.7)
plot.legend.SetY2(0.89)
plot.legend.SetX1(0.78)
plot.legend.SetX2(0.88)
plot.plot("NOSTACK HISTE", "NOSTACK HIST")
plot.set_logx(True, do_more_labels=True)
plot.set_logy(True, do_more_labels=False)
plot.save(output_filename)
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_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)