def plot_cutflow_hist(hist, output_filename, title='', has_data=False):
"""Plot one cutflow histogram. Normalises so bins are fractions of the first"""
frac_hist = hist.Clone()
first_bin = hist.GetBinContent(1)
for i in range(1, frac_hist.GetNbinsX()+1):
frac_hist.SetBinContent(i, hist.GetBinContent(i) / first_bin)
frac_hist.SetBinError(i, hist.GetBinError(i) / first_bin)
col = ROOT.kBlue
entry = [Contribution(frac_hist, label='',
line_color=col, line_width=2, line_style=1,
marker_color=col, marker_size=0.75, marker_style=cu.Marker.get('circle'),
normalise_hist=False)]
hmax = frac_hist.GetMaximum()
hmin = frac_hist.GetMinimum(0)
hdiff = hmax-hmin
ymin = max(0, hmin - (hdiff*0.1))
ymax = hmax + (hdiff*0.25)
plot = Plot(entry, 'hist',
xtitle='',
ytitle='Fraction',
title=title,
ylim=(ymin, ymax),
legend=False,
has_data=has_data)
plot.default_canvas_size = (800, 600)
plot.plot("NOSTACK HISTE")
plot.save(output_filename)
def draw_folded_hists(hist_mc_folded,
hist_mc_reco,
hist_data_reco,
output_filename,
title=""):
entries = []
if hist_mc_folded:
entries.append(
Contribution(hist_mc_folded,
label="Folded MC [detector-level]",
line_color=ROOT.kGreen + 2,
line_width=1,
marker_color=ROOT.kGreen + 2,
marker_size=0,
normalise_hist=False,
subplot=hist_data_reco), )
if hist_mc_reco:
entries.append(
Contribution(hist_mc_reco,
label="Reco MC [detector-level]",
line_color=ROOT.kAzure + 2,
line_width=1,
line_style=2,
marker_color=ROOT.kAzure + 2,
marker_size=0,
normalise_hist=False,
subplot=hist_data_reco), )
if hist_data_reco:
entries.append(
Contribution(hist_data_reco,
label="Reco Data [detector-level]",
line_color=ROOT.kRed,
line_width=0,
marker_color=ROOT.kRed,
marker_size=0.6,
marker_style=20,
normalise_hist=False), )
plot = Plot(entries,
what='hist',
title=title,
xtitle="Bin number",
ytitle="N",
subplot_type='ratio',
subplot_title='MC/Data',
subplot_limits=(0.25, 1.75))
plot.default_canvas_size = (800, 600)
plot.plot("NOSTACK HISTE")
plot.main_pad.SetLogy(1)
ymax = max(h.GetMaximum()
for h in [hist_mc_folded, hist_mc_reco, hist_data_reco] if h)
plot.container.SetMaximum(ymax * 100)
plot.container.SetMinimum(1)
plot.legend.SetY1NDC(0.77)
plot.legend.SetX2NDC(0.85)
plot.save(output_filename)
def do_pf_fraction_plot(hist_map, pt_bins, output_filename):
"""Plot PF particle type fractioin for matches, binned by GenParticle pT"""
entries = []
for pt_low, pt_high, mark in zip(pt_bins[:-1], pt_bins[1:],
cu.Marker().cycle()):
values = {}
for pf_ind, (pf_name, hist) in hist_map.items():
ax = hist.GetXaxis()
binx1 = ax.FindBin(pt_low)
binx2 = ax.FindBin(pt_high) - 1
if pt_high == ax.GetBinUpEdge(ax.GetLast()):
binx2 = ax.GetLast()
biny1 = 1
biny2 = hist.GetNbinsY()
binz1 = 1
binz2 = hist.GetNbinsZ()
values[pf_ind] = hist.Integral(
binx1, binx2, biny1, biny2, binz1,
binz2) # integral includes the last bin
sum_values = sum(values.values())
fracs = {k: (v / sum_values) for k, v in values.items()}
h = ROOT.TH1D("h_pt_bin_%gto%g" % (pt_low, pt_high), "", len(values),
0, len(values))
ax = h.GetXaxis()
for ind, k in enumerate(sorted(fracs.keys()), 1):
h.SetBinContent(ind, fracs[k])
h.SetBinError(ind, sqrt(values[k]) / sum_values)
ax.SetBinLabel(ind, hist_map[k][0])
c = Contribution(h,
label='%g < GenParticle p_{T} < %g GeV' %
(pt_low, pt_high),
line_width=1,
marker_size=0.75,
marker_style=mark,
normalise_hist=False)
entries.append(c)
ROOT.gStyle.SetPalette(55)
plot = Plot(entries,
'hist',
xtitle='PF particle type',
ytitle='Fraction matched as type',
ylim=(1E-3, 2),
has_data=False)
plot.default_canvas_size = (800, 600)
plot.plot("NOSTACK PMC PLC HISTE")
plot.set_logy(do_more_labels=False)
plot.save(output_filename)
ROOT.gStyle.SetPalette(ROOT.kViridis)
def do_plot(entries, output_file, hist_name=None, xlim=None, ylim=None, rebin=2, is_data=True, is_ak8=False):
components = []
do_unweighted = any(["unweighted" in e.get('hist_name', hist_name) for e in entries])
for ent in entries:
if 'tfile' not in ent:
ent['tfile'] = cu.open_root_file(ent['filename'])
ent['hist'] = cu.get_from_tfile(ent['tfile'], ent.get('hist_name', hist_name))
if not do_unweighted and 'scale' in ent:
ent['hist'].Scale(ent.get('scale', 1))
components.append(
Contribution(ent['hist'],
fill_color=ent['color'],
line_color=ent['color'],
marker_color=ent['color'],
marker_size=0,
line_width=2,
label=ent['label'],
rebin_hist=rebin
)
)
# print stats
print(ent['hist_name'], ent['label'], ent['hist'].Integral())
title = 'AK8 PUPPI' if is_ak8 else 'AK4 PUPPI'
plot = Plot(components,
what='hist',
has_data=is_data,
title=title,
xlim=xlim,
ylim=ylim,
xtitle="p_{T}^{jet 1} [GeV]",
ytitle="Unweighted N" if do_unweighted else 'N')
# plot.y_padding_min_log = 10 if 'unweighted' in hist_name else 10
plot.default_canvas_size = (700, 600)
plot.legend.SetNColumns(2)
plot.legend.SetX1(0.55)
plot.legend.SetY1(0.7)
plot.legend.SetY2(0.88)
plot.plot("HISTE")
plot.set_logx()
plot.set_logy(do_more_labels=False)
plot.save(output_file)
# do non-stacked version
stem, ext = os.path.splitext(output_file)
plot.plot("HISTE NOSTACK")
plot.set_logx()
plot.set_logy(do_more_labels=False)
plot.save(stem+"_nostack" + ext)
def compare_flavour_fraction_hists_vs_pt_from_contribs(
contribs,
flav,
output_filename,
title="",
xtitle="p_{T}^{jet} [GeV]",
**plot_kwargs):
"""Plot a specified flavour fraction vs pT for several sources.
TODO: use this one more often - compare_flavour_fractions_vs_pt() is almost identical but has to deal with npartons
"""
flav_str = FLAV_STR_DICT[flav]
ytitle = "Fraction of %s %ss" % (flav_str.lower(), get_jet_str(''))
p = Plot(contribs,
what='graph',
xtitle=xtitle,
ytitle=ytitle,
title=title,
xlim=(50, 2000),
ylim=(0, 1),
has_data=False,
**plot_kwargs)
p.default_canvas_size = (600, 600)
try:
p.plot("AP")
p.main_pad.SetBottomMargin(0.16)
p.get_modifier().GetXaxis().SetTitleOffset(1.4)
p.get_modifier().GetXaxis().SetTitleSize(.045)
p.legend.SetX1(0.56)
p.legend.SetY1(0.65)
p.legend.SetY2(0.87)
if len(contribs) >= 4:
p.legend.SetY1(0.7)
p.legend.SetX1(0.5)
p.legend.SetNColumns(2)
p.set_logx(do_more_labels=True, do_exponent=False)
p.save(output_filename)
except ZeroContributions:
warnings.warn("No contributions for %s" % output_filename)
def do_flavour_fraction_vs_eta(input_file,
dirname,
eta_bins,
output_filename,
title="",
var_prepend="",
which_jet="both",
append=""):
"""Plot all flavour fractions vs eta for one input file & dirname in the ROOT file"""
info = get_flavour_efficiencies(
input_file,
bins=eta_bins,
hist_name=get_flavour_hist_name(
dirname=dirname,
var_prepend=var_prepend,
which_jet="both", # since no jet/jet1/jet2 in hist name
metric='eta' + append))
leg_draw_opt = "LP"
plot_u = Contribution(info['u'].CreateGraph(),
label="Up",
line_color=ROOT.kRed,
marker_color=ROOT.kRed,
marker_style=20,
leg_draw_opt=leg_draw_opt)
plot_d = Contribution(info['d'].CreateGraph(),
label="Down",
line_color=ROOT.kBlue,
marker_color=ROOT.kBlue,
marker_style=21,
leg_draw_opt=leg_draw_opt)
plot_s = Contribution(info['s'].CreateGraph(),
label="Strange",
line_color=ROOT.kBlack,
marker_color=ROOT.kBlack,
marker_style=22,
leg_draw_opt=leg_draw_opt)
plot_c = Contribution(info['c'].CreateGraph(),
label="Charm",
line_color=ROOT.kGreen + 2,
marker_color=ROOT.kGreen + 2,
marker_style=23,
leg_draw_opt=leg_draw_opt)
plot_b = Contribution(info['b'].CreateGraph(),
label="Bottom",
line_color=ROOT.kOrange - 3,
marker_color=ROOT.kOrange - 3,
marker_style=33,
leg_draw_opt=leg_draw_opt)
plot_g = Contribution(info['g'].CreateGraph(),
label="Gluon",
line_color=ROOT.kViolet,
marker_color=ROOT.kViolet,
marker_style=29,
leg_draw_opt=leg_draw_opt)
plot_unknown = Contribution(info['unknown'].CreateGraph(),
label="Unknown",
line_color=ROOT.kGray + 1,
marker_color=ROOT.kGray + 1,
marker_style=26,
leg_draw_opt=leg_draw_opt)
p_flav = Plot(
[plot_d, plot_u, plot_s, plot_c, plot_b, plot_g, plot_unknown],
what='graph',
xtitle="y^{%s}" % get_jet_str(''),
ytitle="Fraction",
title=title,
xlim=(eta_bins[0][0], eta_bins[-1][1]),
ylim=[0, 1],
has_data=False)
p_flav.default_canvas_size = (600, 600)
p_flav.plot("AP")
p_flav.main_pad.SetBottomMargin(0.16)
p_flav.get_modifier().GetXaxis().SetTitleOffset(1.4)
p_flav.get_modifier().GetXaxis().SetTitleSize(.045)
p_flav.legend.SetX1(0.55)
p_flav.legend.SetY1(0.72)
p_flav.legend.SetY2(0.85)
p_flav.legend.SetNColumns(2)
p_flav.save(output_filename)
def do_flavour_fraction_vs_pt(input_file,
hist_name,
pt_bins,
output_filename,
title=""):
"""Plot all flavour fractions vs PT for one input file & hist_name in the ROOT file"""
info = get_flavour_efficiencies(input_file,
bins=pt_bins,
hist_name=hist_name)
leg_draw_opt = "LP"
plot_u = Contribution(info['u'].CreateGraph(),
label="Up",
line_color=ROOT.kRed,
marker_color=ROOT.kRed,
marker_style=20,
leg_draw_opt=leg_draw_opt)
plot_d = Contribution(info['d'].CreateGraph(),
label="Down",
line_color=ROOT.kBlue,
marker_color=ROOT.kBlue,
marker_style=21,
leg_draw_opt=leg_draw_opt)
plot_s = Contribution(info['s'].CreateGraph(),
label="Strange",
line_color=ROOT.kBlack,
marker_color=ROOT.kBlack,
marker_style=22,
leg_draw_opt=leg_draw_opt)
plot_c = Contribution(info['c'].CreateGraph(),
label="Charm",
line_color=ROOT.kGreen + 2,
marker_color=ROOT.kGreen + 2,
marker_style=23,
leg_draw_opt=leg_draw_opt)
plot_b = Contribution(info['b'].CreateGraph(),
label="Bottom",
line_color=ROOT.kOrange - 3,
marker_color=ROOT.kOrange - 3,
marker_style=33,
leg_draw_opt=leg_draw_opt)
plot_g = Contribution(info['g'].CreateGraph(),
label="Gluon",
line_color=ROOT.kViolet,
marker_color=ROOT.kViolet,
marker_style=29,
leg_draw_opt=leg_draw_opt)
plot_unknown = Contribution(info['unknown'].CreateGraph(),
label="Unknown",
line_color=ROOT.kGray + 1,
marker_color=ROOT.kGray + 1,
marker_style=26,
leg_draw_opt=leg_draw_opt)
p_flav = Plot(
[plot_d, plot_u, plot_s, plot_c, plot_b, plot_g, plot_unknown],
what='graph',
xtitle="p_{T}^{%s} [GeV]" % get_jet_str(''),
ytitle="Fraction",
title=title,
xlim=(pt_bins[0][0], pt_bins[-1][1]),
ylim=[0, 1],
has_data=False)
p_flav.default_canvas_size = (600, 600)
p_flav.plot("AP")
p_flav.main_pad.SetBottomMargin(0.16)
p_flav.get_modifier().GetXaxis().SetTitleOffset(1.4)
p_flav.get_modifier().GetXaxis().SetTitleSize(.045)
p_flav.set_logx(do_more_labels=True, do_exponent=False)
p_flav.legend.SetX1(0.55)
p_flav.legend.SetY1(0.72)
p_flav.legend.SetY2(0.85)
p_flav.legend.SetNColumns(2)
p_flav.save(output_filename)
def compare_flavour_fraction_hists_vs_pt(input_files,
hist_names,
pt_bins,
labels,
flav,
output_filename,
title="",
xtitle="p_{T}^{jet} [GeV]",
is_preliminary=True):
"""Plot a specified flavour fraction vs pT for several sources.
Each entry in input_files, dirnames, and labels corresponds to one line
n_partons can be a str, 'all', '1', etc, or a list of str to include
TODO: use this one more often - compare_flavour_fractions_vs_pt() is almost identical but has to deal with npartons
"""
bin_centers = [0.5 * (x[0] + x[1]) for x in pt_bins]
bin_widths = [0.5 * (x[1] - x[0]) for x in pt_bins]
contribs = []
info = [
get_flavour_efficiencies(ifile, bins=pt_bins, hist_name=hname)
for ifile, hname in zip(input_files, hist_names)
]
N = len(bin_centers)
colours = [ROOT.kBlack, ROOT.kBlue, ROOT.kRed, ROOT.kGreen + 2]
for i, fdict in enumerate(info):
if flav in ['u', 'd', 's', 'c', 'b', 't', 'g']:
obj = fdict[flav].CreateGraph()
else:
raise RuntimeError("Robin broke 1-X functionality")
obj = ROOT.TGraphErrors(
N, np.array(bin_centers),
1. - np.array(fdict[flav.replace("1-", '')]),
np.array(bin_widths), np.zeros(N))
if obj.GetN() == 0:
continue
c = Contribution(obj,
label=labels[i],
line_color=colours[i],
line_width=1,
line_style=1,
marker_style=20 + i,
marker_color=colours[i],
marker_size=1,
leg_draw_opt="LP")
contribs.append(c)
flav_str = FLAV_STR_DICT[flav]
ytitle = "Fraction of %s %ss" % (flav_str.lower(), get_jet_str(''))
p = Plot(contribs,
what='graph',
xtitle=xtitle,
ytitle=ytitle,
title=title,
xlim=(50, 2000),
ylim=(0, 1),
has_data=False,
is_preliminary=is_preliminary)
p.default_canvas_size = (600, 600)
try:
p.plot("AP")
p.main_pad.SetBottomMargin(0.16)
p.get_modifier().GetXaxis().SetTitleOffset(1.4)
p.get_modifier().GetXaxis().SetTitleSize(.045)
p.legend.SetX1(0.56)
p.legend.SetY1(0.65)
p.legend.SetY2(0.87)
p.set_logx(do_more_labels=True, do_exponent=False)
p.save(output_filename)
except ZeroContributions:
pass
def compare_flavour_fractions_vs_pt(input_files,
dirnames,
pt_bins,
labels,
flav,
output_filename,
title="",
var_prepend="",
which_jet="both",
xtitle="p_{T}^{jet} [GeV]",
n_partons='all',
is_preliminary=True):
"""Plot a specified flavour fraction vs pT for several sources.
Each entry in input_files, dirnames, and labels corresponds to one line
n_partons can be a str, 'all', '1', etc, or a list of str to include
TODO: fix this - bit stupid input format
"""
bin_centers = [0.5 * (x[0] + x[1]) for x in pt_bins]
bin_widths = [0.5 * (x[1] - x[0]) for x in pt_bins]
if isinstance(n_partons, str):
n_partons = [n_partons]
contribs = []
for n_parton_ind, n_parton in enumerate(n_partons):
metric = 'pt'
if n_parton.lower() != 'all':
metric = 'pt_npartons_%s' % n_parton
info = [
get_flavour_efficiencies(
ifile,
bins=pt_bins,
hist_name=get_flavour_hist_name(
dirname=dname,
var_prepend=var_prepend,
which_jet=(which_jet if "Dijet" in dname else "both"),
metric=metric))
for ifile, dname in zip(input_files, dirnames)
]
N = len(bin_centers)
colours = [ROOT.kBlack, ROOT.kBlue, ROOT.kRed, ROOT.kGreen + 2]
for i, fdict in enumerate(info):
if flav in ['u', 'd', 's', 'c', 'b', 't', 'g']:
obj = fdict[flav].CreateGraph()
else:
raise RuntimeError("Robin broke 1-X functionality")
obj = ROOT.TGraphErrors(
N, np.array(bin_centers),
1. - np.array(fdict[flav.replace("1-", '')]),
np.array(bin_widths), np.zeros(N))
if obj.GetN() == 0:
continue
n_parton_str = "" if n_parton == "all" else " (%s-parton)" % n_parton
c = Contribution(obj,
label="%s%s" % (labels[i], n_parton_str),
line_color=colours[i] + n_parton_ind,
line_width=1,
line_style=n_parton_ind + 1,
marker_style=20 + i,
marker_color=colours[i] + n_parton_ind,
marker_size=1,
leg_draw_opt="LP")
contribs.append(c)
flav_str = FLAV_STR_DICT[flav]
ytitle = "Fraction of %s %ss" % (flav_str.lower(), get_jet_str(''))
p = Plot(contribs,
what='graph',
xtitle=xtitle,
ytitle=ytitle,
title=title,
xlim=(pt_bins[0][0], pt_bins[-1][1]),
ylim=(0, 1),
has_data=False,
is_preliminary=is_preliminary)
p.default_canvas_size = (600, 600)
try:
p.plot("AP")
p.main_pad.SetBottomMargin(0.16)
p.get_modifier().GetXaxis().SetTitleOffset(1.4)
p.get_modifier().GetXaxis().SetTitleSize(.045)
p.legend.SetX1(0.56)
p.legend.SetY1(0.65)
p.legend.SetY2(0.87)
p.set_logx(do_more_labels=True, do_exponent=False)
p.save(output_filename)
except ZeroContributions:
pass
def make_plot(entries,
output_filename,
plot_kwargs,
projection_axis='x',
start_val=None,
end_val=None,
is_pdgid_plot=False,
logy=False):
"""Make a plot from entries. Each one is a projection of a 2D plot.
Parameters
----------
entries : list[dict]
List of plot entries. Each is represented by a dict
output_filename : str
Filename for output plot
plot_kwargs : dict
kwargs for Plot constructor
projection_axis : str, optional
Axis to use for projection. If None, must be specified in entry.
start_val : None, optional
If set, use this to make 1D projection plot. Cuts on X axis.
Otherwise should be set per entry.
end_val : None, optional
If set, use this to make 1D projection plot. Cuts on X axis.
Otherwise should be set per entry.
is_pdgid_plot : bool, optional
True if for PDGIDs (sets special size & binning)
logy : bool, optional
Description
Raises
------
RuntimeError
Description
"""
conts = []
if not is_pdgid_plot:
for ent in entries:
h2d = cu.get_from_tfile(
ent['file'],
"ak4pfchsl1/" + ent['histname'] + "_JetEta0to0.783")
start_val = ent.get('start_val', start_val)
end_val = ent.get('end_val', end_val)
if start_val is None or end_val is None:
raise RuntimeError("Expected start_val and end_val")
hist = cu.get_projection_plot(
h2d, start_val, end_val,
ent.get('projection_axis', projection_axis))
if hist.GetEntries() == 0:
ent['used'] = False
continue
contrib = Contribution(hist,
label=ent['label'],
line_width=lw,
line_color=ent['colour'],
line_style=ent.get('line_style', 1),
marker_size=ent.get('marker_size', 0),
marker_color=ent['colour'],
marker_style=ent.get('marker_style', 1),
normalise_hist=True,
rebin_hist=ent.get('rebin', None))
conts.append(contrib)
ent['used'] = True
else:
# For PDGID plots, we want a different canvas aspect ratio, and only to include bins
# with non-0 contents. We also relabel bins.
custom_bins = []
for ent in entries:
h2d = cu.get_from_tfile(
ent['file'],
"ak4pfchsl1/" + ent['histname'] + "_JetEta0to0.783")
start_val = ent.get('start_val', start_val)
end_val = ent.get('end_val', end_val)
if not start_val or not end_val:
raise RuntimeError("Expected start_val and end_val")
hist = cu.get_projection_plot(
h2d, start_val, end_val,
ent.get('projection_axis', projection_axis))
ax = hist.GetXaxis()
bins = dict()
for i in range(1, hist.GetNbinsX() + 1):
value = ax.GetBinLowEdge(i)
cont = hist.GetBinContent(i)
err = hist.GetBinError(i)
if cont > 0:
bins[value] = [cont, err]
# print(custom_bins[-1])
custom_bins.append(bins)
nbins = max([len(d) for d in custom_bins])
first_keys = set(custom_bins[0].keys())
for cb in custom_bins[1:]:
first_keys = first_keys.union(set(cb.keys()))
all_keys = sorted(list(first_keys))
print(all_keys)
for cbin, ent in zip(custom_bins, entries):
h = ROOT.TH1D(cu.get_unique_str(), ";PDGID;N", nbins, 0, nbins)
for ind, k in enumerate(all_keys, 1):
content, error = cbin.get(k, [0, 0])
h.SetBinContent(ind, content)
h.SetBinError(ind, error)
ax = h.GetXaxis()
for i in range(1, nbins + 1):
# ax.SetBinLabel(i, str(int(all_keys[i-1])))
pdgid = int(all_keys[i - 1])
ax.SetBinLabel(i, PDGID_STR.get(pdgid, str(pdgid)))
h.LabelsOption("v")
contrib = Contribution(h,
label=ent['label'],
line_width=lw,
line_color=ent['colour'],
line_style=ent.get('line_style', 1),
marker_size=ent.get('marker_size', 0),
marker_color=ent['colour'],
marker_style=ent.get('marker_style', 1),
normalise_hist=True,
rebin_hist=ent.get('rebin', None))
conts.append(contrib)
ent['used'] = True
entries = [e for e in entries if e['used']]
for ind, ent in enumerate(entries):
if not ent['used']:
continue
if ent.get('subplot_ind', -1) >= 0:
conts[ind].subplot = conts[ent['subplot_ind']].obj
plot = Plot(conts,
what="hist",
ytitle="p.d.f.",
has_data=False,
**plot_kwargs)
if is_pdgid_plot and conts[0].obj.GetNbinsX() > 10:
plot.default_canvas_size = (800, 800)
else:
plot.default_canvas_size = (450, 600)
plot.legend.SetX1(0.5)
plot.legend.SetX2(0.97)
if len(entries) > 4:
plot.legend.SetY1(0.7)
plot.legend.SetNColumns(2)
else:
plot.legend.SetY1(0.75)
plot.legend.SetY2(0.9)
plot.plot("HISTE NOSTACK")
if logy:
plot.set_logy()
plot.save(output_filename)
def do_zerobias_per_run_comparison_plot(dirname_label_pairs,
output_dir,
append="",
title="",
**plot_kwargs):
runs = [
(qgc.ZEROBIAS_RUNB_FILENAME, 'B'),
(qgc.ZEROBIAS_RUNC_FILENAME, 'C'),
(qgc.ZEROBIAS_RUND_FILENAME, 'D'),
(qgc.ZEROBIAS_RUNE_FILENAME, 'E'),
(qgc.ZEROBIAS_RUNF_FILENAME, 'F'),
(qgc.ZEROBIAS_RUNG_FILENAME, 'G'),
(qgc.ZEROBIAS_RUNH_FILENAME, 'H'),
]
zb_entry = {
'label': 'HLT_ZeroBias',
'color': ROOT.kMagenta - 9,
# 'scale': 35918219492.947 / 29048.362
'scale': 1
}
for filename, run_period in runs:
zb_root_files = [
cu.open_root_file(os.path.join(dl[0], filename))
for dl in dirname_label_pairs
]
# PT JET 1
zb_hist_names = [
"Dijet_jet_hist_0/pt_1", "Dijet_jet_hist_unweighted_0/pt_1"
][1:]
N = len(dirname_label_pairs)
rebin = 2
for zb_name in zb_hist_names:
# add zeero bias ones
this_data_entries = [
Contribution(
cu.get_from_tfile(zb_root_files[i], zb_name),
label=zb_entry['label'] + " Run %s: " % run_period + l,
marker_color=zb_entry['color'],
line_color=zb_entry['color'],
line_style=1 + i,
rebin_hist=rebin,
) for i, (d, l) in enumerate(dirname_label_pairs)
]
for c in this_data_entries[1:]:
c.subplot = this_data_entries[0].obj
plot = Plot(
this_data_entries,
what='hist',
title=title,
xtitle="p_{T}^{jet 1} [GeV]",
ytitle="N",
xlim=[30, 1000],
ylim=[1E3, None],
# ylim=[10, 1E8] if 'unweighted' in ht_name else [1, 1E12],
subplot_type='ratio',
subplot_title='* / %s' % dirname_label_pairs[0][1],
**plot_kwargs)
plot.subplot_maximum_ceil = 10
plot.default_canvas_size = (800, 600)
plot.y_padding_max_log = 500
plot.legend.SetY1(0.7)
plot.legend.SetY2(0.88)
plot.legend.SetX1(0.5)
plot.legend.SetNColumns(2)
plot.plot("NOSTACK HISTE")
plot.set_logx(do_more_labels=False)
plot.set_logy(do_more_labels=False)
output_filename = "%s/DataJetHTZB-pt_jet1%s_Run%s%s.pdf" % (
output_dir, "_unweighted" if 'unweighted' in zb_name else "",
run_period, append)
plot.save(output_filename)
# ETA JET 1
zb_hist_names = ["Dijet_jet_hist_unweighted_0/eta_1"]
N = len(dirname_label_pairs)
rebin = 2
for zb_name in zb_hist_names:
# add zero bias ones
this_data_entries = [
Contribution(
cu.get_from_tfile(zb_root_files[i], zb_name),
label=zb_entry['label'] + " Run %s: " % run_period + l,
marker_color=zb_entry['color'],
line_color=zb_entry['color'],
line_style=1 + i,
rebin_hist=rebin,
) for i, (d, l) in enumerate(dirname_label_pairs)
]
for c in this_data_entries[1:]:
c.subplot = this_data_entries[0].obj
# plot zb
plot = Plot(
this_data_entries,
what='hist',
title=title,
xtitle="y^{jet 1}",
ytitle="N",
subplot_type='ratio',
subplot_title='* / %s' % dirname_label_pairs[0][1],
# subplot_limits=(0, 5),
**plot_kwargs)
plot.subplot_maximum_ceil = 5
plot.default_canvas_size = (800, 600)
plot.y_padding_max_log = 500
plot.legend.SetY1(0.7)
plot.legend.SetY2(0.88)
plot.legend.SetX1(0.5)
plot.legend.SetNColumns(2)
plot.plot("NOSTACK HISTE")
output_filename = "%s/DataZB-eta_jet1%s_Run%s%s.pdf" % (
output_dir, "_unweighted" if 'unweighted' in zb_name else "",
run_period, append)
plot.save(output_filename)
def do_jetht_trigger_comparison_plot(dirname_label_pairs,
output_dir,
append="",
title="",
**plot_kwargs):
# Unweighted pt, showing contributions from different triggers
# Have to add in ZB manually
zb_entry = {
'label': 'HLT_ZeroBias',
'color': ROOT.kMagenta - 9,
# 'scale': 35918219492.947 / 29048.362
'scale': 1
}
jet_ht_entries = [
{
'ind': '0',
'label': "PFJet40",
'color': ROOT.kRed,
},
{
'ind': '1',
'label': "PFJet60",
'color': ROOT.kBlue,
},
{
'ind': '2',
'label': "PFJet80",
'color': ROOT.kGreen + 2,
},
{
'ind': '3',
'label': "PFJet140",
'color': ROOT.kViolet + 5,
},
{
'ind': '4',
'label': "PFJet200",
'color': ROOT.kOrange,
},
{
'ind': '5',
'label': "PFJet260",
'color': ROOT.kTeal,
},
{
'ind': '6',
'label': "PFJet320",
'color': ROOT.kViolet,
},
{
'ind': '7',
'label': "PFJet400",
'color': ROOT.kOrange - 6
},
{
'ind': '8',
'label': "PFJet450",
'color': ROOT.kAzure + 1,
},
]
# PT JET 1
zb_hist_names = [
"Dijet_jet_hist_0/pt_1", "Dijet_jet_hist_unweighted_0/pt_1"
]
jet_ht_hist_names = [
"Dijet_jet_hist_{ind}/pt_1", "Dijet_jet_hist_unweighted_{ind}/pt_1"
]
zb_root_files = [
cu.open_root_file(os.path.join(dl[0], qgc.ZB_FILENAME))
for dl in dirname_label_pairs
]
jetht_root_files = [
cu.open_root_file(os.path.join(dl[0], qgc.JETHT_FILENAME))
for dl in dirname_label_pairs
]
N = len(dirname_label_pairs)
rebin = 2
for zb_name, ht_name in zip(zb_hist_names, jet_ht_hist_names):
# add zeero bias ones
this_data_entries = [
Contribution(
cu.get_from_tfile(zb_root_files[i], zb_name),
label=zb_entry['label'] + ": " + l,
marker_color=zb_entry['color'],
line_color=zb_entry['color'],
line_style=1 + i,
rebin_hist=rebin,
) for i, (d, l) in enumerate(dirname_label_pairs)
]
for c in this_data_entries[1:]:
c.subplot = this_data_entries[0].obj
# # add jet ht ones
for ent in jet_ht_entries:
histname = ht_name.format(ind=ent['ind'])
new_entries = [
Contribution(
cu.get_from_tfile(jetht_root_files[i], histname),
label=ent['label'] + ": " + l,
marker_color=ent['color'],
line_color=ent['color'],
line_style=1 + i,
rebin_hist=rebin,
) for i, (d, l) in enumerate(dirname_label_pairs)
]
for c in new_entries[1:]:
c.subplot = new_entries[0].obj
this_data_entries.extend(new_entries)
plot = Plot(
this_data_entries,
what='hist',
title=title,
ytitle="N",
xtitle="p_{T}^{jet 1} [GeV]",
xlim=[30, 1000],
ylim=[1E3, None],
# ylim=[10, 1E8] if 'unweighted' in ht_name else [1, 1E12],
subplot_type='ratio',
subplot_title='* / %s' % dirname_label_pairs[0][1],
**plot_kwargs)
plot.default_canvas_size = (800, 600)
plot.subplot_maximum_ceil = 10
plot.y_padding_max_log = 500
plot.legend.SetY1(0.7)
plot.legend.SetY2(0.88)
plot.legend.SetX1(0.5)
plot.legend.SetNColumns(2)
plot.plot("NOSTACK HISTE")
plot.set_logx(do_more_labels=False)
plot.set_logy(do_more_labels=False)
output_filename = "%s/DataJetHTZB-pt_jet1%s%s.pdf" % (
output_dir, "_unweighted" if 'unweighted' in zb_name else "",
append)
plot.save(output_filename)
# ETA JET 1
zb_hist_names = ["Dijet_jet_hist_unweighted_0/eta_1"]
jet_ht_hist_names = ["Dijet_jet_hist_unweighted_{ind}/eta_1"]
zb_root_files = [
cu.open_root_file(os.path.join(dl[0], qgc.ZB_FILENAME))
for dl in dirname_label_pairs
]
jetht_root_files = [
cu.open_root_file(os.path.join(dl[0], qgc.JETHT_FILENAME))
for dl in dirname_label_pairs
]
N = len(dirname_label_pairs)
rebin = 2
for zb_name, ht_name in zip(zb_hist_names, jet_ht_hist_names):
# add zero bias ones
this_data_entries = [
Contribution(
cu.get_from_tfile(zb_root_files[i], zb_name),
label=zb_entry['label'] + ": " + l,
marker_color=zb_entry['color'],
line_color=zb_entry['color'],
line_style=1 + i,
rebin_hist=rebin,
) for i, (d, l) in enumerate(dirname_label_pairs)
]
for c in this_data_entries[1:]:
c.subplot = this_data_entries[0].obj
# plot zb
plot = Plot(
this_data_entries,
what='hist',
title=title,
xtitle="y^{jet 1}",
ytitle="N",
subplot_type='ratio',
subplot_title='* / %s' % dirname_label_pairs[0][1],
# subplot_limits=(0, 5),
**plot_kwargs)
plot.subplot_maximum_ceil = 5
plot.default_canvas_size = (800, 600)
plot.y_padding_max_log = 500
plot.legend.SetY1(0.7)
plot.legend.SetY2(0.88)
plot.legend.SetX1(0.5)
plot.legend.SetNColumns(2)
plot.plot("NOSTACK HISTE")
output_filename = "%s/DataZB-eta_jet1%s%s.pdf" % (
output_dir, "_unweighted" if 'unweighted' in zb_name else "",
append)
plot.save(output_filename)
# add jet ht ones
for ent in jet_ht_entries:
histname = ht_name.format(ind=ent['ind'])
this_data_entries = [
Contribution(
cu.get_from_tfile(jetht_root_files[i], histname),
label=ent['label'] + ": " + l,
marker_color=ent['color'],
line_color=ent['color'],
line_style=1 + i,
rebin_hist=rebin,
) for i, (d, l) in enumerate(dirname_label_pairs)
]
for c in this_data_entries[1:]:
c.subplot = this_data_entries[0].obj
plot = Plot(
this_data_entries,
what='hist',
title=title,
xtitle="y^{jet 1}",
ytitle="N",
# xlim=[30, 1000],
# ylim=[10, 1E8] if 'unweighted' in ht_name else [1, 1E12],
subplot_type='ratio',
subplot_title='* / %s' % dirname_label_pairs[0][1],
**plot_kwargs)
plot.default_canvas_size = (800, 600)
plot.y_padding_max_log = 500
plot.legend.SetY1(0.7)
plot.legend.SetY2(0.88)
plot.legend.SetX1(0.5)
plot.legend.SetNColumns(2)
plot.plot("NOSTACK HISTE")
output_filename = "%s/DataJetHTZB-%s_eta_jet1%s%s.pdf" % (
output_dir, ent['label'],
"_unweighted" if 'unweighted' in zb_name else "", append)
plot.save(output_filename)
def draw_projection_comparison(h_orig,
h_projection,
title,
xtitle,
output_filename,
print_bin_comparison=True):
"""Draw 2 hists, h_orig the original, and h_projection the projection of a 2D hist"""
# Check integrals
int_orig = h_orig.Integral()
int_proj = h_projection.Integral()
if abs(int_orig - int_proj) / int_orig > 0.01:
print("draw_projection_comparison: different integrals: %f vs %f" %
(int_orig, int_proj))
# Check bin-by-bin
if print_bin_comparison:
for i in range(1, h_orig.GetNbinsX() + 1):
value_orig = h_orig.GetBinContent(i)
value_proj = h_projection.GetBinContent(i)
if value_orig == 0 and value_proj == 0:
continue
rel_diff = abs((value_orig - value_proj) /
max(abs(value_orig), abs(value_proj)))
if rel_diff > 1E-3:
print(
"draw_projection_comparison: bin %s has different contents: %f vs %f (rel diff %f)"
% (i, value_orig, value_proj, rel_diff))
entries = [
Contribution(h_orig,
label="1D hist",
line_color=ROOT.kBlue,
line_width=1,
marker_color=ROOT.kBlue,
marker_size=0,
normalise_hist=False),
Contribution(h_projection,
label="Response map projection",
line_color=ROOT.kRed,
line_width=1,
marker_color=ROOT.kRed,
marker_size=0,
normalise_hist=False,
subplot=h_orig),
]
plot = Plot(entries,
what='hist',
title=title,
xtitle=xtitle,
ytitle="N",
subplot_type='ratio',
subplot_title='Projection / 1D',
subplot_limits=(0.999, 1.001))
plot.default_canvas_size = (800, 600)
plot.plot("NOSTACK HIST")
plot.main_pad.SetLogy(1)
ymax = max(h.GetMaximum() for h in [h_orig, h_projection])
plot.container.SetMaximum(ymax * 10)
# plot.container.SetMinimum(1E-8)
plot.legend.SetY1NDC(0.77)
plot.legend.SetX2NDC(0.85)
plot.save(output_filename)
