def plot_rsp_Vs_ref(check_file, eta_min, eta_max, normX, logZ, oDir, oFormat="pdf"):
"""Plot response (l1/ref) Vs ref pt"""
app = "_normX" if normX else ""
hname = "eta_%g_%g/Histograms/h2d_rsp_gen%s" % (eta_min, eta_max, app)
fwd_bin = abs(eta_min)>2.9
if cu.exists_in_file(check_file, hname):
h2d_rsp_ref_orig = cu.get_from_file(check_file, hname)
else:
h2d_rsp_ref_orig = cu.get_from_file(check_file, "eta_%g_%g/Histograms/h2d_rsp_gen" % (eta_min, eta_max))
if normX:
h2d_rsp_ref_orig = cu.norm_vertical_bins(h2d_rsp_ref_orig, rescale_peaks=True)
h2d_rsp_ref = h2d_rsp_ref_orig.Rebin2D(2, 1, "hnew")
c = generate_canvas()
if logZ:
c.SetLogz()
app += "_log"
h2d_rsp_ref.SetTitle("%s: %g-%g;%s;%s" % (eta_l1_str, eta_min, eta_max, pt_ref_str, rsp_str))
if normX:
h2d_rsp_ref.Draw("COL")
else:
h2d_rsp_ref.Draw("COLZ")
h2d_rsp_ref.SetAxisRange(rsp_min, rsp_max, 'Y')
if fwd_bin:
h2d_rsp_ref.SetAxisRange(0, 254, 'X')
line = ROOT.TLine(0, 1, 1022, 1)
line.SetLineStyle(2)
line.SetLineWidth(2)
line.Draw()
c.SaveAs("%s/h2d_rsp_ref_%g_%g%s.%s" % (oDir, eta_min, eta_max, app, oFormat))
def plot_rsp_Vs_pt_candle_violin(check_file, eta_min, eta_max, ptVar, oDir, oFormat):
"""Plot response vs pt as a candle plot and violin plot.
Also puts fitted peak graph on there as well for comparison."""
hname = "eta_%g_%g/Histograms/h2d_rsp_%s" % (eta_min, eta_max, ptVar)
if cu.exists_in_file(check_file, hname):
h2d_rsp_pt_orig = cu.get_from_file(check_file, hname)
else:
h2d_rsp_pt_orig = cu.get_from_file(check_file, "eta_%g_%g/Histograms/h2d_rsp_%s" % (eta_min, eta_max, ptVar))
h2d_rsp_pt = h2d_rsp_pt_orig.Rebin2D(1, 1, "hnew")
c = generate_canvas()
ptStr = pt_l1_str if ptVar == 'l1' else pt_ref_str
h2d_rsp_pt.SetTitle("%s: %g-%g;%s;%s" % (eta_l1_str, eta_min, eta_max, ptStr, rsp_str))
h2d_rsp_pt.Draw("CANDLE")
# Draw fitted peaks as well
gr_name = "eta_{0:g}_{1:g}/gr_rsp_{2}_eta_{0:g}_{1:g}".format(eta_min, eta_max, 'pt' if ptVar == 'l1' else 'ptRef')
gr = cu.get_from_file(check_file, gr_name)
gr.SetLineColor(ROOT.kRed)
gr.SetMarkerColor(ROOT.kRed)
gr.SetMarkerStyle(21)
gr.Draw("LP")
max_pt = 100
gr.GetXaxis().SetLimits(0, max_pt)
h2d_rsp_pt.SetAxisRange(0, max_pt, 'X')
h2d_rsp_pt.SetAxisRange(rsp_min, rsp_max, 'Y')
line = ROOT.TLine(0, 1, max_pt, 1)
line.SetLineStyle(2)
line.SetLineWidth(2)
line.Draw()
c.SaveAs("%s/h2d_rsp_%s_%g_%g_box.%s" % (oDir, 'l1' if ptVar == 'l1' else 'ref', eta_min, eta_max, oFormat))
h2d_rsp_pt.Draw("VIOLIN")
gr.Draw("LP")
c.SaveAs("%s/h2d_rsp_%s_%g_%g_violin.%s" % (oDir, 'l1' if ptVar == 'l1' else 'ref', eta_min, eta_max, oFormat))
dir_append = hist_dir.lower().replace("weight_", "")
odir = os.path.join(MAINDIR, workdir, "var_jet_pt_weights_%s_%s" % (dir_append, filename.replace("uhh2.AnalysisModuleRunner.MC.MC_", "").replace(".root", "")))
cu.check_dir_exists_create(odir)
# do_weight_vs_pt_plot(input_filename=ifile,
# output_filename=os.path.join(odir, "weight_vs_pt.pdf"))
# do_weight_vs_genjet_pt_plot(input_filename=ifile,
# output_filename=os.path.join(odir, "weight_vs_genjet_pt.pdf"))
for ind, base_hname in enumerate(histnames):
hname = os.path.join(hist_dir, base_hname)
tf = cu.open_root_file(ifile)
if not cu.exists_in_file(tf, hname):
continue
do_var_vs_pt_plot(histname=hname,
input_filename=ifile,
output_filename=os.path.join(odir, base_hname.replace("weight_vs_", "") + ".pdf"))
# if "_vs_pt_" in hname:
# # skip the _vs_pt_genjet_ since identical, and we collapse that axis anyway
# do_weight_vs_var_plot(histname=hname,
# input_filename=ifile,
# output_filename=os.path.join(odir, base_hname.replace("_vs_pt_vs_", "_").replace("_vs_pt_genjet_vs_", "") + ".pdf"))
cuts = [10, 9, 8, 7, 6, 5, 4, 3, 2]
cuts = [10, 8, 6, 4, 3, 2]
cuts = [100, 75, 50, 25, 10, 8, 5, 2]
def main(in_args):
parser = argparse.ArgumentParser()
parser.add_argument(
"--input",
help=
"Input ROOT file with response & resolution hists (from jet_response_fitter_x)",
required=True)
parser.add_argument("--outputDir",
help="Output directory for plots",
default=os.getcwd())
parser.add_argument("--title", help="Title string for plots", default="")
parser.add_argument("--sampleName",
help="Sample name string for plots",
default="")
parser.add_argument("--plotN",
help="Plot grpah of N vs pT that goes into the median",
action='store_true')
parser.add_argument(
"--plotRMS",
help="Plot graph of raw RMS vs pT that goes into memdian",
action='store_true')
args = parser.parse_args(in_args)
cu.check_dir_exists_create(args.outputDir)
lw = 2
entry_dicts = [
{
"flav": "RelRsp",
"label": "All",
"colour": ROOT.kBlack,
"marker_style": ROOT.kFullCircle,
"line_style": 2,
"line_width": lw,
"marker_size": 1.2
},
{
"flav": "ud_RelRsp",
"label": "ud",
"colour": ROOT.kRed,
"marker_style": ROOT.kFullSquare,
"line_style": 1,
"line_width": lw,
"marker_size": 1.2
},
{
"flav": "s_RelRsp",
"label": "s",
"colour": ROOT.kBlue,
"marker_style": ROOT.kFullTriangleUp,
"line_style": 1,
"line_width": lw,
"marker_size": 1.4
},
{
"flav": "c_RelRsp",
"label": "c",
"colour": ROOT.kGreen + 2,
"marker_style": ROOT.kFullTriangleDown,
"line_style": 1,
"line_width": lw,
"marker_size": 1.4
},
{
"flav": "b_RelRsp",
"label": "b",
"colour": ROOT.kOrange - 3,
"marker_style": ROOT.kFullDiamond,
"line_style": 1,
"line_width": lw,
"marker_size": 1.6
},
{
"flav": "g_RelRsp",
"label": "g",
"colour": ROOT.kAzure + 1,
"marker_style": 29,
"line_style": 1,
"line_width": lw,
"marker_size": 1.8
},
]
# Loop through all different ak4pfchs, etc
input_tfile = cu.open_root_file(args.input)
dirs = cu.get_list_of_element_names(input_tfile)
for mydir in dirs[:1]:
jec_text = ROOT.TPaveText(0.14, 0.91, 0.2, 0.92, "NDC")
jec_text.AddText(args.title)
jec_text.SetTextAlign(ROOT.kHAlignLeft + ROOT.kVAlignBottom)
jec_text.SetTextFont(42)
jec_text.SetTextSize(FONT_SIZE)
jec_text.SetBorderSize(0)
jec_text.SetFillStyle(0)
dir_text = ROOT.TPaveText(0.17, 0.72, 0.2, 0.73, "NDC")
dir_label = mydir.upper().replace("PFCHS", " PF CHS").replace(
"PUPPI", " PUPPI").replace("L1L2L3",
" + L1L2L3").replace("L1", " + L1")
dir_text.AddText(dir_label)
dir_text.SetTextAlign(ROOT.kHAlignLeft + ROOT.kVAlignBottom)
dir_text.SetTextFont(42)
dir_text.SetTextSize(FONT_SIZE)
dir_text.SetBorderSize(0)
dir_text.SetFillStyle(0)
sample_text = ROOT.TPaveText(0.91, 0.91, 0.97, 0.92, "NDC")
sample_text.AddText(args.sampleName + " 13 TeV")
sample_text.SetTextFont(42)
sample_text.SetTextSize(FONT_SIZE)
sample_text.SetTextAlign(ROOT.kHAlignRight + ROOT.kVAlignBottom)
sample_text.SetBorderSize(0)
sample_text.SetFillStyle(0)
sample_text.Draw()
other_elements = [jec_text, dir_text, sample_text]
plot_dir = os.path.join(args.outputDir, mydir)
cu.check_dir_exists_create(plot_dir)
obj_list = cu.get_list_of_objects_in_dir(args.input, mydir)
# Do separate dir for each eta bin, then separate plot for each pt bin
common_eta_bins = cu.sort_human(cu.get_common_eta_bins(obj_list))
common_pt_bins = cu.sort_human(cu.get_common_pt_bins(obj_list))
print("Doing eta bins", common_eta_bins)
print("Doing pt bins", common_pt_bins)
for eta_bin in common_eta_bins[:]:
this_plot_dir = os.path.join(plot_dir, eta_bin)
cu.check_dir_exists_create(this_plot_dir)
all_pt_entries = []
for pt_bin in common_pt_bins:
entries = []
if not cu.exists_in_file(
input_tfile, "%s/%s_%s_%s" %
(mydir, entry_dicts[0]['flav'], eta_bin, pt_bin)):
continue
for fdict in entry_dicts:
entry = deepcopy(fdict)
# entry["hist"] = cu.grab_obj_from_file(args.input, "%s/%s_%s_%s" % (mydir, fdict['flav'], eta_bin, pt_bin))
entry["hist"] = cu.get_from_tfile(
input_tfile, "%s/%s_%s_%s" %
(mydir, fdict['flav'], eta_bin, pt_bin))
entry["hist"].Rebin(int(entry["hist"].GetNbinsX() / 200))
entry["line_color"] = fdict['colour']
entry["marker_color"] = fdict['colour']
entries.append(entry)
bin_title = eta_bin.replace("to", " < |#eta| < ").replace(
"JetEta", "")
bin_title += "\n"
bin_title += pt_bin.replace("to", " < p^{Gen}_{T} < ").replace(
"RefPt", "")
bin_title += " GeV"
norm_entries = deepcopy(entries)
do_comparison_hist(
entries,
bin_title=bin_title,
xlimits=(0, 2),
xtitle="Response (p_{T}^{Reco} / p_{T}^{Gen})",
ytitle="N",
other_elements=other_elements,
normalise=False,
output_filename=os.path.join(
this_plot_dir, "rsp_vs_pt_%s.pdf" % (pt_bin)))
all_pt_entries.append(deepcopy(entries))
do_comparison_hist(
norm_entries,
bin_title=bin_title,
xlimits=(0, 2),
xtitle="Response (p_{T}^{Reco} / p_{T}^{Gen})",
ytitle="p.d.f",
other_elements=other_elements,
normalise=True,
draw_fits=False,
output_filename=os.path.join(
this_plot_dir, "rsp_vs_pt_%s_normed.pdf" % (pt_bin)))
this_dir_text = dir_text.Clone()
this_dir_text.SetY1(0.76)
this_dir_text.SetY2(0.77)
bin_title = eta_bin.replace("to",
" < |#eta| < ").replace("JetEta", "")
do_flavour_fraction_graph(
all_pt_entries,
common_pt_bins,
title=bin_title,
xtitle="p^{Gen}_{T} [GeV]",
ytitle="Flavour fraction",
other_elements=[jec_text, this_dir_text, sample_text],
add_unknown=False,
logx=True,
logy=True,
output_filename=os.path.join(
plot_dir, "flav_frac_vs_pt_%s.pdf" % (eta_bin)))
if args.plotN:
do_plot_N_graph(
all_pt_entries,
common_pt_bins,
title=bin_title,
which="GetEffectiveEntries",
xtitle="p^{Gen}_{T} [GeV]",
other_elements=[jec_text, this_dir_text, sample_text],
logx=True,
logy=True,
output_filename=os.path.join(
plot_dir, "Neff_vs_pt_%s.pdf" % (eta_bin)))
if args.plotRMS:
do_plot_RMS_graph(
all_pt_entries,
common_pt_bins,
title=bin_title,
xtitle="p^{Gen}_{T} [GeV]",
other_elements=[jec_text, this_dir_text, sample_text],
logx=True,
logy=True,
output_filename=os.path.join(
plot_dir, "RMS_vs_pt_%s.pdf" % (eta_bin)))
return 0
