def do_projection_plots(in_file, plot_dir, do_fit=True, skip_dirs=None):
hist_name = "pt_jet_response"
tfile = cu.open_root_file(in_file)
dirs = cu.get_list_of_element_names(tfile)
for mydir in dirs:
if skip_dirs and mydir in skip_dirs:
continue
if hist_name not in cu.get_list_of_element_names(tfile.Get(mydir)):
continue
print("Doing", mydir)
h2d = cu.grab_obj_from_file(in_file, "%s/%s" % (mydir, hist_name))
ax = h2d.GetXaxis()
bin_edges = [ax.GetBinLowEdge(i) for i in range(1, ax.GetNbins() + 2)]
bin_centers, sigmas, sigmas_unc = [], [], []
for pt_min, pt_max in zip(bin_edges[:-1], bin_edges[1:]):
obj = qgg.get_projection_plot(h2d, pt_min, pt_max, cut_axis='x')
if obj.GetEffectiveEntries() < 20:
continue
# obj.Rebin(rebin)
obj.Scale(1. / obj.Integral())
label = "%s < p_{T}^{Gen} < %s GeV" % (str(pt_min), str(pt_max))
if do_fit:
do_gaus_fit(obj)
fit = obj.GetFunction("gausFit")
label += "\n"
label += fit_results_to_str(fit)
# bin_centers.append(fit.GetParameter(1))
bin_centers.append(0.5 * (pt_max + pt_min))
sigmas.append(fit.GetParameter(2))
sigmas_unc.append(fit.GetParError(2))
# output_filename = os.path.join(plot_dir, "%s_%s_ptGen%sto%s.%s" % (mydir, hist_name, str(pt_min), str(pt_max), OUTPUT_FMT))
# cont = Contribution(obj, label=label)
# delta = pt_max - pt_min
# # xlim = (pt_min - 10*delta, pt_max + 10*delta)
# xlim = (obj.GetMean()-3*obj.GetRMS(), obj.GetMean()+3*obj.GetRMS())
# ylim = (0, obj.GetMaximum()*1.1)
# plot = Plot([cont], what='hist',
# xtitle="p_{T}^{Reco} [GeV]", xlim=xlim, ylim=ylim)
# plot.plot() # don't use histe as it wont draw the fit
# plot.save(output_filename)
gr = ROOT.TGraphErrors(len(bin_centers), array('d', bin_centers),
array('d', sigmas),
array('d', [0] * len(bin_centers)),
array('d', sigmas_unc))
factor = 0.2
gr_ideal = ROOT.TGraphErrors(
len(bin_centers), array('d', bin_centers),
array('d', [factor * pt for pt in bin_centers]),
array('d', [0] * len(bin_centers)),
array('d', [0] * len(bin_centers)))
gr_cont = Contribution(gr, label='Measured')
gr_ideal_cont = Contribution(gr_ideal,
label=str(factor) + '*p_{T}',
line_color=ROOT.kBlue,
marker_color=ROOT.kBlue)
plot = Plot([gr_cont, gr_ideal_cont],
what='graph',
xtitle="p_{T}^{Reco}",
ytitle="#sigma [GeV]",
ylim=[0, 100],
xlim=[10, 4000])
plot.plot()
plot.set_logx()
output_filename = os.path.join(
plot_dir, "%s_%s_sigma_plot.%s" % (mydir, hist_name, OUTPUT_FMT))
plot.save(output_filename)
import argparse
import os
import ROOT
ROOT.PyConfig.IgnoreCommandLineOptions = True
ROOT.gROOT.SetBatch(1)
ROOT.TH1.SetDefaultSumw2()
# ROOT.gStyle.SetOptStat(0)
ROOT.gStyle.SetOptFit(1111)
# My stuff
import common_utils as cu
if __name__ == '__main__':
parser = argparse.ArgumentParser(description=__doc__)
parser.add_argument("--input", help="Input ROOT file with response hist", required=True)
parser.add_argument("--inputDir", help="TDirectory in ROOT file", required=True)
parser.add_argument("--output", help="Output ROOT file to append hist to", required=True)
args = parser.parse_args()
hist = cu.grab_obj_from_file(args.input, "%s/pt_jet_response" % (args.inputDir))
hist.SetName("pt_jet_response")
hist_rebin = cu.make_normalised_TH2(hist, 'X', recolour=False, do_errors=False)
hist_rebin.SetName("pt_jet_response")
outf = cu.open_root_file(args.output, "UPDATE")
hist_rebin.Write()
outf.Close()
def main(in_args):
parser = argparse.ArgumentParser()
parser.add_argument("--input", help="Input ROOT file with correction graphs", 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="")
args = parser.parse_args(in_args)
cu.check_dir_exists_create(args.outputDir)
lw = 1
entry_dicts = [
{"flav": "AbsCorVsJetPt", "label": "All", "colour": ROOT.kBlack, "marker_style": ROOT.kFullCircle, "line_style": 2, "line_width": lw, "marker_size": 1.2},
{"flav": "ud_AbsCorVsJetPt", "label": "ud", "colour": ROOT.kRed, "marker_style": ROOT.kFullSquare, "line_style": 1, "line_width": lw, "marker_size": 1.2},
{"flav": "s_AbsCorVsJetPt", "label": "s", "colour": ROOT.kBlue, "marker_style": ROOT.kFullTriangleUp, "line_style": 1, "line_width": lw, "marker_size": 1.4},
{"flav": "c_AbsCorVsJetPt", "label": "c", "colour": ROOT.kGreen+2, "marker_style": ROOT.kFullTriangleDown, "line_style": 1, "line_width": lw, "marker_size": 1.4},
{"flav": "b_AbsCorVsJetPt", "label": "b", "colour": ROOT.kOrange-3, "marker_style": ROOT.kFullDiamond, "line_style": 1, "line_width": lw, "marker_size": 1.6},
{"flav": "g_AbsCorVsJetPt", "label": "g", "colour": ROOT.kAzure+1, "marker_style": 29, "line_style": 1, "line_width": lw, "marker_size": 1.8},
]
all_dirs = cu.get_list_of_element_names(cu.open_root_file(args.input))
dirs = sorted(list(all_dirs))[:1]
print("Doing: ", dirs)
# Loop through all different ak4pfchs, etc
for mydir in dirs:
jec_text = ROOT.TPaveText(0.15, 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, 0.76, 0.2, 0.77, "NDC")
dir_label = mydir.upper().replace("PFCHS", " PF CHS").replace("PUPPI", " PUPPI").replace("L1L2L3", " + L1L2L3")
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(0.93, 0.91, 0.94, 0.92, "NDC")
# sample_text.AddText("Flat QCD 13 TeV")
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)
# ylimits = (float(args.ylim[0]), float(args.ylim[1])) if args.ylim else None
ylimits = None
X_MIN, X_MAX = 8, 5000
# For limit protection:
Y_MIN, Y_MAX = 0.8, 1.6
# Do all flavs corr vs pt for given eta bin
common_eta_bins = cu.sort_human(cu.get_common_eta_bins(obj_list))
# Find the matching + and - eta bins
eta_bin_pairs = make_pos_neg_eta_pairs(common_eta_bins)
print(eta_bin_pairs)
for eta_bin_pair in eta_bin_pairs:
all_entries = []
title = eta_bin_pair[0].replace("to", " < |#eta| < ").replace("JetEta", "")
# Do a per-flavour comparison plot
for fdict in entry_dicts:
entries = []
for ind, (eta_bin, label) in enumerate(zip(eta_bin_pair, ['+#eta', '-#eta'])):
entry = deepcopy(fdict)
entry["graph"] = cu.grab_obj_from_file(args.input, "%s/%s_%s" % (mydir, fdict['flav'], eta_bin))
entry['label'] += " [%s]" % label
entry["line_color"] = fdict['colour']+ind
entry["marker_color"] = fdict['colour']+ind
entry["fill_color"] = fdict['colour']+ind
entry["fill_style"] = 1001
entry["fill_alpha"] = 0.7
if ind == 1:
entry["marker_style"] = get_open_marker(entry['marker_style'])
entry["line_style"] += 1
if ind == 2:
entry["line_style"] += 1
if ind == 3:
entry["line_style"] += 1
entry["marker_style"] = get_open_marker(entry['marker_style'])
entries.append(entry)
all_entries.append(entry)
do_comparison_graph(entries, title=title,
xtitle="p_{T}^{Reco} [GeV]", ytitle="Correction", logx=True,
xlimits=(X_MIN, X_MAX), y_limit_protection=(Y_MIN, Y_MAX),
ylimits=ylimits,
other_elements=other_elements,
output_filename=os.path.join(plot_dir, "compare_corr_vs_pt_%s_pos_neg_%s.pdf" % (eta_bin_pair[0], fdict['label'])))
# Do a plot with all flavours
do_comparison_graph(all_entries, title=title,
xtitle="p_{T}^{Reco} [GeV]", ytitle="Correction", logx=True,
xlimits=(X_MIN, X_MAX), y_limit_protection=(Y_MIN, Y_MAX),
other_elements=other_elements,
output_filename=os.path.join(plot_dir, "compare_corr_vs_pt_%s_pos_neg_allFlavs.pdf" % (eta_bin_pair[0])))
return 0
def main(in_args):
parser = argparse.ArgumentParser()
parser.add_argument(
"--input",
help=
"Input ROOT file with response & resolution graphs (from jet_response_and_resolution_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="")
args = parser.parse_args(in_args)
cu.check_dir_exists_create(args.outputDir)
lw = 1
entry_dicts = [
{
"flav": "AbsCorVsJetPt",
"label": "All",
"colour": ROOT.kBlack,
"marker_style": ROOT.kFullCircle,
"line_style": 1,
"line_width": lw,
"marker_size": 1.2
},
{
"flav": "ud_AbsCorVsJetPt",
"label": "ud",
"colour": ROOT.kRed,
"marker_style": ROOT.kFullSquare,
"line_style": 1,
"line_width": lw,
"marker_size": 1.2
},
{
"flav": "s_AbsCorVsJetPt",
"label": "s",
"colour": ROOT.kBlue,
"marker_style": ROOT.kFullTriangleUp,
"line_style": 1,
"line_width": lw,
"marker_size": 1.4
},
{
"flav": "c_AbsCorVsJetPt",
"label": "c",
"colour": ROOT.kGreen + 2,
"marker_style": ROOT.kFullTriangleDown,
"line_style": 1,
"line_width": lw,
"marker_size": 1.4
},
{
"flav": "b_AbsCorVsJetPt",
"label": "b",
"colour": ROOT.kOrange - 3,
"marker_style": ROOT.kFullDiamond,
"line_style": 1,
"line_width": lw,
"marker_size": 1.6
},
{
"flav": "g_AbsCorVsJetPt",
"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
dirs = cu.get_list_of_element_names(cu.open_root_file(args.input))
for mydir in dirs[:]:
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, 0.71, 0.2, 0.74, "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(0.93, 0.91, 0.94, 0.92, "NDC")
# sample_text.AddText("Flat QCD 13 TeV")
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 all flavs rsp vs pt for given eta bin
common_eta_bins = cu.get_common_eta_bins(obj_list)
for eta_bin in common_eta_bins:
entries = []
# repsonse
# for fdict in entry_dicts:
# entry = deepcopy(fdict)
# entry["graph"] = cu.grab_obj_from_file(args.input, "%s/%s_%s" % (mydir, fdict['flav'], eta_bin))
# entry["line_color"] = fdict['colour']
# entry["marker_color"] = fdict['colour']
# entries.append(entry)
# bin_title = eta_bin.replace("to", " < |#eta| < ").replace("JetEta", "")
# do_comparison_graph(entries, bin_title=bin_title,
# xtitle="p_{T}^{Gen} [GeV]", ytitle="Response", logx=True,
# xlimits=(10, 5000), y_limit_protection=(0.5, 1.5),
# other_elements=other_elements,
# output_filename=os.path.join(plot_dir, "rsp_vs_pt_%s.pdf" % (eta_bin)))
# correction
entries = []
bin_title = eta_bin.replace("to",
" < #eta < ").replace("JetEta", "")
for fdict in entry_dicts:
entry = deepcopy(fdict)
entry["graph"] = cu.grab_obj_from_file(
args.input, "%s/%s_%s" % (mydir, fdict['flav'], eta_bin))
entry["line_color"] = fdict['colour']
entry["marker_color"] = fdict['colour']
entries.append(entry)
do_comparison_graph([entry],
bin_title=bin_title,
xtitle="p_{T}^{Reco} [GeV]",
ytitle="Correction",
logx=True,
y_limit_protection=(0.7, 1.8),
other_elements=other_elements,
draw_fit_graph_ratio=True,
output_filename=os.path.join(
plot_dir, "%s_%s_logX.pdf" %
(fdict['flav'], eta_bin)))
do_comparison_graph([entry],
bin_title=bin_title,
xtitle="p_{T}^{Reco} [GeV]",
ytitle="Correction",
logx=False,
y_limit_protection=(0.7, 1.8),
other_elements=other_elements,
draw_fit_graph_ratio=True,
output_filename=os.path.join(
plot_dir, "%s_%s_linX.pdf" %
(fdict['flav'], eta_bin)))
do_comparison_graph(entries,
bin_title=bin_title,
xtitle="p_{T}^{Reco} [GeV]",
ytitle="Correction",
logx=True,
y_limit_protection=(0.7, 1.8),
other_elements=other_elements,
draw_fit_graph_ratio=True,
output_filename=os.path.join(
plot_dir,
"corr_vs_pt_%s_logX.pdf" % (eta_bin)))
do_comparison_graph(entries,
bin_title=bin_title,
xtitle="p_{T}^{Reco} [GeV]",
ytitle="Correction",
logx=False,
y_limit_protection=(0.7, 1.8),
other_elements=other_elements,
draw_fit_graph_ratio=True,
output_filename=os.path.join(
plot_dir,
"corr_vs_pt_%s_linX.pdf" % (eta_bin)))
return 0
def main(in_args):
parser = argparse.ArgumentParser()
parser.add_argument("--input",
help="Input ROOT file with correction graphs",
action='append')
parser.add_argument("--label",
help="Label for input file",
action='append')
parser.add_argument("--outputDir",
help="Output directory for plots",
default=os.getcwd())
parser.add_argument("--title", help="Title string for plots")
parser.add_argument("--chi2",
help="Do Chi2 comparison plot",
action='store_true')
parser.add_argument("--ylim", help="Set explicit y limits", nargs=2)
parser.add_argument(
"--slides",
help="Dump JSON snippet to file for use with beamer-plot-slides",
default=None)
parser.add_argument("--vertLine",
help="Add a vertical dashed line at this x value",
type=float)
args = parser.parse_args(in_args)
print(args)
if not args.input or len(args.input) == 0:
return 1
cu.check_dir_exists_create(args.outputDir)
if len(args.input) != len(args.label):
raise RuntimeError("Need a --label for each --input")
do_slides = args.slides not in (None, "")
lw = 1
entry_dicts = [
# {"flav": "AbsCorVsJetPt", "label": "All", "colour": ROOT.kBlack, "marker_style": ROOT.kFullCircle, "line_style": 2, "line_width": lw, "marker_size": 1.2},
{
"flav": "ud_AbsCorVsJetPt",
"label": "ud",
"colour": ROOT.kRed,
"marker_style": ROOT.kFullSquare,
"line_style": 1,
"line_width": lw,
"marker_size": 0.8
},
{
"flav": "g_AbsCorVsJetPt",
"label": "g",
"colour": ROOT.kAzure + 1,
"marker_style": 29,
"line_style": 1,
"line_width": lw,
"marker_size": 1.
},
{
"flav": "s_AbsCorVsJetPt",
"label": "s",
"colour": ROOT.kBlue,
"marker_style": ROOT.kFullTriangleUp,
"line_style": 1,
"line_width": lw,
"marker_size": 1.
},
{
"flav": "c_AbsCorVsJetPt",
"label": "c",
"colour": ROOT.kGreen + 2,
"marker_style": ROOT.kFullTriangleDown,
"line_style": 1,
"line_width": lw,
"marker_size": 1.
},
{
"flav": "b_AbsCorVsJetPt",
"label": "b",
"colour": ROOT.kOrange - 3,
"marker_style": ROOT.kFullDiamond,
"line_style": 1,
"line_width": lw,
"marker_size": 1.2
},
][:]
sample_str = "QCD MC"
all_dirs = [
set(cu.get_list_of_element_names(cu.open_root_file(infile)))
for infile in args.input
]
dirs = all_dirs[0]
for d in all_dirs[1:]:
dirs = dirs & d
dirs = sorted(list(dirs))[:1]
print("Doing: ", dirs)
# Loop through all different ak4pfchs, etc
slides_contents = []
for mydir in dirs:
jec_text = ROOT.TPaveText(0.15, 0.93, 0.2, 0.94, "NDC")
# jec_label = "Without JEC"
# jec_label = "With JEC"
# jec_label = "Summer16_23Sep2016V4"
# jec_label = "Summer16_03Feb2017_V8"
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, 0.78, 0.2, 0.79, "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)
other_elements = [jec_text, dir_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[0], mydir)
ylimits = (float(args.ylim[0]),
float(args.ylim[1])) if args.ylim else None
X_MIN, X_MAX = 7, None
# For limit protection:
Y_MIN, Y_MAX = 0.8, 1.6
py_herwig_ratio_title = "Parton / Hadron"
py_herwig_ratio_title = "H++ / Py8"
# Store chi2 for fits over pT
# Each entry is for a flavour,
# and is a dict of file label : chi2/dof values
fit_chi2entries = {}
for fdict in entry_dicts:
fit_chi2entries[fdict['label']] = {}
for label in args.label:
fit_chi2entries[fdict['label']][label] = []
# Do all flavs corr vs pt for given eta bin
common_eta_bins = cu.sort_human(cu.get_common_eta_bins(obj_list))
for eta_bin in common_eta_bins:
title = eta_bin.replace("to", " < #eta < ").replace("JetEta", "")
# Do a per-flavour comparison plot
outputs = []
for fdict in entry_dicts:
entries = []
chi2entries = []
for ind, (input_filename,
label) in enumerate(zip(args.input, args.label)):
entry = deepcopy(fdict)
entry["graph"] = cu.grab_obj_from_file(
input_filename,
"%s/%s_%s" % (mydir, fdict['flav'], eta_bin))
entry['label'] += " [%s]" % label
new_colour = cu.get_alternate_colour(fdict['colour'], ind)
entry["line_color"] = new_colour
entry["marker_color"] = new_colour
entry["fill_color"] = new_colour
entry["fill_style"] = 1001
entry["fill_alpha"] = 0.7
entry["ratio"] = None
if ind == 1:
entry["marker_style"] = cu.get_open_marker(
entry['marker_style'])
entry["line_style"] += 1
if ind == 2:
entry["line_style"] += 1
if ind == 3:
entry["line_style"] += 1
entry["marker_style"] = cu.get_open_marker(
entry['marker_style'])
entries.append(entry)
if ind != 0:
entries[-1]['ratio'] = entries[0]['graph']
if args.chi2:
# chi2entry = deepcopy(entry)
# chi2entry["graph"] = cu.grab_obj_from_file(input_filename, "%s/%s_%s" % (mydir, fdict['flav'].replace("corrVs", "Chi2NDoFVs"), eta_bin))
# chi2entries.append(chi2entry)
if entry['graph'].GetListOfFunctions().GetSize() > 0:
fit = entry['graph'].GetListOfFunctions().Last()
# chi2 = entry['graph'].Chisquare(fit) # can't do this as we don't want to use the plateau in chi2
chi2 = fit.GetChisquare()
ndof = fit.GetNDF()
fit_chi2entries[fdict['label']][label].append(
chi2 / ndof)
output_filename = os.path.abspath(
os.path.join(
plot_dir,
"compare_corr_vs_pt_%s_%s_funcGraphRatio.pdf" %
(eta_bin, fdict['label'])))
cu.do_comparison_graph(
entries,
title=title,
sample_title=sample_str,
xtitle="p_{T}^{Reco} [GeV]",
ytitle="Correction",
logx=True,
xlimits=(X_MIN, X_MAX),
# xlimits=None,
y_limit_protection=(Y_MIN, Y_MAX),
ylimits=ylimits,
other_elements=other_elements,
output_filename=output_filename,
vertical_line=args.vertLine,
do_fit_graph_ratio=True)
outputs.append(output_filename)
output_filename = os.path.abspath(
os.path.join(
plot_dir,
"compare_corr_vs_pt_%s_%s_pyHerwigRatio.pdf" %
(eta_bin, fdict['label'])))
cu.do_comparison_graph(
entries,
title=title,
sample_title=sample_str,
xtitle="p_{T}^{Reco} [GeV]",
ytitle="Correction",
logx=True,
xlimits=(X_MIN, X_MAX),
# xlimits=None,
y_limit_protection=(Y_MIN, Y_MAX),
ylimits=ylimits,
other_elements=other_elements,
output_filename=output_filename,
vertical_line=args.vertLine,
draw_fits=True,
do_ratio_plots=True,
ratio_title=py_herwig_ratio_title)
output_filename = os.path.abspath(
os.path.join(
plot_dir, "compare_corr_vs_pt_%s_%s_pull.pdf" %
(eta_bin, fdict['label'])))
cu.do_comparison_graph(
entries,
title=title,
sample_title=sample_str,
xtitle="p_{T}^{Reco} [GeV]",
ytitle="Correction",
logx=True,
xlimits=(X_MIN, X_MAX),
# xlimits=None,
y_limit_protection=(Y_MIN, Y_MAX),
ylimits=ylimits,
other_elements=other_elements,
output_filename=output_filename,
vertical_line=args.vertLine,
do_fit_graph_pull=True)
# if args.chi2:
# cu.do_comparison_graph(chi2entries, title=title, sample_title=sample_str,
# xtitle="p_{T}^{Reco} [GeV]", ytitle="#chi^{2}/N_{DoF}", logx=True,
# xlimits=(X_MIN, X_MAX),
# other_elements=other_elements,
# output_filename=os.path.join(plot_dir, "compare_corr_vs_pt_%s_%s_chi2.pdf" % (eta_bin, fdict['label'])))
# Do a plot with all flavours
entries = []
ud_entries, g_entries = [], []
for fdict in entry_dicts[:]:
for ind, (input_filename,
label) in enumerate(zip(args.input, args.label)):
entry = deepcopy(fdict)
entry["graph"] = cu.grab_obj_from_file(
input_filename,
"%s/%s_%s" % (mydir, fdict['flav'], eta_bin))
entry['label'] += " [%s]" % label
new_colour = cu.get_alternate_colour(fdict['colour'], ind)
entry["line_color"] = new_colour
entry["marker_color"] = new_colour
entry["fill_color"] = new_colour
entry["fill_style"] = 1001
entry["fill_alpha"] = 0.8
entry['ratio'] = None
if ind == 1:
entry["marker_style"] = cu.get_open_marker(
entry['marker_style'])
entry["line_style"] += 1
if ind == 2:
entry["line_style"] += 1
if ind == 3:
entry["line_style"] += 1
entry["marker_style"] = cu.get_open_marker(
entry['marker_style'])
entries.append(entry)
if fdict['label'] == "ud":
ud_entries.append(entry)
elif fdict['label'] == "g":
g_entries.append(entry)
if ind > 0:
entries[-1]['ratio'] = entries[-2]['graph']
title = eta_bin.replace("to", " < #eta < ").replace("JetEta", "")
output_filename = os.path.abspath(
os.path.join(
plot_dir,
"compare_corr_vs_pt_%s_allFlavs_funcGraphRatio.pdf" %
(eta_bin)))
cu.do_comparison_graph(entries,
title=title,
sample_title=sample_str,
xtitle="p_{T}^{Reco} [GeV]",
ytitle="Correction",
logx=True,
xlimits=(X_MIN, X_MAX),
y_limit_protection=(Y_MIN, Y_MAX),
ylimits=ylimits,
other_elements=other_elements,
output_filename=output_filename,
vertical_line=args.vertLine,
do_fit_graph_ratio=True)
outputs.insert(0, output_filename)
output_filename = os.path.abspath(
os.path.join(
plot_dir,
"compare_corr_vs_pt_%s_allFlavs_pyHerwigRatio.pdf" %
(eta_bin)))
cu.do_comparison_graph(entries,
title=title,
sample_title=sample_str,
xtitle="p_{T}^{Reco} [GeV]",
ytitle="Correction",
logx=True,
xlimits=(X_MIN, X_MAX),
y_limit_protection=(Y_MIN, Y_MAX),
ylimits=ylimits,
other_elements=other_elements,
output_filename=output_filename,
vertical_line=args.vertLine,
draw_fits=True,
do_ratio_plots=True,
ratio_title=py_herwig_ratio_title)
# make 1 slide with all flavours for this eta bin
if do_slides:
plots = ",\n".join([
' ["{{{fname}}}{ext}", "{title}"]'.format(
fname=os.path.splitext(fname)[0],
ext=os.path.splitext(fname)[1],
title="") for fname in outputs
])
text = """ {{
"title": "${thistitle}$",
"plots": [
{plots}
]
}}""".format(thistitle=title.replace("#", r"\\"), plots=plots)
slides_contents.append(text)
if args.chi2:
# for each flav, do a plot of chi2 of total fit vs eta for all files
all_entries = []
all_ymax = 0
for fdict in entry_dicts:
entries = []
file_labels = list(fit_chi2entries[fdict['label']].keys())
ymax = 0
for ind, flabel in enumerate(file_labels):
eta_bins = [get_eta_mid(x) for x in common_eta_bins]
y = fit_chi2entries[fdict['label']][flabel]
ymax = max(ymax, max(y))
ey = [0] * len(y)
ex = [get_eta_half_width(x) for x in common_eta_bins]
gr = ROOT.TGraphErrors(len(y), array('d', eta_bins),
array('d', y), array('d', ex),
array('d', ey))
entry = deepcopy(fdict)
entry["graph"] = gr
entry['label'] = "%s [%s]" % (fdict['label'], flabel)
new_colour = cu.get_alternate_colour(fdict['colour'], ind)
entry["line_color"] = new_colour
entry["marker_color"] = new_colour
entry["fill_color"] = new_colour
entry["fill_style"] = 1001
entry["fill_alpha"] = 0.8
if ind == 1:
entry["marker_style"] = cu.get_open_marker(
entry['marker_style'])
entry["line_style"] += 1
if ind == 2:
entry["line_style"] += 1
if ind == 3:
entry["line_style"] += 1
entry["marker_style"] = cu.get_open_marker(
entry['marker_style'])
entries.append(entry)
all_ymax = max(all_ymax, ymax)
ylimits = [0, ymax * 1.3]
# if ylimits[1] > 20:
# ylimits[1] = 20
output_filename = os.path.abspath(
os.path.join(
plot_dir,
"compare_chi2_vs_eta_%s.pdf" % (fdict['label'])))
cu.do_comparison_graph(entries,
title="",
sample_title=sample_str,
xtitle="#eta^{Reco}",
ytitle="#chi^{2} / N_{dof}",
draw_opt="ALP",
ylimits=ylimits,
other_elements=other_elements,
output_filename=output_filename)
all_entries.extend(entries)
# do a single plot with all flavs
ylimits = [0, all_ymax * 1.3]
if ylimits[1] > 20:
ylimits[1] = 20
output_filename = os.path.abspath(
os.path.join(plot_dir, "compare_chi2_vs_eta_allFlavs.pdf"))
cu.do_comparison_graph(all_entries,
title="",
sample_title=sample_str,
xtitle="#eta^{Reco}",
ytitle="#chi^{2} / N_{dof}",
draw_opt="ALP",
ylimits=ylimits,
other_elements=other_elements,
output_filename=output_filename)
# diff_entries = []
# for ind, (ud, g, label) in enumerate(zip(ud_entries, g_entries, args.label)):
# diff_graph = construct_difference_graph(ud['graph'], g['graph'])
# diff = deepcopy(ud)
# diff['graph'] = diff_graph
# diff['label'] = label
# diff_entries.append(diff)
# cu.do_comparison_graph(diff_entries, title=title, sample_title=sample_str,
# xtitle="p_{T}^{Reco} [GeV]", ytitle="Correction (ud) - Correction (g)", logx=True,
# xlimits=(X_MIN, X_MAX), ylimits=(0, 0.08),
# other_elements=other_elements,
# output_filename=os.path.join(plot_dir, "compare_corr_vs_pt_%s_ud_g_diff.pdf" % (eta_bin)))
# # Do all flavs corr vs eta for given pt bin
# common_pt_bins = cu.sort_human(cu.get_common_pt_bins(obj_list))
# for pt_bin in common_pt_bins:
# # Do a per-flavour comparison plot
# for fdict in entry_dicts:
# entries = []
# chi2entries = []
# for ind, (input_filename, label) in enumerate(zip(args.input, args.label)):
# entry = deepcopy(fdict)
# entry["graph"] = cu.grab_obj_from_file(input_filename, "%s/%s_%s" % (mydir, fdict['flav'].replace("RefPt", "JetEta"), pt_bin))
# entry['label'] += " [%s]" % label
# entry["line_color"] = fdict['colour']
# entry["marker_color"] = fdict['colour']
# if ind == 1:
# entry["marker_style"] = cu.get_open_marker(entry['marker_style'])
# if ind == 2:
# entry["line_style"] += 1
# if ind == 3:
# entry["line_style"] += 1
# entry["marker_style"] = cu.get_open_marker(entry['marker_style'])
# entries.append(entry)
# if args.chi2:
# chi2entry = deepcopy(entry)
# chi2entry["graph"] = cu.grab_obj_from_file(input_filename, "%s/%s_%s" % (mydir, fdict['flav'].replace("RefPt", "JetEta").replace("corrVs", "Chi2NDoFVs"), pt_bin))
# chi2entries.append(chi2entry)
# title = pt_bin.replace("to", " < p_{T} < ").replace("RefPt", "")
# cu.do_comparison_graph(entries, title=title + " GeV", sample_title=sample_str,
# xtitle="|#eta|", ytitle="Correction",
# xlimits=(0, 5.2), y_limit_protection=(Y_MIN, Y_MAX),
# other_elements=other_elements, ylimits=ylimits,
# output_filename=os.path.join(plot_dir, "compare_corr_vs_eta_%s_%s.pdf" % (pt_bin, fdict['label'])))
# if args.chi2:
# cu.do_comparison_graph(entries, title=title, sample_title=sample_str,
# xtitle="|#eta|", ytitle="#chi^{2}/N_{DoF}",
# xlimits=(0, 5.2),
# other_elements=other_elements,
# output_filename=os.path.join(plot_dir, "compare_corr_vs_eta_%s_%s_chi2.pdf" % (pt_bin, fdict['label'])))
# # Do a plot with all flavours
# entries = []
# for fdict in entry_dicts:
# for ind, (input_filename, label) in enumerate(zip(args.input, args.label)):
# entry = deepcopy(fdict)
# entry["graph"] = cu.grab_obj_from_file(input_filename, "%s/%s_%s" % (mydir, fdict['flav'].replace("RefPt", "JetEta"), pt_bin))
# entry['label'] += " [%s]" % label
# entry["line_color"] = fdict['colour']
# entry["marker_color"] = fdict['colour']
# if ind == 1:
# entry["marker_style"] = cu.get_open_marker(entry['marker_style'])
# if ind == 2:
# entry["line_style"] += 1
# if ind == 3:
# entry["line_style"] += 1
# entry["marker_style"] = cu.get_open_marker(entry['marker_style'])
# entries.append(entry)
# title = pt_bin.replace("to", " < p_{T} < ").replace("RefPt", "")
# cu.do_comparison_graph(entries, title=title + " GeV", sample_title=sample_str,
# xtitle="|#eta|", ytitle="Correction",
# xlimits=(0, 5.2), y_limit_protection=(Y_MIN, Y_MAX),
# other_elements=other_elements, ylimits=ylimits,
# output_filename=os.path.join(plot_dir, "compare_corr_vs_eta_%s_allFlavs.pdf" % (pt_bin)))
if do_slides:
print("Writing JSON to", args.slides)
with open(args.slides, "w") as fout:
fout.write(",\n".join(slides_contents))
return 0
def main(in_args):
parser = argparse.ArgumentParser()
parser.add_argument(
"--input",
help=
"Input ROOT file with response & resolution graphs (from jet_response_and_resolution_x)",
action='append')
parser.add_argument("--label",
help="Label for input file",
action='append')
parser.add_argument("--outputDir",
help="Output directory for plots",
default=os.getcwd())
parser.add_argument("--title", help="Title string for plots")
parser.add_argument("--chi2",
help="Do Chi2 comparison plot",
action='store_true')
parser.add_argument("--ylim", help="Set explicit y limits", nargs=2)
args = parser.parse_args(in_args)
cu.check_dir_exists_create(args.outputDir)
if len(args.input) != len(args.label):
raise RuntimeError("Need a --label for each --input")
if args.input:
lw = 2
entry_dicts = [
{
"flav": "RelRspVsRefPt",
"label": "All",
"colour": ROOT.kBlack,
"marker_style": ROOT.kFullCircle,
"line_style": 2,
"line_width": lw,
"marker_size": 1.2
},
{
"flav": "ud_RspVsRefPt_RelRsp",
"label": "ud",
"colour": ROOT.kRed,
"marker_style": ROOT.kFullSquare,
"line_style": 1,
"line_width": lw,
"marker_size": 1.2
},
{
"flav": "s_RRspVsRefPt_RelRsp",
"label": "s",
"colour": ROOT.kBlue,
"marker_style": ROOT.kFullTriangleUp,
"line_style": 1,
"line_width": lw,
"marker_size": 1.4
},
{
"flav": "c_RRspVsRefPt_RelRsp",
"label": "c",
"colour": ROOT.kGreen + 2,
"marker_style": ROOT.kFullTriangleDown,
"line_style": 1,
"line_width": lw,
"marker_size": 1.4
},
{
"flav": "b_RRspVsRefPt_RelRsp",
"label": "b",
"colour": ROOT.kOrange - 3,
"marker_style": ROOT.kFullDiamond,
"line_style": 1,
"line_width": lw,
"marker_size": 1.6
},
{
"flav": "g_RRspVsRefPt_RelRsp",
"label": "g",
"colour": ROOT.kAzure + 1,
"marker_style": 29,
"line_style": 1,
"line_width": lw,
"marker_size": 1.8
},
]
all_dirs = [
set(cu.get_list_of_element_names(cu.open_root_file(infile)))
for infile in args.input
]
dirs = all_dirs[0]
for d in all_dirs[1:]:
dirs = dirs & d
dirs = sorted(list(dirs))[:1]
print("Doing: ", dirs)
# Loop through all different ak4pfchs, etc
for mydir in dirs:
jec_text = ROOT.TPaveText(0.17, 0.91, 0.2, 0.92, "NDC")
jec_label = "Without JEC"
# jec_label = "With JEC"
# jec_label = "Summer16_23Sep2016V4"
# jec_label = "Summer16_03Feb2017_V8"
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, 0.76, 0.2, 0.77, "NDC")
dir_label = mydir.upper().replace("PFCHS", " PF CHS").replace(
"PUPPI", " PUPPI").replace("L1L2L3", " + L1L2L3")
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)
other_elements = [jec_text, dir_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[0], mydir)
ylimits = (float(args.ylim[0]),
float(args.ylim[1])) if args.ylim else None
# Do all flavs rsp vs pt for given eta bin
common_eta_bins = cu.get_common_eta_bins(obj_list)
for eta_bin in common_eta_bins:
# Do a per-flavour comparison plot
for fdict in entry_dicts:
entries = []
chi2entries = []
for ind, (input_filename,
label) in enumerate(zip(args.input, args.label)):
entry = deepcopy(fdict)
entry["graph"] = cu.grab_obj_from_file(
input_filename,
"%s/%s_%s" % (mydir, fdict['flav'], eta_bin))
entry['label'] += " [%s]" % label
entry["line_color"] = fdict['colour']
entry["marker_color"] = fdict['colour']
if ind == 1:
entry["marker_style"] = get_open_marker(
entry['marker_style'])
if ind == 2:
entry["line_style"] += 1
if ind == 3:
entry["line_style"] += 1
entry["marker_style"] = get_open_marker(
entry['marker_style'])
entries.append(entry)
if args.chi2:
chi2entry = deepcopy(entry)
chi2entry["graph"] = cu.grab_obj_from_file(
input_filename,
"%s/%s_%s" % (mydir, fdict['flav'].replace(
"RspVs", "Chi2NDoFVs"), eta_bin))
chi2entries.append(chi2entry)
title = eta_bin.replace("to", " < |#eta| < ").replace(
"JetEta", "")
do_comparison_graph(entries,
title=title,
xtitle="p_{T}^{Gen} [GeV]",
ytitle="Response",
logx=True,
xlimits=(10, 3000),
y_limit_protection=(0.7, 1.4),
ylimits=ylimits,
other_elements=other_elements,
output_filename=os.path.join(
plot_dir,
"compare_rsp_vs_pt_%s_%s.pdf" %
(eta_bin, fdict['label'])))
if args.chi2:
do_comparison_graph(
chi2entries,
title=title,
xtitle="p_{T}^{Gen} [GeV]",
ytitle="#chi^{2}/N_{DoF}",
logx=True,
xlimits=(10, 3000),
other_elements=other_elements,
output_filename=os.path.join(
plot_dir, "compare_rsp_vs_pt_%s_%s_chi2.pdf" %
(eta_bin, fdict['label'])))
# Do a plot with all flavours
entries = []
ud_entries, g_entries = [], []
for fdict in entry_dicts:
for ind, (input_filename,
label) in enumerate(zip(args.input, args.label)):
entry = deepcopy(fdict)
entry["graph"] = cu.grab_obj_from_file(
input_filename,
"%s/%s_%s" % (mydir, fdict['flav'], eta_bin))
entry['label'] += " [%s]" % label
entry["line_color"] = fdict['colour']
entry["marker_color"] = fdict['colour']
if ind == 1:
entry["marker_style"] = get_open_marker(
entry['marker_style'])
if ind == 2:
entry["line_style"] += 1
if ind == 3:
entry["line_style"] += 1
entry["marker_style"] = get_open_marker(
entry['marker_style'])
entries.append(entry)
if fdict['label'] == "ud":
ud_entries.append(entry)
elif fdict['label'] == "g":
g_entries.append(entry)
title = eta_bin.replace("to",
" < |#eta| < ").replace("JetEta", "")
do_comparison_graph(
entries,
title=title,
xtitle="p_{T}^{Gen} [GeV]",
ytitle="Response",
logx=True,
xlimits=(10, 3000),
y_limit_protection=(0.7, 1.4),
other_elements=other_elements,
output_filename=os.path.join(
plot_dir,
"compare_rsp_vs_pt_%s_allFlavs.pdf" % (eta_bin)))
# diff_entries = []
# for ind, (ud, g, label) in enumerate(zip(ud_entries, g_entries, args.label)):
# diff_graph = construct_difference_graph(ud['graph'], g['graph'])
# diff = deepcopy(ud)
# diff['graph'] = diff_graph
# diff['label'] = label
# diff_entries.append(diff)
# do_comparison_graph(diff_entries, title=title,
# xtitle="p_{T}^{Gen} [GeV]", ytitle="Response (ud) - response (g)", logx=True,
# xlimits=(10, 3000), ylimits=(0, 0.08),
# other_elements=other_elements,
# output_filename=os.path.join(plot_dir, "compare_rsp_vs_pt_%s_ud_g_diff.pdf" % (eta_bin)))
return
# Do all flavs rsp vs eta for given pt bin
common_pt_bins = cu.get_common_pt_bins(obj_list)
for pt_bin in common_pt_bins:
# Do a per-flavour comparison plot
for fdict in entry_dicts:
entries = []
chi2entries = []
for ind, (input_filename,
label) in enumerate(zip(args.input, args.label)):
entry = deepcopy(fdict)
entry["graph"] = cu.grab_obj_from_file(
input_filename,
"%s/%s_%s" % (mydir, fdict['flav'].replace(
"RefPt", "JetEta"), pt_bin))
entry['label'] += " [%s]" % label
entry["line_color"] = fdict['colour']
entry["marker_color"] = fdict['colour']
if ind == 1:
entry["marker_style"] = get_open_marker(
entry['marker_style'])
if ind == 2:
entry["line_style"] += 1
if ind == 3:
entry["line_style"] += 1
entry["marker_style"] = get_open_marker(
entry['marker_style'])
entries.append(entry)
if args.chi2:
chi2entry = deepcopy(entry)
chi2entry["graph"] = cu.grab_obj_from_file(
input_filename,
"%s/%s_%s" % (mydir, fdict['flav'].replace(
"RefPt", "JetEta").replace(
"RspVs", "Chi2NDoFVs"), pt_bin))
chi2entries.append(chi2entry)
title = pt_bin.replace("to",
" < p_{T} < ").replace("RefPt", "")
do_comparison_graph(entries,
title=title + " GeV",
xtitle="|#eta|",
ytitle="Response",
xlimits=(0, 5.2),
y_limit_protection=(0.8, 1.4),
other_elements=other_elements,
ylimits=ylimits,
output_filename=os.path.join(
plot_dir,
"compare_rsp_vs_eta_%s_%s.pdf" %
(pt_bin, fdict['label'])))
if args.chi2:
do_comparison_graph(
entries,
title=title,
xtitle="|#eta|",
ytitle="#chi^{2}/N_{DoF}",
xlimits=(0, 5.2),
other_elements=other_elements,
output_filename=os.path.join(
plot_dir, "compare_rsp_vs_eta_%s_%s_chi2.pdf" %
(pt_bin, fdict['label'])))
# Do a plot with all flavours
entries = []
for fdict in entry_dicts:
for ind, (input_filename,
label) in enumerate(zip(args.input, args.label)):
entry = deepcopy(fdict)
entry["graph"] = cu.grab_obj_from_file(
input_filename,
"%s/%s_%s" % (mydir, fdict['flav'].replace(
"RefPt", "JetEta"), pt_bin))
entry['label'] += " [%s]" % label
entry["line_color"] = fdict['colour']
entry["marker_color"] = fdict['colour']
if ind == 1:
entry["marker_style"] = get_open_marker(
entry['marker_style'])
if ind == 2:
entry["line_style"] += 1
if ind == 3:
entry["line_style"] += 1
entry["marker_style"] = get_open_marker(
entry['marker_style'])
entries.append(entry)
title = pt_bin.replace("to",
" < p_{T} < ").replace("RefPt", "")
do_comparison_graph(
entries,
title=title + " GeV",
xtitle="|#eta|",
ytitle="Response",
xlimits=(0, 5.2),
y_limit_protection=(0.8, 1.4),
other_elements=other_elements,
ylimits=ylimits,
output_filename=os.path.join(
plot_dir,
"compare_rsp_vs_eta_%s_allFlavs.pdf" % (pt_bin)))
return 0
def main(in_args):
parser = argparse.ArgumentParser()
parser.add_argument("--input", help="Input ROOT file with response & resolution graphs (from jet_response_and_resolution_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="")
args = parser.parse_args(in_args)
cu.check_dir_exists_create(args.outputDir)
lw = 2
entry_dicts = [
{"flav": "RelRspVsRefPt", "label": "All", "colour": ROOT.kBlack, "marker_style": ROOT.kFullCircle, "line_style": 2, "line_width": lw, "marker_size": 1.2},
{"flav": "ud_RspVsRefPt_RelRsp", "label": "ud", "colour": ROOT.kRed, "marker_style": ROOT.kFullSquare, "line_style": 1, "line_width": lw, "marker_size": 1.2},
{"flav": "s_RRspVsRefPt_RelRsp", "label": "s", "colour": ROOT.kBlue, "marker_style": ROOT.kFullTriangleUp, "line_style": 1, "line_width": lw, "marker_size": 1.4},
{"flav": "c_RRspVsRefPt_RelRsp", "label": "c", "colour": ROOT.kGreen+2, "marker_style": ROOT.kFullTriangleDown, "line_style": 1, "line_width": lw, "marker_size": 1.4},
{"flav": "b_RRspVsRefPt_RelRsp", "label": "b", "colour": ROOT.kOrange-3, "marker_style": ROOT.kFullDiamond, "line_style": 1, "line_width": lw, "marker_size": 1.6},
{"flav": "g_RRspVsRefPt_RelRsp", "label": "g", "colour": ROOT.kAzure+1, "marker_style": 29, "line_style": 1, "line_width": lw, "marker_size": 1.8},
]
# no JEC
eta_bin_limits = {
'JetEta0to0.783': (0.9, 1.15),
'JetEta0.783to1.305': None,
'JetEta1.305to1.93': (0.85, 1.05),
'JetEta1.93to2.5': None,
'JetEta2.5to2.964': None,
'JetEta2.964to3.139': None,
'JetEta3.139to5.191': (0.98, 1.8),
}
eta_bin_ratio_limits = {
'JetEta0to0.783': (0.96, 1.07),
'JetEta0.783to1.305': None,
'JetEta1.305to1.93': (0.95, 1.07),
'JetEta1.93to2.5': None,
'JetEta2.5to2.964': None,
'JetEta2.964to3.139': None,
'JetEta3.139to5.191': (0.93, 1.1),
}
# with L1 JEC
# eta_bin_limits = {
# 'JetEta0to0.783': (0.76, 1.05),
# 'JetEta0.783to1.305': (0.77, 1),
# 'JetEta1.305to1.93': (0.7, 1.),
# 'JetEta1.93to2.5': (0.68, 1.1),
# 'JetEta2.5to2.964': (0.55, 1.1),
# 'JetEta2.964to3.139': (0.6, 1.1),
# 'JetEta3.139to5.191': (0.75, 1.1),
# }
# eta_bin_ratio_limits = {
# 'JetEta0to0.783': (0.96, 1.08),
# 'JetEta0.783to1.305': (0.96, 1.08),
# 'JetEta1.305to1.93': (0.95, 1.09),
# 'JetEta1.93to2.5': (0.95, 1.13),
# 'JetEta2.5to2.964': (0.93, 1.15),
# 'JetEta2.964to3.139': (0.9, 1.12),
# 'JetEta3.139to5.191': (0.93, 1.1),
# }
# default
# eta_bin_limits = {
# 'JetEta0to0.783': None,
# 'JetEta0.783to1.305': None,
# 'JetEta1.305to1.93': None,
# 'JetEta1.93to2.5': None,
# 'JetEta2.5to2.964': None,
# 'JetEta2.964to3.139': None,
# 'JetEta3.139to5.191': None,
# }
# eta_bin_ratio_limits = {
# 'JetEta0to0.783': None,
# 'JetEta0.783to1.305': None,
# 'JetEta1.305to1.93': None,
# 'JetEta1.93to2.5': None,
# 'JetEta2.5to2.964': None,
# 'JetEta2.964to3.139': None,
# 'JetEta3.139to5.191': None,
# }
# Loop through all different ak4pfchs, etc
dirs = cu.get_list_of_element_names(cu.open_root_file(args.input))
for mydir in dirs[:]:
jec_text = ROOT.TPaveText(0.14, 0.93, 0.2, 0.96, "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, 0.75, 0.2, 0.77, "NDC")
dir_label = mydir.upper().replace("PFCHS", " PF CHS").replace("PUPPI", " PUPPI").replace("L1L2L3", " + L1L2L3")
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(0.94, 0.93, 0.95, 0.96, "NDC")
# sample_text.AddText("Flat QCD 13 TeV")
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 all flavs rsp vs pt for given eta bin
common_eta_bins = cu.sort_human(cu.get_common_eta_bins(obj_list))
for eta_bin in common_eta_bins[:]:
entries = []
contributions = []
for fdict in entry_dicts:
entry = deepcopy(fdict)
# entry["graph"] = cu.grab_obj_from_file(args.input, "%s/%s_%s" % (mydir, fdict['flav'], eta_bin))
entry["obj"] = cu.grab_obj_from_file(args.input, "%s/%s_%s" % (mydir, fdict['flav'], eta_bin))
entry["line_color"] = fdict['colour']
entry["marker_color"] = fdict['colour']
# entries.append(entry)
del entry['flav']
del entry['colour']
this_contrib = Contribution(**entry)
contributions.append(this_contrib)
bin_title = eta_bin.replace("to", " < |#eta| < ").replace("JetEta", "")
do_comparison_graph(contributions, bin_title=bin_title,
xtitle="p_{T}^{Gen} [GeV]", ytitle="Response", logx=True,
xlimits=(10, 5000),
ylimits=eta_bin_limits.get(eta_bin, None),
y_limit_protection=(0.5, 1.7),
other_elements=other_elements,
output_filename=os.path.join(plot_dir, "rsp_vs_pt_%s.pdf" % (eta_bin)),
ratio_limits=eta_bin_ratio_limits.get(eta_bin, None)
)
# Inverse response ie ~ correction
# entries = []
# for fdict in entry_dicts:
# entry = deepcopy(fdict)
# entry["graph"] = construct_inverse_graph(cu.grab_obj_from_file(args.input, "%s/%s_%s" % (mydir, fdict['flav'], eta_bin)))
# entry["line_color"] = fdict['colour']
# entry["marker_color"] = fdict['colour']
# entries.append(entry)
# bin_title = eta_bin.replace("to", " < |#eta| < ").replace("JetEta", "")
# do_comparison_graph(entries, bin_title=bin_title,
# xtitle="p_{T}^{Gen} [GeV]", ytitle="1/Response", logx=True,
# y_limit_protection=(0.8, 1.2),
# other_elements=other_elements,
# output_filename=os.path.join(plot_dir, "inv_rsp_vs_pt_%s.pdf" % (eta_bin)))
# Do all flavs rsp vs eta for given pt bin
# common_pt_bins = cu.get_common_pt_bins(obj_list)
# for pt_bin in common_pt_bins:
# entries = []
# contributions = []
# for fdict in entry_dicts:
# entry = deepcopy(fdict)
# # entry["graph"] = cu.grab_obj_from_file(args.input, "%s/%s_%s" % (mydir, fdict['flav'].replace("RefPt", "JetEta"), pt_bin))
# entry["obj"] = cu.grab_obj_from_file(args.input, "%s/%s_%s" % (mydir, fdict['flav'].replace("RefPt", "JetEta"), pt_bin))
# entry["line_color"] = fdict['colour']
# entry["marker_color"] = fdict['colour']
# # entries.append(entry)
# del entry['flav']
# del entry['colour']
# this_contrib = Contribution(**entry)
# contributions.append(this_contrib)
# bin_title = pt_bin.replace("to", " < p_{T} < ").replace("RefPt", "")
# do_comparison_graph(contributions, bin_title=bin_title + " GeV",
# xtitle="|#eta|", ytitle="Response",
# xlimits=(0, 5.2), y_limit_protection=(0.5, 1.5),
# other_elements=other_elements,
# output_filename=os.path.join(plot_dir, "rsp_vs_eta_%s.pdf" % (pt_bin)))
# Inverse response ie ~ correction
# entries = []
# for fdict in entry_dicts:
# entry = deepcopy(fdict)
# entry["graph"] = construct_inverse_graph(cu.grab_obj_from_file(args.input, "%s/%s_%s" % (mydir, fdict['flav'].replace("RefPt", "JetEta"), pt_bin)))
# entry["line_color"] = fdict['colour']
# entry["marker_color"] = fdict['colour']
# entries.append(entry)
# bin_title = pt_bin.replace("to", " < p_{T} < ").replace("RefPt", "")
# do_comparison_graph(entries, bin_title=bin_title + " GeV",
# xtitle="|#eta|", ytitle="1/Response",
# y_limit_protection=(0.8, 1.6),
# other_elements=other_elements,
# output_filename=os.path.join(plot_dir, "inv_rsp_vs_eta_%s.pdf" % (pt_bin)))
# Do all flavs resolution vs pt for given eta bin
# for eta_bin in common_eta_bins:
# entries = []
# for fdict in entry_dicts:
# entry = deepcopy(fdict)
# entry["graph"] = cu.grab_obj_from_file(args.input, "%s/%s_%s" % (mydir, fdict['flav'].replace("Rsp", "Res", 1), eta_bin))
# entry["line_color"] = fdict['colour']
# entry["marker_color"] = fdict['colour']
# entries.append(entry)
# bin_title = eta_bin.replace("to", " < |#eta| < ").replace("JetEta", "")
# do_comparison_graph(entries, bin_title=bin_title,
# xtitle="p_{T}^{Gen} [GeV]", ytitle="Relative resolution", logx=True,
# y_limit_protection=(0, 0.5), draw_fits=False,
# ylimits=(0, 0.5),
# xlimits=(10, 5000), other_elements=other_elements,
# output_filename=os.path.join(plot_dir, "res_vs_pt_%s.pdf" % (eta_bin)))
# Do all flavs resolution plots vs eta for given pt bin
# for pt_bin in common_pt_bins:
# entries = []
# for fdict in entry_dicts:
# entry = deepcopy(fdict)
# entry["graph"] = cu.grab_obj_from_file(args.input, "%s/%s_%s" % (mydir, fdict['flav'].replace("Rsp", "Res", 1).replace("RefPt", "JetEta"), pt_bin))
# entry["line_color"] = fdict['colour']
# entry["marker_color"] = fdict['colour']
# entries.append(entry)
# bin_title = pt_bin.replace("to", " < p_{T} < ").replace("RefPt", "")
# do_comparison_graph(entries, bin_title=bin_title + " GeV",
# xtitle="|#eta|", ytitle="Relative resolution", other_elements=other_elements,
# y_limit_protection=(0, 0.5), draw_fits=True, xlimits=(0, 5.2),
# output_filename=os.path.join(plot_dir, "res_vs_eta_%s.pdf" % (pt_bin)))
return 0
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)