def plot_exclusion(path, region, outdir):
#set_default_style()
set_atlas_style()
ROOT.gStyle.SetLegendFont(42)
# input files
if sig_xs_syst:
file_name = path + '/Output_fixSigXSecNominal_hypotest__1_harvest_list.root'
file_name_high = path + '/Output_fixSigXSecUp_hypotest__1_harvest_list.root'
file_name_low = path + '/Output_fixSigXSecDown_hypotest__1_harvest_list.root'
else:
file_name = path + '/Output_hypotest__1_harvest_list.root'
# Get histograms
## obs CLs (Nominal, Low, High)
sigp1clsf = return_contour95('sigp1clsf', file_name)
if sig_xs_syst:
sigp1clsfLow = return_contour95('sigp1clsf', file_name_low)
sigp1clsfHigh = return_contour95('sigp1clsf', file_name_high)
sigp1clsfLow.SetName('sigp1clsfLow')
sigp1clsfLow.SetTitle('sigp1clsfLow')
sigp1clsfHigh.SetName('sigp1clsfHigh')
sigp1clsfHigh.SetTitle('sigp1clsfHigh')
sigp1expclsf = return_contour95('sigp1expclsf', file_name)
sigclsu1s = return_contour95('sigclsu1s', file_name)
sigclsd1s = return_contour95('sigclsd1s', file_name)
graph_sigp1clsf = convert_hist_to_graph(sigp1clsf)
if sig_xs_syst:
graph_sigp1clsfLow = convert_hist_to_graph(sigp1clsfLow)
graph_sigp1clsfHigh = convert_hist_to_graph(sigp1clsfHigh)
graph_sigp1expclsf = convert_hist_to_graph(sigp1expclsf)
graph_sigclsu1s = convert_hist_to_graph(sigclsu1s)
graph_sigclsd1s = convert_hist_to_graph(sigclsd1s)
# Colours
c_yellow = ROOT.TColor.GetColor('#ffe938')
c_red = ROOT.TColor.GetColor('#aa0000')
c_blue = ROOT.TColor.GetColor('#28373c')
frame = draw_grid_frame(xmin=1146, xmax=2550, ymin=147, ymax=2550)
# Create the text in the plot
# DATA info
leg1 = ROOT.TLatex()
leg1.SetNDC()
leg1.SetTextSize(0.035)
leg1.SetTextColor(1)
if args.datalabel is not None:
leg1.DrawLatex(0.15, 0.7, args.datalabel)
else:
leg1.DrawLatex(0.15, 0.7, style.data_label)
# if style.atlas_label:
# leg1.SetTextSize(0.04)
# leg1.DrawLatex(1810, 230, style.atlas_label)
# Signal Regions label
leg3 = ROOT.TLatex()
leg3.SetNDC()
leg3.SetTextSize(0.035)
leg3.SetTextColor(1)
leg3.SetTextFont(42)
region_text = region
if 'SRL,SRH' in region_text or 'SRiL,SRiH' in region_text:
region_text = region_text = 'SR_{L} and SR_{H}'
elif 'SRL' in region_text or 'SRiL' in region_text:
region_text = 'SR_{L}'
elif 'SRH' in region_text or 'SRiH' in region_text:
region_text = 'SR_{H}'
leg3.DrawLatex(0.15, 0.63, region_text)
# Legend
leg = ROOT.TLegend(0.15, 0.77, 0.49, 0.92)
leg.SetFillColor(0)
leg.SetBorderSize(0)
# extra text
leg4 = ROOT.TLatex()
leg4.SetNDC()
leg4.SetTextSize(0.03)
leg4.SetTextColor(1)
leg4.SetTextAngle(90)
if (args.obscls or args.expcls or args.bestsr):
leg4.SetTextColor(ROOT.kGray+2)
textx = 0.98
texty = 0.12
if args.obscls:
leg4.DrawLatex(textx, texty, 'Numbers give observed CL_{s} values')
elif args.expcls:
leg4.DrawLatex(textx, texty, 'Numbers give expected CL_{s} values')
elif args.bestsr:
leg4.DrawLatex(textx, texty, 'Labels indicate best-expected SR')
# leg2 = ROOT.TLatex()
# leg2.SetNDC()
# leg2.SetTextSize(0.03)
# leg2.SetTextColor(1)
# leg2.DrawLatex(0.17, 0.75, "All limits at 95% CL")
graph_sigp1clsf.SetFillColor(ROOT.kWhite)
graph_sigp1clsf.SetFillStyle(3003)
graph_sigp1clsf.SetLineColor(c_red)
graph_sigp1clsf.SetLineStyle(1)
graph_sigp1clsf.SetLineWidth(3)
if sig_xs_syst:
graph_sigp1clsfHigh.SetFillColor(ROOT.kWhite)
graph_sigp1clsfHigh.SetFillStyle(3003)
graph_sigp1clsfHigh.SetLineColor(c_red)
graph_sigp1clsfHigh.SetLineStyle(3)
graph_sigp1clsfHigh.SetLineWidth(2)
graph_sigp1clsfLow.SetFillColor(ROOT.kWhite)
graph_sigp1clsfLow.SetFillStyle(3003)
graph_sigp1clsfLow.SetLineColor(c_red)
graph_sigp1clsfLow.SetLineStyle(3)
graph_sigp1clsfLow.SetLineWidth(2)
sigp1expclsf.SetLineColor(c_blue)
sigp1expclsf.SetLineStyle(1)
sigp1expclsf.SetLineWidth(2)
sigp1clsf.SetLineWidth(3)
sigclsu1s.SetFillColor(ROOT.kWhite)
sigclsd1s.SetFillColor(c_yellow)
graph_sigp1expclsf.SetFillColor(c_yellow)
graph_sigp1expclsf.SetFillStyle(1001)
graph_sigp1expclsf.SetLineColor(c_blue)
graph_sigp1expclsf.SetLineStyle(7)
graph_sigp1expclsf.SetLineWidth(2)
# Load run 1 limit
# if ',' in region:
# f = ROOT.TFile.Open(os.environ['SUSY_ANALYSIS'] + '/results/limit_run1_gln1.root')
# limit_run1 = f.Get('clsf_obs')
# leg.AddEntry(limit_run1, 'ATLAS 8 TeV, 20.3 fb^{-1}', 'F')
if not args.onlyexp:
obs_entry = leg.AddEntry(graph_sigp1clsf, "Observed limit (#pm1 #sigma^{SUSY}_{theory})", "LF")
leg.AddEntry(graph_sigp1expclsf, "Expected limit (#pm1 #sigma_{exp})", "LF")
leg.Draw()
if not args.onlyexp and sig_xs_syst:
ROOT.gPad.Update()
n_rows = leg.GetNRows()
x1 = 0.15
y1 = 0.77
x2 = 0.49
y2 = 0.92
margin = leg.GetMargin() * (x2-x1)
boxw = margin*0.35
yspace = (y2-y1) / n_rows
xsym = x1 + margin/2.
ysym = y2 - 0.5*yspace - yspace * (n_rows-2)
dy = 0.015
line = ROOT.TLine()
ROOT.SetOwnership(line, False)
line.SetLineColor(obs_entry.GetLineColor())
line.SetLineWidth(2)
line.SetLineStyle(3)
line.DrawLineNDC(xsym-boxw, ysym+dy, xsym+boxw, ysym+dy)
line.DrawLineNDC(xsym-boxw, ysym-dy, xsym+boxw, ysym-dy)
# Plot
sigclsd1s.Draw("same cont0")
sigclsu1s.Draw("same cont0")
graph_sigp1expclsf.Draw("same l")
if not args.onlyexp:
graph_sigp1clsf.Draw('same l')
if sig_xs_syst:
graph_sigp1clsfHigh.Draw("same l")
graph_sigp1clsfLow.Draw("same l")
# plot Run 1 limit
# if ',' in region:
# limit_run1.SetLineWidth(2)
# limit_run1.SetLineColor(get_color('#b9b7b7'))
# limit_run1.SetFillColor(get_color('#c6c4c4'))
# limit_run1.Draw('f same')
# limit_run1.Draw('l same')
# Redraw axis and update frame
frame.RedrawAxis()
ROOT.gPad.Update()
output_tag = ''
if args.obscls or args.expcls:
# if sig_xs_syst:
# file_name = '%s/Output_fixSigXSecNominal_hypotest__1_harvest_list.root' % path
# else:
# file_name = '%s/Output_hypotest__1_harvest_list.root' % path
l_region = ROOT.TLatex()
l_region.SetTextSize(0.014)
l_region.SetTextColor(ROOT.kGray+2)
if sig_xs_syst:
tree_file = '%s/Output_fixSigXSecNominal_hypotest__1_harvest_list_hack.root' % path
else:
tree_file = '%s/Output_hypotest__1_harvest_list_hack.root' % path
if args.obscls:
cls_dict = get_cls_values(tree_file, False)
output_tag = '_obscls'
if args.expcls:
cls_dict = get_cls_values(tree_file, True)
output_tag = '_expcls'
for (mgl, mn1), cls in cls_dict.iteritems():
l_region.DrawLatex(mgl, mn1, "%.3f" % cls)
elif args.bestsr:
output_tag = '_bestsr'
region_events = dict()
dict_events = dict()
for sel in region.split(','):
if sig_xs_syst:
tree_file = '%s/Output_%s_fixSigXSecNominal_hypotest__1_harvest_list_hack.root' % (path, sel)
else:
tree_file = '%s/Output_%s_hypotest__1_harvest_list_hack.root' % (path, sel)
dict_events = get_cls_values(tree_file, exp=True)
region_events[sel] = dict_events
l_tot = ROOT.TLatex()
l_tot.SetTextSize(0.016)
l_tot.SetTextColor(ROOT.kGray+3)
for mgl, mn1 in dict_events.iterkeys():
binCLs = 100.
best_region_string = ''
for r in region_events.iterkeys():
if region_events[r][(mgl, mn1)] < binCLs:
binCLs = region_events[r][(mgl, mn1)]
best_region_string = r
print mgl, mn1, r, binCLs
l_tot.DrawLatex(mgl, mn1, "%s" % best_region_string[-1])
elif args.points:
lp = ROOT.TLatex()
lp.SetTextSize(0.016)
lp.SetTextColor(ROOT.kGray+3)
for (m3, mu), (mgl, mn1) in grid_m3_mu.iteritems():
if m3 > 2000:
lp.SetTextColor(ROOT.kRed-4)
lp.DrawLatex(mgl, mn1, "#times")
else:
lp.SetTextColor(ROOT.kGray+3)
lp.DrawLatex(mgl, mn1, "#bullet")
frame.SaveAs(path+'/limitPlot_%s%s.pdf' % (region.replace(',', '_'), output_tag))
# Save contours
outname = path + '/limit_contour_%s' % region.replace(',', '_') + '.root'
outfile = ROOT.TFile(outname, 'recreate')
outfile.cd()
## observed
graph_sigp1clsf.Write('clsf_obs')
if sig_xs_syst:
graph_sigp1clsfHigh.Write("clsf_obs_up")
graph_sigp1clsfLow.Write("clsf_obs_dn")
## expected
graph_sigp1expclsf.Write('clsf_exp')
if sig_xs_syst:
graph_sigclsd1s = convert_hist_to_graph(sigclsd1s)
graph_sigclsu1s = convert_hist_to_graph(sigclsu1s)
graph_sigclsd1s.Write('clsf_exp_dn')
graph_sigclsu1s.Write('clsf_exp_up')
outfile.Close()
else:
names.append(name)
x.append(counter)
xe.append(0)
y.append(val)
y_dn.append(abs(val_dn))
y_up.append(val_up)
counter += 1
# plot
set_atlas_style()
c = ROOT.TCanvas('pulls', '', 1200, 500)
c.SetBottomMargin(0.32)
c.SetTopMargin(0.03)
c.SetRightMargin(0.06)
c.SetLeftMargin(0.06)
frame = ROOT.TH2D('frame_', '', len(y), -0.5, len(y)-0.5, 5, -1.5, 1.5)
frame.SetYTitle('#alpha parameters after fit')
frame.SetXTitle('')
frame.Draw()
frame.GetYaxis().SetTitleOffset(0.5)
eg = ROOT.TGraphAsymmErrors(len(x), x, y, xe, xe, y_dn, y_up)
eg.SetMarkerStyle(20)
def main():
parser = argparse.ArgumentParser(description='analysis.py')
# Input/output
# version, data
parser.add_argument('-v', '--version', help='Mini-ntuples version')
parser.add_argument('--data', help='2015+2016 or 2017')
parser.add_argument('-o', dest='output_dir', help='Output directory')
# Steps
parser.add_argument('-c',
'--chist',
action='store_true',
help='Do "ntuples -> cuts histograms" step')
parser.add_argument('-d',
'--dhist',
action='store_true',
help='Do "ntuples -> distributions histograms" step')
parser.add_argument('-f',
'--fit',
action='store_true',
help='Do "histograms -> fit" step')
parser.add_argument('-t',
'--tables',
action='store_true',
help='Do "fit -> tables" step')
parser.add_argument('-p',
'--plots',
action='store_true',
help='Do "histograms/fit -> plots" step')
# Systematics
parser.add_argument('--syst',
action='store_true',
help='Include all systematics (detector + DD + MC)')
parser.add_argument('--detsyst',
action='store_true',
help='Include detector systematics')
parser.add_argument('--ddsyst',
action='store_true',
help='Include DD systematics')
parser.add_argument('--mcsyst',
action='store_true',
help='Include MC systematics')
# Extra options
parser.add_argument('--conf', help='HistFitter config file')
parser.add_argument(
'--unblind',
action='store_true',
help='Unblind Signal Regions! Use with caution, you can discover SUSY')
parser.add_argument('--noval',
action='store_true',
help='Don\'t include Validation Regions')
parser.add_argument('--mc', action='store_true', help='Use only MC')
# Histogram options
parser.add_argument('--force',
action='store_true',
help='Force histogram creation')
parser.add_argument('-s',
'--sample',
help='Only update histograms for this sample')
parser.add_argument(
'--ignore-missing',
dest='ignore_missing',
action='store_true',
help='Ignore missing samples. Do not use this option! ')
args = parser.parse_args()
step_chist = args.chist
step_dhist = args.dhist
step_fit = args.fit
step_tables = args.tables
step_plots = args.plots
if not any([
step_chist, step_dhist, step_fit, step_tables, step_plots
]) or args.output_dir is None or args.version is None or args.data is None:
parser.print_usage()
sys.exit(1)
# Configuration
unblind = args.unblind
data = args.data
version = args.version
do_validation = (not args.noval)
use_mc = args.mc
do_det_syst = False
do_dd_syst = False
do_mc_syst = False
if args.syst:
syst_str = ' --syst'
do_det_syst = True
do_dd_syst = True
do_mc_syst = True
else:
syst_str = ''
if args.detsyst:
do_det_syst = True
syst_str += ' --detsyst'
if args.ddsyst:
do_dd_syst = True
syst_str += ' --ddsyst'
if args.mcsyst:
do_mc_syst = True
syst_str += ' --mcsyst'
# -------
# Regions
# -------
srs = ['SRL200', 'SRL300', 'SRH']
crs = ['CRQ', 'CRW', 'CRT']
vrs = [
'VRQ', 'VRM1L', 'VRM2L', 'VRM1H', 'VRM2H', 'VRL1', 'VRL2', 'VRL3',
'VRL4', 'VRE'
]
sr_str = ','.join(srs)
if do_validation:
regions = crs + vrs + srs
regions_str = '%s,%s,%s' % (','.join(srs), ','.join(crs),
','.join(vrs))
else:
regions = crs + srs
regions_str = '%s,%s' % (','.join(srs), ','.join(crs))
# -------
# Samples
# -------
mc_samples = [
'photonjet',
'wgamma',
'zllgamma',
'znunugamma',
'ttgamma',
'diphoton',
]
mc_fake_samples = ['ttbar', 'multijet', 'wjets', 'zjets']
dd_samples = [
'efake',
'jfake',
]
if use_mc:
backgrounds = mc_samples + mc_fake_samples
else:
backgrounds = dd_samples + mc_samples
samples = [
'data',
] + backgrounds
#backgrounds_str = 'photonjet,wgamma,[zllgamma,znunugamma],ttgamma,efake,jfake,diphoton'
#backgrounds_str = 'photonjet,wgamma,[zllgamma,znunugamma],ttgamma'
backgrounds_str = ','.join(backgrounds)
# -----
# Plots
# -----
plot_variables = [
'ph_pt[0]',
'jet_n',
'bjet_n',
'jet_pt[0]',
'met_et',
'ht',
'meff',
'dphi_jetmet',
'dphi_gammet',
'dphi_gamjet',
'rt4',
]
#plot_bkgs = ['photonjet', 'wgamma','zgamma', 'fakes', 'ttgamma', 'diphoton']
plot_bkgs = [
'photonjet', 'wgamma', 'zgamma', 'efake', 'jfake', 'ttgamma',
'diphoton'
]
plot_regions = regions
plot_bkg_merge_dict = {
'zgamma': [
'zllgamma',
'znunugamma',
],
#'fakes': ['efake', 'jfake']
}
plot_bkg_norm_dict = {
'CRQ': 'photonjet',
'CRW': 'wgamma',
'CRT': 'ttgamma',
}
lumi = 0.
for year in data.split('+'):
lumi += miniutils.lumi_dict.get(year, 0.)
lumi /= 1000.
data_label = '#sqrt{s} = 13 TeV, %.1f fb^{-1}' % lumi
# ------------------
# Results output dir
# ------------------
susy_dir = os.environ['SUSY_ANALYSIS']
results_dir = args.output_dir
log_dir = '%s/log' % results_dir
histograms_dir = '%s/histograms' % results_dir
fit_dir = '%s/fit' % results_dir
tables_dir = '%s/tables' % results_dir
plots_dir = '%s/plots' % results_dir
mkdirp(results_dir)
mkdirp(log_dir)
mkdirp(histograms_dir)
mkdirp(fit_dir)
mkdirp(tables_dir)
mkdirp(plots_dir)
#-------------------
# Create Histograms
#-------------------
histograms_txt_path = '%s/histograms_cuts.txt' % (histograms_dir)
histograms_path = '%s/histograms_cuts.root' % (histograms_dir)
if step_chist and (not os.path.isfile(histograms_path) or args.force):
print('Creating cuts histograms ...')
do_histograms(histograms_path,
regions,
samples,
do_det_syst,
do_dd_syst,
do_mc_syst,
data,
version,
unblind,
ignore_missing=args.ignore_missing)
# Observables distributions
histograms_plots_path = '%s/histograms_plots.root' % (histograms_dir)
histograms_plots_before_path = '%s/histograms_plots_before.root' % (
histograms_dir)
histograms_plots_after_path = '%s/histograms_plots_after.root' % (
histograms_dir)
if step_dhist and (not os.path.isfile(histograms_plots_path) or args.force
or args.sample is not None):
print('Creating histograms for plots ...')
if args.force and os.path.isfile(histograms_plots_path):
os.remove(histograms_plots_path)
if args.sample is not None:
do_plots_histograms(histograms_plots_path, plot_regions,
args.sample.split(','), plot_variables, data,
version)
else:
do_plots_histograms(histograms_plots_path,
plot_regions,
samples,
plot_variables,
data,
version,
ignore_missing=args.ignore_missing)
#--------------
# Bkg-only Fit
#--------------
if args.conf is not None:
configfile = os.path.abspath(args.conf)
else:
configfile = susy_dir + '/lib/PhotonMet_HistFitter_config.py'
ws = fit_dir + "/BkgOnlyFit_combined_BasicMeasurement_model_afterFit.root"
if step_fit:
print('Performing bkg-only fit ...')
do_bkgonlyfit(configfile,
histograms_path,
fit_dir,
sr_str,
lumi,
do_validation,
syst_str,
use_mc,
'%s/bkgonlyfit.log' % log_dir,
hf_options='-D correlationMatrix') # -m ALL
#--------
# Tables
#--------
if step_tables:
print('Creating tables ...')
do_tables(ws, tables_dir, backgrounds, regions, sr_str, do_validation,
unblind, (do_det_syst or do_mc_syst or do_dd_syst),
plot_bkg_norm_dict)
#-------
# Plots
#-------
if step_plots:
print('Preparing histograms for plots...')
prepare_histograms_for_plots(histograms_plots_path,
histograms_plots_before_path,
plot_regions,
backgrounds,
plot_variables,
merge_dict=plot_bkg_merge_dict)
prepare_histograms_for_plots(histograms_plots_path,
histograms_plots_after_path,
plot_regions,
backgrounds,
plot_variables,
merge_dict=plot_bkg_merge_dict,
ws=ws,
norm_dict=plot_bkg_norm_dict)
## Pull plot
print('Creating pull plot ...')
do_regions_pull_plot(ws,
plots_dir + '/regions_pull.pdf',
backgrounds,
plot_bkgs,
regions,
plot_bkg_merge_dict,
unblind=unblind,
data_label=data_label)
#do_regions_pull_plot(ws, plots_dir+'/regions_pull_significance.pdf', backgrounds, plot_bkgs, regions, plot_bkg_merge_dict, unblind=unblind, data_label=data_label, plot_significance=True)
set_atlas_style()
# Before fit plots
print('Creating before-fit plots ...')
do_plots(histograms_plots_before_path,
plots_dir,
plot_regions,
plot_bkgs,
plot_variables,
data_label,
unblind=unblind,
output_label='beforeFit')
# After fit plots
print('Creating after-fit plots ...')
do_plots(histograms_plots_after_path,
plots_dir,
plot_regions,
plot_bkgs,
plot_variables,
data_label,
unblind=unblind,
output_label='afterFit')
h_yields_norm.SetBinContent(counter, norm_yield)
h_yields_norm.SetBinError(counter, error/lumi)
print run, norm_yield
# avgmu
htemp = ROOT.TH1D('avgmu_%i' % run, 'avgmu', 50, 0., 50.)
tree.Project('avgmu_%i' % run, 'avgmu', selection)
h_avgmu.SetBinContent(counter, htemp.GetMean())
counter += 1
set_atlas_style()
set_style(h_yields_norm, color=ROOT.kBlack, lwidth=1)
set_style(h_avgmu, color='pink', lwidth=1, alpha=0.5)
c = ROOT.TCanvas('', '', 2400, 600)
c.SetFillColor(0)
c.SetBorderMode(0)
c.SetBorderSize(2)
c.SetTicks(0,1)
c.SetTickx(0)
c.SetTopMargin (0.03)
c.SetRightMargin(0.02)
c.SetLeftMargin (0.05)
c.SetBottomMargin (0.1)
