'jmult').integrate('lepcat').integrate('btag')
# split hslice into signal samples/SM MC+data
sig_hslice = hslice[Plotter.signal_samples]
SM_hslice = hslice[Plotter.nonsignal_samples]
if hname == 'Jets_njets':
print(jmult)
yields_txt, yields_json = Plotter.get_samples_yield_and_frac(
hslice,
data_lumi_year['%ss' % args.lepton] / 1000.)
yields_fname = os.path.join(
pltdir,
'%s_%s_yields_and_fracs' % (jmult, args.lepton))
plt_tools.print_table(yields_txt,
filename='%s.txt' % yields_fname,
print_output=True)
with open('%s.json' % yields_fname, 'w') as out:
out.write(prettyjson.dumps(yields_json))
# plot signal
if sig_hslice.values():
for signal in sig_hslice.values().keys():
fig, ax = plt.subplots()
fig.subplots_adjust(hspace=.07)
sig_hist = sig_hslice[signal].integrate('process')
Plotter.plot_1D(
*sig_hist.values().values(),
sig_hist.axis(xaxis_name).edges(),
xlabel=xtitle,
mtt_ct_interp_yields == mtt_ct_interp_yields[0]
) # values are all equal up to specified decimal place
if mtt_ct_interp_same:
mtt_ct_interp_yield = mtt_ct_interp_yields[0]
if not (nom_same and pt_same and mtt_ct_same and pt_interp_same
and mtt_ct_interp_same):
dec_tolerance -= 1
rows = [("Lumi: %s fb^-1" % format(lumi_to_use, ".1f"), "",
"Values are the same up to %i decimal places" % dec_tolerance)]
rows += [("Reweighting", "Yield", "Yield/Nominal")]
rows += [("Nominal", format(nom_yield, ".%if" % dec_tolerance),
format(nom_yield / nom_yield, ".%if" % dec_tolerance))]
rows += [("thad_pt", format(pt_yield, ".%if" % dec_tolerance),
format(pt_yield / nom_yield, ".%if" % dec_tolerance))]
rows += [("mtt_vs_thad_ctstar", format(mtt_ct_yield, ".%if" % dec_tolerance),
format(mtt_ct_yield / nom_yield, ".%if" % dec_tolerance))]
rows += [("thad_pt_interp", format(pt_interp_yield, ".%if" % dec_tolerance),
format(pt_interp_yield / nom_yield, ".%if" % dec_tolerance))]
rows += [("mtt_vs_thad_ctstar_interp",
format(mtt_ct_interp_yield, ".%if" % dec_tolerance),
format(mtt_ct_interp_yield / nom_yield, ".%if" % dec_tolerance))]
yields_fname = os.path.join(outdir, "reweighting_yields.txt")
plt_tools.print_table(rows,
filename=yields_fname,
print_output=True,
header_line=1)
print(f"{yields_fname} written")
fig, ax = plt.subplots()
fig.subplots_adjust(hspace=.07)
hslice = histo[:, btag_applied, jmult, lepcat,
btagregion].integrate(
'jmult'
).integrate('lepcat').integrate(
'btag').integrate('btagging')
if hname == 'Jets_njets':
print(jmult)
yields_txt, yields_json = Plotter.get_samples_yield_and_frac(
hslice,
data_lumi_year['%ss' % args.lepton] / 1000.)
plt_tools.print_table(
yields_txt,
filename='%s/%s_%s_yields_and_fracs.txt' %
(pltdir, jmult, args.lepton),
print_output=True)
with open(
'%s/%s_%s_yields_and_fracs.json' %
(pltdir, jmult, args.lepton), 'w') as out:
out.write(prettyjson.dumps(yields_json))
if rebinning != 1:
xaxis_name = hslice.dense_axes()[0].name
hslice = hslice.rebin(xaxis_name, rebinning)
mc_opts = {
'mcorder': ['QCD', 'EWK', 'singlet', 'ttJets']
}
if withData:
ax = Plotter.plot_mc1d(ax,
hslice,
xlabel=xtitle,
xlimits=x_lims,
**mc_opts)
if hname == 'Jets_njets':
print(jmult)
yields_txt, yields_json = Plotter.get_samples_yield_and_frac(
hslice,
data_lumi_year['%ss' % args.lepton] / 1000.,
promptmc=True)
frac_name = '%s_yields_and_fracs' % '_'.join(
[jmult, args.lepton, lepcat, btagregion])
plt_tools.print_table(yields_txt,
filename='%s/%s.txt' %
(pltdir, frac_name),
print_output=True)
print('%s/%s.txt written' % (pltdir, frac_name))
with open('%s/%s.json' % (pltdir, frac_name),
'w') as out:
out.write(prettyjson.dumps(yields_json))
# add lepton/jet multiplicity label
#set_trace()
ax.text(0.02,
0.88 if withData else 0.90,
"%s, %s\n%s" % (lep_cats[lepcat], jet_mults[jmult],
btag_cats[btagregion]),
fontsize=rcParams['font.size'] * 0.75,
horizontalalignment='left',
verticalalignment='bottom',
ax_norm.text(
0.02, 0.90, "$e/\mu$, %s\nParton Level" % jet_mults[jmult],
fontsize=rcParams['font.size'], horizontalalignment='left', verticalalignment='bottom', transform=ax_norm.transAxes
)
## set axes labels and titles
hep.cms.label(ax=ax_norm, data=False, paper=False, year=args.year, lumi=round(lumi_to_use, 1))
#set_trace()
figname_norm = os.path.join(pltdir, '_'.join([args.year, jobid, jmult, 'Group_Cats', hname, 'Norm']))
fig_norm.savefig(figname_norm)
print('%s written' % figname_norm)
plt.close()
## make table
rows = [("Lumi: %s fb^-1" % format(round(lumi_to_use, 1), '.1f'), 'e/mu', jmult, "")]
rows += [("Event Type", "Yield", "Error", "Frac of l+jets ttbar events")]
for cat in evt_groups.keys():
rows += [(cat, format(general_cat_histo.values(overflow='all', sumw2=True)[(cat,)][0].sum(), '.3f'), format(np.sqrt(general_cat_histo.values(overflow='all', sumw2=True)[(cat,)][1].sum()), '.3f'), format(general_cat_histo.values(overflow='all', sumw2=True)[(cat,)][0].sum()/general_cat_histo.integrate('gen_evt_cat').values(overflow='all')[()].sum(), '.5f'))]
rows += [("", "", "", "")]
for cat in indiv_evt_groups.keys():
if cat == 'Other': continue
rows += [(cat, format(indiv_cat_histo.values(overflow='all', sumw2=True)[(cat,)][0].sum(), '.3f'), format(np.sqrt(indiv_cat_histo.values(overflow='all', sumw2=True)[(cat,)][1].sum()), '.3f'), format(indiv_cat_histo.values(overflow='all', sumw2=True)[(cat,)][0].sum()/indiv_cat_histo.integrate('all_evt_cat').values(overflow='all')[()].sum(), '.5f'))]
#set_trace()
cat_fractions_name = os.path.join(pltdir, '%s_%s_Event_Categories_%s_yields_and_fractions.txt' % (args.year, jobid, jmult))
plt_tools.print_table(rows, filename=cat_fractions_name, header_line=1, print_output=True)
print('%s written' % cat_fractions_name)
'%s %s' % (proc, decay), )][1].sum()
), hslice.values(overflow='all', sumw2=True)[
('%s %s' %
(proc, decay), )][0].sum() / sigreg_ntot
rows += [("", name, format(proc_yield, '.2f'),
format(proc_err,
'.2f'), format(proc_frac, '.6f'))]
rows += [("", "", "", "", "")]
#set_trace()
# nevents
ttdecay_name = '%s_ttdecay_yields' % '_'.join(
[jmult, args.lepton, lepcat, btagregion])
plt_tools.print_table(rows,
filename='%s/%s.txt' %
(pltdir, ttdecay_name),
header_line=1,
print_output=True)
print('%s/%s.txt written' % (pltdir, ttdecay_name))
## combine jet channels, so only depends on lepton
#set_trace()
lep_histo = histo[:, :, 'btagPass', 'Tight'].integrate(
'process').integrate('jmult').integrate('lepcat').integrate('btag')
pltdir = os.path.join(outdir, args.lepton)
if not os.path.isdir(pltdir):
os.makedirs(pltdir)
rows = [("Lumi: %s fb^-1" %
format(data_lumi_year['%ss' % args.lepton] / 1000., '.1f'),
Plotter.plot_1D(hslice.values()[('Before',)], hslice.axis(xaxis_name).edges(), xlimits=x_lims, ax=ax, label='Runs $<$ 319077')
Plotter.plot_1D(hslice.values()[('After',)], hslice.axis(xaxis_name).edges(), xlimits=x_lims, xlabel=xtitle, color='r', ax=ax, label='Runs $\\geq$ 319077')
ax.legend(loc='upper right')
if hname == 'Jets_njets':
print(jmult)
#set_trace()
rows = [("Lumi: %s fb^-1" % format(data_lumi_year['%ss' % args.lepton]/1000., '.1f'), "Yield", "Error", "Frac")]
rows += [("Runs < 319077", format(sum(hslice.values(overflow='all')[('Before',)]), '.1f'), format(np.sqrt(sum(hslice.values(overflow='all', sumw2=True)[('Before',)][1])), '.1f'),
format(sum(hslice.values(overflow='all')[('Before',)])/sum(hslice.sum('hem').values(overflow='all')[()]), '.3f'))]
rows += [("Runs >= 319077", format(sum(hslice.values(overflow='all')[('After',)]), '.1f'), format(np.sqrt(sum(hslice.values(overflow='all', sumw2=True)[('After',)][1])), '.1f'),
format(sum(hslice.values(overflow='all')[('After',)])/sum(hslice.sum('hem').values(overflow='all')[()]), '.3f'))]
rows += [("Total", format(sum(hslice.sum('hem').values(overflow='all')[()]), '.1f'), format(np.sqrt(sum(hslice.sum('hem').values(overflow='all', sumw2=True)[()][1])), '.1f'), "")]
frac_name = '%s_yields_and_fracs.txt' % '_'.join([jmult, args.lepton, lepcat, btagregion])
plt_tools.print_table(rows, filename=os.path.join(pltdir, frac_name), print_output=True)
print('%s/%s.txt written' % (pltdir, frac_name))
# add lepton/jet multiplicity label
ax.text(
0.02, 0.90, "%s, %s\n%s" % (lep_cats[lepcat], jet_mults[jmult], btag_cats[btagregion]),
fontsize=rcParams['font.size']*0.75, horizontalalignment='left', verticalalignment='bottom', transform=ax.transAxes
)
hep.cms.label(ax=ax, data=True, paper=False, year=args.year, lumi=round(data_lumi_year['%ss' % args.lepton]/1000., 1))
#set_trace()
figname = os.path.join(pltdir, '_'.join([jmult, args.lepton, lepcat, btagregion, hname]))
fig.savefig(figname)
print('%s written' % figname)
plt.close()