else:
regions = [ cr + '_L' for cr in analysis.cr_regions ] + \
[ cr + '_H' for cr in analysis.cr_regions ] + \
[ vr + '_L' for vr in analysis.vr_regions ] + \
[ vr + '_H' for vr in analysis.vr_regions ]
set_atlas_style()
set_palette()
for region in regions:
selection = getattr(regions_, region)
total_bkg = 0
for bkg in backgrounds:
total_bkg += get_events(bkg, selection=selection, lumi='data').mean
gl_min = 1146
gl_max = 2050
n1_min = 147
n1_max = 2050
gl_bins = (gl_max - gl_min) / 25
n1_bins = (n1_max - n1_min) / 25
hmap = ROOT.TH2F('hmap', 'hmap', gl_bins, gl_min, gl_max, n1_bins, n1_min, n1_max)
hmap.SetDirectory(0)
ROOT.SetOwnership(hmap, False)
largest_cont = 0
for iregion, region in enumerate(regions):
if sample == 'data' and region == 'SR':
continue
sel = getattr(regions_, region)
histograms[0].GetXaxis().SetBinLabel(iregion + 1, region)
print region
print '-----'
for idx, ver in enumerate(versions):
evts = get_events(sample,
selection=sel,
version=ver,
scale=args.scale,
lumi='data')
print ver, evts
histograms[idx].SetBinContent(iregion + 1, evts.mean)
set_style(histograms[idx], msize=1, lwidth=2, color=colors[idx])
# Plot
c = ROOT.TCanvas()
cup = ROOT.TPad("u", "u", 0., 0.305, 0.99, 1)
cdown = ROOT.TPad("d", "d", 0., 0.01, 0.99, 0.295)
cup.SetLogy()
hist.SetBinErrorOption(ROOT.TH1.kPoisson)
for iregion, region in enumerate(regions):
if sample == 'data' and region == 'SR':
continue
sel = getattr(regions_, region)
histograms[0].GetXaxis().SetBinLabel(iregion+1, region)
print region
for idx, ver in enumerate(versions):
evts = get_events(sample, selection=sel, version=ver, scale=False)
print ver, evts
histograms[idx].SetBinContent(iregion+1, evts.mean)
set_style(histograms[idx], msize=1, lwidth=2, color=colors[idx])
# Plot
c = ROOT.TCanvas()
cup = ROOT.TPad("u", "u", 0., 0.305, 0.99, 1)
cdown = ROOT.TPad("d", "d", 0., 0.01, 0.99, 0.295)
cup.SetLogy()
cup.SetFillColor(0);
args = parser.parse_args()
backgrounds = analysis.backgrounds
regions = args.regions.split(',')
set_atlas_style()
set_palette()
for region in regions:
selection = getattr(regions_, region)
total_bkg = 0
for bkg in backgrounds:
total_bkg += get_events(bkg, selection=selection, lumi='data').mean
gl_min = 1300
gl_max = 2500
n1_min = 147
n1_max = 2500
gl_bins = (gl_max - gl_min) / 30
n1_bins = (n1_max - n1_min) / 30
hmap = ROOT.TH2F('hmap', 'hmap', gl_bins, gl_min, gl_max, n1_bins, n1_min,
n1_max)
hmap.SetDirectory(0)
ROOT.SetOwnership(hmap, False)
largest_cont = 0
ROOT.SetOwnership(h_sel_srl200, False)
ROOT.SetOwnership(h_sel_srl300, False)
ROOT.SetOwnership(h_sel_srh, False)
for (m3, mu), (mgl, mn1) in sorted(mg_gg_grid.iteritems()):
name = 'GGM_GG_bhmix_%i_%i' % (m3, mu)
# total events
ds = get_sample_datasets(name)[0]
total_events = get_sumw(ds)
if total_events == 0:
continue
srl200_events_scaled = get_events(name, selection=SRL200, lumi='data').mean
srl300_events_scaled = get_events(name, selection=SRL300, lumi='data').mean
srh_events_scaled = get_events(name, selection=SRH, lumi='data').mean
h_sel_srl200.Fill(mgl, mn1, round(srl200_events_scaled, 2))
h_sel_srl300.Fill(mgl, mn1, round(srl300_events_scaled, 2))
h_sel_srh.Fill(mgl, mn1, round(srh_events_scaled, 2))
srl200_events = get_events(name, selection=SRL200, scale=False).mean
srl300_events = get_events(name, selection=SRL300, scale=False).mean
srh_events = get_events(name, selection=SRH, scale=False).mean
## acc x eff
srl200_acceff = round(srl200_events / total_events, 2)
srl300_acceff = round(srl300_events / total_events, 2)
srh_acceff = round(srh_events / total_events, 2)
for (m3, mu) in sorted(mass_dict.iterkeys()):
mgl, mn1 = mass_dict[(int(m3), int(mu))]
name = 'GGM_M3_mu_%i_%i' % (m3, mu)
# total events
ds = get_sample_datasets(name)[0]
total_events = get_sumw(ds)
if total_events == 0:
continue
srl_events_scaled = get_events(name, selection=SR_L, lumi='data').mean
srh_events_scaled = get_events(name, selection=SR_H, lumi='data').mean
sril_events_scaled = get_events(name, selection=SRincl_L, lumi='data').mean
srih_events_scaled = get_events(name, selection=SRincl_H, lumi='data').mean
h_sel_srl.Fill(mgl, mn1, round(srl_events_scaled, 2))
h_sel_srh.Fill(mgl, mn1, round(srh_events_scaled, 2))
h_sel_sril.Fill(mgl, mn1, round(sril_events_scaled, 2))
h_sel_srih.Fill(mgl, mn1, round(srih_events_scaled, 2))
srl_events = get_events(name, selection=SR_L, scale=False).mean
srh_events = get_events(name, selection=SR_H, scale=False).mean
sril_events = get_events(name, selection=SRincl_L, scale=False).mean