)
parser.add_argument(
'-ai', '--anti_iso', required=False, action='store_true', dest='use_antiiso',
help='Change region to anti-isolated region'
)
args = parser.parse_args()
#Do both channels by default
if not args.channels:
args.channels = ["mu", "ele"]
output_folder = OutputFolder(
os.path.join(os.environ["STPOL_DIR"],"out", "plots"),
subpath="make_all_plots",
overwrite=False,
unique_subdir=args.new,
skip_png=args.cluster
)
logger.info("Output folder is %s" % output_folder.out_folder)
#FIXME: factorize
#Check if any of the provided hashtags matches any of the (optional) hashtags of the plot defs
args.plots += [k for (k, v) in plot_defs.items() if 'tags' in v.keys() and len(set(args.tags).intersection(set(v['tags'])))>0]
#Remove plots with disabled tags
disabled_tags = map(lambda x: x[1:], filter(lambda x: x.startswith("."), args.tags))
for n, plotname in plot_defs.items():
if 'tags' in plotname.keys() and len(set(disabled_tags).intersection(set(plotname['tags'])))>0:
args.plots = filter(lambda x: x!=n, args.plots)
#If there are no plots defined, do all of them
hcomphep.SetLineColor(ROOT.kRed)
hcomphep.SetFillColor(ROOT.kRed)
hcomphep.SetFillStyle('/')
hcomphep.SetLineStyle('dashed')
hcomphep.SetMarkerSize(0)
Styling.data_style(data_post)
hi = [data_post, htrue, hcomphep]
chi2 = data_post.Chi2Test(htrue, "WW CHI2/NDF")
#htrue.SetTitle(htrue.GetTitle() + " #chi^{2}/#nu = %.1f" % chi2)
#hi_norm = hi
hi_norm = map(post_normalize, hi)
for h in hi[1:]:
h.SetMarkerSize(0)
of = OutputFolder(subdir='unfolding/%s' % lep)
canv = plot_hists(hi_norm, x_label="cos #theta*", draw_cmd=len(hi)*["E1"], y_label="a.u.")
#leg = legend(hi, styles=['p', 'f'], legend_pos='bottom-right', nudge_x=-0.29, nudge_y=-0.08)
leg = legend(hi, styles=['p', 'f'], legend_pos='top-left', nudge_y=-0.14)
lb = lumi_textbox(lumi,
pos='top-center',
line2="#scale[1.5]{A = %.2f #pm %.2f (stat.) #pm %.2f (syst.)}" % (
measured_asym, measured_asym_errs[lep][0], measured_asym_errs[lep][1]
), nudge_y=0.03
)
pmi = PlotMetaInfo(
'costheta_unfolded',
'2j1t_mva_loose {0}'.format(channel),
'weighted to lumi={0}, sf(tchan)={1}'.format(lumi, fitpars[lep]),
[args.infileMC, args.infileD]
)
