) 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] )