ranges["x2"] = (25, 0, 1) channels = ["mu", "ele"] jettag = ["2j1t", "2j0t", "3j1t", "3j2t"] histos = {} infile = TFile.Open(base_filename, "read") infile2 = TFile.Open(added_filename, "read") events = infile.Get('dataframe') events2 = infile2.Get('dataframe') colnames = ["bdt_qcd", "bdt_sig_bg", "xsweight", "wjets_ct_shape_weight", "wjets_fl_yield_weight", "wjets_pt_weight"] extra_data = {} (pdf_weights, average_weights, pdf_input) = get_weights(dataset, thispdf, channel, counter, -1) maxscale = 200 minscale = 170 maxid = 0 minid = 0 maxx = 0. minx = 0. histograms = dict() c = channel #luminosity = 19764 luminosity = 19670 if channel == "ele": #luminosity = 19820 luminosity = 19637
variables = ["cos_theta_lj_gen"] var = variables[0] ranges = {} ranges["cos_theta_lj"] = (48, -1, 1) ranges["cos_theta_lj_gen"] = (24, -1, 1) channels = ["mu", "ele"] jettag = ["2j1t"] infile = TFile.Open(base_filename, "read") infile2 = TFile.Open(added_filename, "read") events = infile.Get('dataframe') #events2 = infile2.Get('dataframe') (pdf_weights, average_weights, pdf_input) = get_weights(dataset, thispdf, channel, counter, counter_w, dont_skim= True) histograms = dict() c = channel luminosity = 19670 if channel == "ele": luminosity = 19637 #bdt_cuts = ["-0.20000", "-0.10000", "0.00000", "0.06000", "0.10000", "0.13000", "0.20000", "0.25000", "0.30000", "0.35000", "0.40000", "0.45000", "0.50000", "0.55000", "0.60000", "0.65000", "0.70000", "0.75000", "0.80000"] histograms[c] = dict() for p in pdfs: if not (thispdf == p or (p == 'NNPDF23' and thispdf == "NNPDF23nloas0119LHgrid")): continue histograms[c][p] = dict() name = "cos_theta_lj_gen__%s__%s" % (dataset, p)