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)
