Variables
tuple	log = logging.getLogger(__name__)

tuple	parser

string	help = "input files"

string	default = "mt"

list	choices = ["tt", "mt", "et", "em", "mm", "ee"]

tuple	args = parser.parse_args()

	outputname = args.score_name

string	ntuple_string = args.channel+"_jecUncNom/ntuple"

list	keys = []

dictionary	TestLeafs = {}

dictionary	ROCintegral = {}

dictionary	ROCintegralTrain = {}

list	y1 = [1.0]

list	y2 = [1.0]

list	ymean = [1.0]

list	y1T = [1.0]

list	y2T = [1.0]

list	ymeanT = [1.0]

tuple	f = ROOT.TFile.Open(TestLeafs[key]+"T%i.root"%(i))

tuple	hist = f.Get("Method_BDT/BDT_"+TestLeafs[key]+"/MVA_BDT_"+TestLeafs[key]+"_rejBvsS")

tuple	hist2 = f.Get("Method_BDT/BDT_"+TestLeafs[key]+"/MVA_BDT_"+TestLeafs[key]+"_trainingRejBvsS")

float	ROCcrossing = 0.0

list	x_values = [0.0]

tuple	fig = plt.figure()

tuple	ax = fig.add_subplot(111, xlabel='signal efficiency', ylabel='background rejection')

tuple	Output = open(outputname + ".txt","w")

list	y_values = []

list	yT_values = []

tuple	llim = int(args.sublims.split(":")[0])

tuple	ulim = int(args.sublims.split(":")[1])

Variable Documentation

tuple plot_AUC_1D.args = parser.parse_args()

tuple plot_AUC_1D.ax = fig.add_subplot(111, xlabel='signal efficiency', ylabel='background rejection')

list plot_AUC_1D.choices = ["tt", "mt", "et", "em", "mm", "ee"]

string plot_AUC_1D.default = "mt"

tuple plot_AUC_1D.f = ROOT.TFile.Open(TestLeafs[key]+"T%i.root"%(i))

tuple plot_AUC_1D.fig = plt.figure()

string plot_AUC_1D.help = "input files"

tuple plot_AUC_1D.hist = f.Get("Method_BDT/BDT_"+TestLeafs[key]+"/MVA_BDT_"+TestLeafs[key]+"_rejBvsS")

tuple plot_AUC_1D.hist2 = f.Get("Method_BDT/BDT_"+TestLeafs[key]+"/MVA_BDT_"+TestLeafs[key]+"_trainingRejBvsS")

list plot_AUC_1D.keys = []

tuple plot_AUC_1D.llim = int(args.sublims.split(":")[0])

tuple plot_AUC_1D.log = logging.getLogger(__name__)

string plot_AUC_1D.ntuple_string = args.channel+"_jecUncNom/ntuple"

tuple plot_AUC_1D.Output = open(outputname + ".txt","w")

tuple plot_AUC_1D.outputname = args.score_name

tuple plot_AUC_1D.parser

Initial value:

1 = argparse.ArgumentParser(description="Get information on overtraining.",

2 parents=[logger.loggingParser])

float plot_AUC_1D.ROCcrossing = 0.0

dictionary plot_AUC_1D.ROCintegral = {}

dictionary plot_AUC_1D.ROCintegralTrain = {}

dictionary plot_AUC_1D.TestLeafs = {}

tuple plot_AUC_1D.ulim = int(args.sublims.split(":")[1])

list plot_AUC_1D.x_values = [0.0]

list plot_AUC_1D.y1 = [1.0]

list plot_AUC_1D.y1T = [1.0]

list plot_AUC_1D.y2 = [1.0]

list plot_AUC_1D.y2T = [1.0]

list plot_AUC_1D.y_values = []

list plot_AUC_1D.ymean = [1.0]

list plot_AUC_1D.ymeanT = [1.0]

list plot_AUC_1D.yT_values = []

Variables