plot_AUC_2D.py File Reference

Namespaces
	plot_AUC_2D

Variables
tuple	plot_AUC_2D.log = logging.getLogger(__name__)
tuple	plot_AUC_2D.parser
string	plot_AUC_2D.help = "output file pattern"
string	plot_AUC_2D.default = "mt"
list	plot_AUC_2D.choices = ["tt", "mt", "et", "em", "mm", "ee"]
tuple	plot_AUC_2D.args = parser.parse_args()
tuple	plot_AUC_2D.outputfolder = os.path.dirname(args.output_dir)
	plot_AUC_2D.outputname = args.score_name
string	plot_AUC_2D.ntuple_string = args.channel+"_jecUncNom/ntuple"
tuple	plot_AUC_2D.Output = open(os.path.join(outputfolder, outputname.replace("$N$", "_N_").replace("$X$", "_X_") + ".txt"),"w")
tuple	plot_AUC_2D.fig2 = plt.figure()
tuple	plot_AUC_2D.ax2 = fig2.add_subplot(111, xlabel='number of trees', ylabel='integral over ROC curve', xlim=[1.1*min(args.NTrees)-0.1*max(args.NTrees),1.1*max(args.NTrees)-0.1*min(args.NTrees)])
list	plot_AUC_2D.colors = ["r", "b", "g", "y"]
list	plot_AUC_2D.keys = []
string	plot_AUC_2D.filename = args.channel+"_"
dictionary	plot_AUC_2D.TestLeafs = {}
dictionary	plot_AUC_2D.ROCintegral = {}
dictionary	plot_AUC_2D.ROCintegralTrain = {}
list	plot_AUC_2D.y1 = [1.0]
list	plot_AUC_2D.y2 = [1.0]
list	plot_AUC_2D.ymean = [1.0]
list	plot_AUC_2D.y1T = [1.0]
list	plot_AUC_2D.y2T = [1.0]
list	plot_AUC_2D.ymeanT = [1.0]
tuple	plot_AUC_2D.f = ROOT.TFile.Open(TestLeafs[key]+"T%i.root"%(i))
tuple	plot_AUC_2D.hist = f.Get("Method_BDT/BDT_"+TestLeafs[key]+"/MVA_BDT_"+TestLeafs[key]+"_rejBvsS")
tuple	plot_AUC_2D.hist2 = f.Get("Method_BDT/BDT_"+TestLeafs[key]+"/MVA_BDT_"+TestLeafs[key]+"_trainingRejBvsS")
float	plot_AUC_2D.ROCcrossing = 0.0
list	plot_AUC_2D.x_values = [0.0]
tuple	plot_AUC_2D.fig = plt.figure()
tuple	plot_AUC_2D.ax = fig.add_subplot(111, xlabel='signal efficiency', ylabel='background rejection')
list	plot_AUC_2D.y_values = []
list	plot_AUC_2D.yT_values = []