cutOptimizer Namespace Reference

Classes
class	CutOptimizer

Functions
def	make_Histogram
def	optimize
def	test_function

Variables
tuple	log = logging.getLogger(__name__)
tuple	parser
string	help = "Input directory."
list	default = ["ztt", "zll", "zl", "zj", "ttj", "vv", "wj", "qcd", "data"]
list	choices = ["ztt", "zll", "zl", "zj", "ttj", "vv", "wj", "qcd", "ff", "ggh", "qqh", "bbh", "vh", "htt", "data"]
tuple	args = parser.parse_args()
list	list_of_samples = [getattr(samples.Samples, sample) for sample in args.samples]
tuple	sample_settings = samples.Samples()
list	bkg_samples = [sample for sample in args.samples if sample not in ["data", "htt", "bbh"]]
list	sig_samples_raw = [sample for sample in args.samples if sample in ["htt", "bbh"]]
list	sig_samples = []
string	scale_str = "_%i"
tuple	binnings_settings = binnings.BinningsDict()
	category_string = None
tuple	config
list	x_bins = [x for x in range(int(float(args.x_range[0])*100),int(float(args.x_range[1])*100)+1, int((float(args.x_range[1])-float(args.x_range[0]))*4))]
list	y_bins = []
list	z_bins = []
list	variables = [args.x_quantity]
list	current_cuts = []
int	current_max = 0
list	real_values = []
list	b_max_index = current_cuts[0]
list	b_min = x_bins[b_max_index-3]
list	b_max = x_bins[b_max_index+3]
tuple	step = (b_max-b_min)
tuple	tfile = ROOT.TFile(os.path.expandvars(os.path.join(args.output_dir, "CutOptimizerStorage.root")), "READ")
list	hist_list = [tfile.Get(name) for name in bkg_samples]
tuple	htt = tfile.Get(sig_samples[0])
tuple	bkg_hist = hist_list.pop(0)
tuple	opt_test = CutOptimizer(variables, [htt,bkg_hist])

Function Documentation

def cutOptimizer.make_Histogram

(

)

def cutOptimizer.optimize

(

root_histogram

)

def cutOptimizer.test_function

(

kwargs

)

Variable Documentation

tuple cutOptimizer.args = parser.parse_args()

tuple cutOptimizer.b_max = x_bins[b_max_index+3]

list cutOptimizer.b_max_index = current_cuts[0]

tuple cutOptimizer.b_min = x_bins[b_max_index-3]

tuple cutOptimizer.binnings_settings = binnings.BinningsDict()

tuple cutOptimizer.bkg_hist = hist_list.pop(0)

list cutOptimizer.bkg_samples = [sample for sample in args.samples if sample not in ["data", "htt", "bbh"]]

tuple cutOptimizer.category_string = None

list cutOptimizer.choices = ["ztt", "zll", "zl", "zj", "ttj", "vv", "wj", "qcd", "ff", "ggh", "qqh", "bbh", "vh", "htt", "data"]

tuple cutOptimizer.config

Initial value:

= sample_settings.get_config(
                        samples=list_of_samples,
                        channel=args.channel,
                        category=category_string,
                        higgs_masses=args.higgs_masses,
                        normalise_signal_to_one_pb=False,
                        ztt_from_mc=args.ztt_from_mc,
                        weight="({0})".format(args.weight),
                        lumi = args.lumi * 1000,
                        exclude_cuts=args.exclude_cuts,
                        fakefactor_method=args.fakefactor_method,
                        scale_signal=args.scale_signal,
                        project_to_lumi=args.project_to_lumi,
                        cut_mc_only=args.cut_mc_only,
                        scale_mc_only=args.scale_mc_only,
                        mssm=args.mssm,
                        cut_type="mssm2016" if (args.era == "2016" and args.mssm) else "mssm" if args.mssm else "baseline2016" if args.era == "2016" else "baseline"
        )

list cutOptimizer.current_cuts = []

int cutOptimizer.current_max = 0

string cutOptimizer.default = ["ztt", "zll", "zl", "zj", "ttj", "vv", "wj", "qcd", "data"]

string cutOptimizer.help = "Input directory."

list cutOptimizer.hist_list = [tfile.Get(name) for name in bkg_samples]

tuple cutOptimizer.htt = tfile.Get(sig_samples[0])

list cutOptimizer.list_of_samples = [getattr(samples.Samples, sample) for sample in args.samples]

tuple cutOptimizer.log = logging.getLogger(__name__)

tuple cutOptimizer.opt_test = CutOptimizer(variables, [htt,bkg_hist])

tuple cutOptimizer.parser

Initial value:

= argparse.ArgumentParser(description="Make Data-MC control plots.",
                                         parents=[logger.loggingParser])

list cutOptimizer.real_values = []

tuple cutOptimizer.sample_settings = samples.Samples()

string cutOptimizer.scale_str = "_%i"

list cutOptimizer.sig_samples = []

list cutOptimizer.sig_samples_raw = [sample for sample in args.samples if sample in ["htt", "bbh"]]

tuple cutOptimizer.step = (b_max-b_min)

tuple cutOptimizer.tfile = ROOT.TFile(os.path.expandvars(os.path.join(args.output_dir, "CutOptimizerStorage.root")), "READ")

list cutOptimizer.variables = [args.x_quantity]

list cutOptimizer.x_bins = [x for x in range(int(float(args.x_range[0])*100),int(float(args.x_range[1])*100)+1, int((float(args.x_range[1])-float(args.x_range[0]))*4))]

list cutOptimizer.y_bins = []

list cutOptimizer.z_bins = []