Functions
def	addArguments

def	matching_process

def	remove_procs_and_systs_with_zero_yield2

def	remove_procs_and_systs_with_zero_yield

Variables
tuple	log = logging.getLogger(__name__)

tuple	pp = pprint.PrettyPrinter(indent=4)

dictionary	decayMode_dict

tuple	parser

tuple	args = parser.parse_args()

list	es_shifts = [args.shift_ranges[0] + x * args.shift_binning for x in range(int((args.shift_ranges[1] - args.shift_ranges[0]) / args.shift_binning) + 1)]

list	es_shifts_str = [str(x) for x in es_shifts]

tuple	decay_modes = copy.deepcopy(args.decay_modes)

list	pt_ranges = ["0.0"]

list	pt_weights = ["(pt_2>20)"]

list	pt_strings = ["p_{T}(#tau_{h}) > 20 GeV"]

list	pt_bins = [str(x) for x in range(0, len(pt_ranges))]

list	eta_ranges = ["0.0", "1.479", "2.3"]

list	eta_weights = ["(abs(eta_2)<2.3)", "(abs(eta_2)<1.479)", "(abs(eta_2)>1.479)*(abs(eta_2)<2.3)"]

list	eta_strings = ["\|#eta(#tau_{h})\| < 2.3", "\|#eta(#tau_{h})\| < 1.479", "1.479 < \|#eta(#tau_{h})\| < 2.3"]

list	eta_bins = ["0", "1", "2"]

tuple	weight_type = ("eta" if args.eta_binning else "pt")

tuple	weight_ranges = (eta_ranges if args.eta_binning else pt_ranges)

tuple	extra_weights = (eta_weights if args.eta_binning else pt_weights)

tuple	weight_strings = (eta_strings if args.eta_binning else pt_strings)

tuple	weight_bins = (eta_bins if args.eta_binning else pt_bins)

tuple	sample_settings = samples.Samples()

tuple	systematics_factory = systematics.SystematicsFactory()

	quantity = args.quantity

string	tmp_input_root_filename_template = "input/${ANALYSIS}_${CHANNEL}_${BIN}_${SYSTEMATIC}_${ERA}.root"

string	input_root_filename_template = "input/${ANALYSIS}_${CHANNEL}_${BIN}_${ERA}.root"

string	bkg_histogram_name_template = "${BIN}/${PROCESS}"

string	sig_histogram_name_template = "${BIN}/${PROCESS}${MASS}"

string	bkg_syst_histogram_name_template = "${BIN}/${PROCESS}_${SYSTEMATIC}"

string	sig_syst_histogram_name_template = "${BIN}/${PROCESS}${MASS}_${SYSTEMATIC}"

list	datacard_filename_templates = ["datacards/${BIN}/${ANALYSIS}_${CHANNEL}_${BIN}_${ERA}.txt"]

string	output_root_filename_template = "datacards/common/${ANALYSIS}.input_${ERA}.root"

list	categories = []

dictionary	mapping_category2binid = {}

string	category = channel+"_"

dictionary	ss_os_factors

tuple	datacards = taupogdatacards.TauEsDatacards(es_shifts_str, decay_modes, quantity, weight_bins, weight_type, args.era, mapping_category2binid)

tuple	channel = category.split("_")

tuple	decayMode = category.split("_")

tuple	weight_index = int(category.split("_")[-1].split(weight_type + "bin")[-1])

int	useRelaxedIsolation = weight_index>0

tuple	output_file

list	input_plot_configs = []

list	hadd_commands = []

tuple	datacards_per_channel_category = taupogdatacards.TauEsDatacards(cb=datacards.cb.cp().channel([channel]).bin([category]), mapping_category2binid=mapping_category2binid)

list	tmp_output_files = []

tuple	nominal = (shape_systematic == "nominal")

tuple	list_of_samples = (["data"] if nominal else [])

string	systematic = "nominal"

string	samples = "\", \""

float	wj_sf_shift = 0.0

dictionary	merged_config = {}

string	catForConfig = "cat"

tuple	config_rest

	histogram_name_template = bkg_histogram_name_templateifnominalelsebkg_syst_histogram_name_template

tuple	PROCESS = datacards.configs.sample2process(sample)

	BIN = category,

	SYSTEMATIC = systematic

tuple	systematics_settings = systematics_factory.get(shape_systematic)

tuple	config_ztt

tuple	MASS = str(shift)

tuple	tmp_output_file

	DST = output_file,

string	SRC = " "

tuple	output_files = list(set([os.path.join(config["output_dir"], config["filename"]+".root") for config in input_plot_configs[:args.n_plots[0]]]))

	update_systematics = True

tuple	processes = datacards.cb.cp()

float	add_threshold = 0.1

dictionary	datacards_cbs = {}

tuple	datacards_workspaces = datacards.text2workspace(datacards_cbs, n_processes=args.n_processes)

	VERBOSITY = args.combine_verbosity,

	STABLE = datacards.stable_options

tuple	BINNING = int((args.shift_ranges[1]-args.shift_ranges[0])/args.shift_binning)

tuple	RANGE = str(args.shift_ranges[0])

tuple	datacards_postfit_shapes = datacards.postfit_shapes_fromworkspace(datacards_cbs, datacards_workspaces, True, args.n_processes, "--sampling" + (" --print" if args.n_processes <= 1 else ""))

list	www_output_dirs_postfit = []

list	www_output_dirs_weightbin = []

list	www_output_dirs_parabola = []

list	postfit_plot_configs = []

list	bkg_plotting_order = ["ZTT", "ZL", "ZJ", "TTT","TTJJ", "VVT", "VVJ", "W", "QCD"]

tuple	postfit_shapes = datacards_postfit_shapes.get("fit_s", {})

tuple	weightBin = int(category.split("_")[-1].split(weight_type+"bin")[-1])

list	bkg_process = datacards_cbs[datacard]

list	sig_process = datacards_cbs[datacard]

dictionary	config = {}

tuple	processes_to_plot = list(processes)

list	parabola_plot_configs = []

list	weightbin_plot_configs = []

tuple	filename_mlfit = os.path.join(os.path.dirname(datacard), args.combine_cmssw==8 * "fitDiagnostics.root" + args.combine_cmssw==7 * "mlfit.root")

tuple	file_mlfit = ROOT.TFile(filename_mlfit)

tuple	tree_mlfit = file_mlfit.Get("tree_fit_sb")

tuple	filename_multidimfit = os.path.join(os.path.dirname(datacard), "higgsCombineTest.MultiDimFit.mH0.root")

tuple	file_multidimfit = ROOT.TFile(filename_multidimfit)

tuple	tree_multidimfit = file_multidimfit.Get("limit")

list	mes_list = []

list	deltaNLL_list = []

list	deltaNLLshifted_list = []

list	min_nll = deltaNLL_list[0]

list	min_shift = mes_list[0]

list	mes_list_nll_belowX = []

list	nll_belowX = []

int	nllMax = 10

	found2sigmaLow = True

tuple	err2sigmaLow = abs((mes_list[index-1]+mes_list[index])/2.0 - min_shift)

	found1sigmaLow = True

tuple	err1sigmaLow = abs((mes_list[index-1]+mes_list[index])/2.0 - min_shift)

	found1sigmaHi = True

tuple	err1sigmaHi = abs((mes_list[index]+mes_list[index+1])/2.0 - min_shift)

	found2sigmaHi = True

tuple	err2sigmaHi = abs((mes_list[index]+mes_list[index+1])/2.0 - min_shift)

list	xvaluesF = []

string	xvalues = ""

string	yvalues = ""

list	xvaluesF_belowX = []

tuple	RooFitGraph_Parabola

tuple	fitf = ROOT.TF1("f1","pol2",min(xvaluesF_belowX),max(xvaluesF_belowX))

tuple	minimumScanFit = fitf.GetMinimumX(min(xvaluesF_belowX),max(xvaluesF_belowX))

tuple	minimumScanFitY = fitf.GetMinimum(min(xvaluesF_belowX),max(xvaluesF_belowX))

tuple	sigmaScanFit = abs(fitf.GetX(minimumScanFitY+1)-minimumScanFit)

tuple	graphfilename = os.path.join(os.path.dirname(datacard), "parabola_" + category + ("_tightenedMassWindow" if args.tighten_mass_window else "")+".root")

tuple	graphfile = ROOT.TFile(graphfilename, "RECREATE")

list	weight_bins_loop = weight_binsifargs.no_inclusiveelseweight_bins[1:]

list	weight_ranges_loop = weight_rangesifargs.no_inclusiveelseweight_ranges[1:]

string	xval = "0.7395 2.2185"

string	xerrsval = "0.7395 0.7395"

list	xbinsF = [0.7395, 2.2185]

list	xerrsF = [0.7395, 0.7395]

tuple	RooFitGraph_Linear

tuple	fit_polZero = ROOT.TF1("f2","pol0",min(xbinsF),max(xbinsF))

tuple	fit_polOne = ROOT.TF1("f3","pol1",min(xbinsF),max(xbinsF))

tuple	polZero_filename = os.path.join(args.output_dir, "datacards/result_fit_" + ("eta" if args.eta_binning else "pt") + "_pol0_" + decayMode + "_" + quantity + ".root")

tuple	polZero_file = ROOT.TFile(polZero_filename, "RECREATE")

tuple	polOne_filename = os.path.join(args.output_dir, "datacards/result_fit_" + ("eta" if args.eta_binning else "pt") + "_pol1_" + decayMode + "_" + quantity + ".root")

tuple	polOne_file = ROOT.TFile(polOne_filename, "RECREATE")

string	row_format = "{:^22}"

string	polZero_string1 = "%1.2f"

string	polZero_string2 = "%1.2f"

string	polOne_string1 = "%1.2f"

string	polOne_string2 = "%1.2f"

tuple	subpath = os.path.normpath(output_dir)

list	output_filenames = []

tuple	www = args.wwwif(subpath == "tauEsStudies_datacards")

	output_dir = output_dir,

	export_json = False,

Function Documentation

def makePlots_datacardsTauEsStudies.addArguments ( parser )

def makePlots_datacardsTauEsStudies.matching_process	(	obj1,
		obj2
	)

def makePlots_datacardsTauEsStudies.remove_procs_and_systs_with_zero_yield ( proc )

def makePlots_datacardsTauEsStudies.remove_procs_and_systs_with_zero_yield2 ( proc )

Variable Documentation

float makePlots_datacardsTauEsStudies.add_threshold = 0.1

tuple makePlots_datacardsTauEsStudies.args = parser.parse_args()

makePlots_datacardsTauEsStudies.BIN = category,

tuple makePlots_datacardsTauEsStudies.BINNING = int((args.shift_ranges[1]-args.shift_ranges[0])/args.shift_binning)

string makePlots_datacardsTauEsStudies.bkg_histogram_name_template = "${BIN}/${PROCESS}"

list makePlots_datacardsTauEsStudies.bkg_plotting_order = ["ZTT", "ZL", "ZJ", "TTT","TTJJ", "VVT", "VVJ", "W", "QCD"]

list makePlots_datacardsTauEsStudies.bkg_process = datacards_cbs[datacard]

string makePlots_datacardsTauEsStudies.bkg_syst_histogram_name_template = "${BIN}/${PROCESS}_${SYSTEMATIC}"

list makePlots_datacardsTauEsStudies.categories = []

tuple makePlots_datacardsTauEsStudies.category = channel+"_"

string makePlots_datacardsTauEsStudies.catForConfig = "cat"

tuple makePlots_datacardsTauEsStudies.channel = category.split("_")

dictionary makePlots_datacardsTauEsStudies.config = {}

tuple makePlots_datacardsTauEsStudies.config_rest

Initial value:

 = sample_settings.get_config(
                                         samples=[getattr(samples.Samples, sample) for sample in list_of_samples if sample not in ["ztt", "ttt", "vvt"]],
                                         channel=channel,
                                         category=catForConfig,
                                         nick_suffix="_" + str(weight_index),
                                         weight="(pt_2>20)*" + args.weight,
                                         lumi=args.lumi * 1000,
                                         cut_type="tauescuts2016" if args.era == "2016" else "tauescuts",
                                         estimationMethod=args.background_method,
                                         wj_sf_shift=wj_sf_shift,
                                         ss_os_factor = ss_os_factors.get(channel, 0.0),
                                         useRelaxedIsolationForW = useRelaxedIsolation,
                                         useRelaxedIsolationForQCD = useRelaxedIsolation
                                 )

tuple makePlots_datacardsTauEsStudies.config_ztt

Initial value:

 = sample_settings.get_config(
                                                 samples=[getattr(samples.Samples, sample) for sample in list_of_samples if sample in ["ztt", "ttt", "vvt"]],
                                                 channel=channel,
                                                 category=catForConfig,
                                                 nick_suffix="_" + str(shift).replace(".", "_") + "_" + str(weight_index),
                                                 weight="(pt_2>20)*" + args.weight,
                                                 lumi=args.lumi * 1000,
                                                 cut_type="tauescuts2016" if args.era == "2016" else "tauescuts",
                                                 estimationMethod=args.background_method,
                                                 wj_sf_shift=wj_sf_shift,
                                                 ss_os_factor = ss_os_factors.get(channel,0.0),
                                                 useRelaxedIsolation = useRelaxedIsolation
                                         )

list makePlots_datacardsTauEsStudies.datacard_filename_templates = ["datacards/${BIN}/${ANALYSIS}_${CHANNEL}_${BIN}_${ERA}.txt"]

tuple makePlots_datacardsTauEsStudies.datacards = taupogdatacards.TauEsDatacards(es_shifts_str, decay_modes, quantity, weight_bins, weight_type, args.era, mapping_category2binid)

dictionary makePlots_datacardsTauEsStudies.datacards_cbs = {}

tuple makePlots_datacardsTauEsStudies.datacards_per_channel_category = taupogdatacards.TauEsDatacards(cb=datacards.cb.cp().channel([channel]).bin([category]), mapping_category2binid=mapping_category2binid)

tuple makePlots_datacardsTauEsStudies.datacards_postfit_shapes = datacards.postfit_shapes_fromworkspace(datacards_cbs, datacards_workspaces, True, args.n_processes, "--sampling" + (" --print" if args.n_processes <= 1 else ""))

tuple makePlots_datacardsTauEsStudies.datacards_workspaces = datacards.text2workspace(datacards_cbs, n_processes=args.n_processes)

tuple makePlots_datacardsTauEsStudies.decay_modes = copy.deepcopy(args.decay_modes)

tuple makePlots_datacardsTauEsStudies.decayMode = category.split("_")

dictionary makePlots_datacardsTauEsStudies.decayMode_dict

Initial value:

 = {
         "AllDMs" :
         {
                 "color" : "1",
                 "label" : "All decay modes"
         },
         "OneProng" :
         {
                 "color" : "2",
                 "label" : "h^{#pm} decay mode"
         },
         "OneProngPiZeros" :
         {
                 "color" : "4",
                 "label" : "h^{#pm}#pi^{0} decay mode"
         },
         "ThreeProng" :
         {
                 "color" : "6",
                 "label" : "h^{#pm}h^{#pm}h^{#mp} decay mode"
         }
 }

list makePlots_datacardsTauEsStudies.deltaNLL_list = []

list makePlots_datacardsTauEsStudies.deltaNLLshifted_list = []

makePlots_datacardsTauEsStudies.DST = output_file,

tuple makePlots_datacardsTauEsStudies.err1sigmaHi = abs((mes_list[index]+mes_list[index+1])/2.0 - min_shift)

tuple makePlots_datacardsTauEsStudies.err1sigmaLow = abs((mes_list[index-1]+mes_list[index])/2.0 - min_shift)

tuple makePlots_datacardsTauEsStudies.err2sigmaHi = abs((mes_list[index]+mes_list[index+1])/2.0 - min_shift)

tuple makePlots_datacardsTauEsStudies.err2sigmaLow = abs((mes_list[index-1]+mes_list[index])/2.0 - min_shift)

list makePlots_datacardsTauEsStudies.es_shifts = [args.shift_ranges[0] + x * args.shift_binning for x in range(int((args.shift_ranges[1] - args.shift_ranges[0]) / args.shift_binning) + 1)]

list makePlots_datacardsTauEsStudies.es_shifts_str = [str(x) for x in es_shifts]

list makePlots_datacardsTauEsStudies.eta_bins = ["0", "1", "2"]

list makePlots_datacardsTauEsStudies.eta_ranges = ["0.0", "1.479", "2.3"]

list makePlots_datacardsTauEsStudies.eta_strings = ["|#eta(#tau_{h})| < 2.3", "|#eta(#tau_{h})| < 1.479", "1.479 < |#eta(#tau_{h})| < 2.3"]

list makePlots_datacardsTauEsStudies.eta_weights = ["(abs(eta_2)<2.3)", "(abs(eta_2)<1.479)", "(abs(eta_2)>1.479)*(abs(eta_2)<2.3)"]

makePlots_datacardsTauEsStudies.export_json = False,

tuple makePlots_datacardsTauEsStudies.extra_weights = (eta_weights if args.eta_binning else pt_weights)

tuple makePlots_datacardsTauEsStudies.file_mlfit = ROOT.TFile(filename_mlfit)

tuple makePlots_datacardsTauEsStudies.file_multidimfit = ROOT.TFile(filename_multidimfit)

tuple makePlots_datacardsTauEsStudies.filename_mlfit = os.path.join(os.path.dirname(datacard), args.combine_cmssw==8 * "fitDiagnostics.root" + args.combine_cmssw==7 * "mlfit.root")

tuple makePlots_datacardsTauEsStudies.filename_multidimfit = os.path.join(os.path.dirname(datacard), "higgsCombineTest.MultiDimFit.mH0.root")

tuple makePlots_datacardsTauEsStudies.fit_polOne = ROOT.TF1("f3","pol1",min(xbinsF),max(xbinsF))

tuple makePlots_datacardsTauEsStudies.fit_polZero = ROOT.TF1("f2","pol0",min(xbinsF),max(xbinsF))

tuple makePlots_datacardsTauEsStudies.fitf = ROOT.TF1("f1","pol2",min(xvaluesF_belowX),max(xvaluesF_belowX))

makePlots_datacardsTauEsStudies.found1sigmaHi = True

makePlots_datacardsTauEsStudies.found1sigmaLow = True

makePlots_datacardsTauEsStudies.found2sigmaHi = True

makePlots_datacardsTauEsStudies.found2sigmaLow = True

tuple makePlots_datacardsTauEsStudies.graphfile = ROOT.TFile(graphfilename, "RECREATE")

tuple makePlots_datacardsTauEsStudies.graphfilename = os.path.join(os.path.dirname(datacard), "parabola_" + category + ("_tightenedMassWindow" if args.tighten_mass_window else "")+".root")

list makePlots_datacardsTauEsStudies.hadd_commands = []

makePlots_datacardsTauEsStudies.histogram_name_template = bkg_histogram_name_templateifnominalelsebkg_syst_histogram_name_template

list makePlots_datacardsTauEsStudies.input_plot_configs = []

string makePlots_datacardsTauEsStudies.input_root_filename_template = "input/${ANALYSIS}_${CHANNEL}_${BIN}_${ERA}.root"

tuple makePlots_datacardsTauEsStudies.list_of_samples = (["data"] if nominal else [])

tuple makePlots_datacardsTauEsStudies.log = logging.getLogger(__name__)

dictionary makePlots_datacardsTauEsStudies.mapping_category2binid = {}

tuple makePlots_datacardsTauEsStudies.MASS = str(shift)

tuple makePlots_datacardsTauEsStudies.merged_config = {}

list makePlots_datacardsTauEsStudies.mes_list = []

list makePlots_datacardsTauEsStudies.mes_list_nll_belowX = []

list makePlots_datacardsTauEsStudies.min_nll = deltaNLL_list[0]

list makePlots_datacardsTauEsStudies.min_shift = mes_list[0]

tuple makePlots_datacardsTauEsStudies.minimumScanFit = fitf.GetMinimumX(min(xvaluesF_belowX),max(xvaluesF_belowX))

tuple makePlots_datacardsTauEsStudies.minimumScanFitY = fitf.GetMinimum(min(xvaluesF_belowX),max(xvaluesF_belowX))

list makePlots_datacardsTauEsStudies.nll_belowX = []

int makePlots_datacardsTauEsStudies.nllMax = 10

tuple makePlots_datacardsTauEsStudies.nominal = (shape_systematic == "nominal")

makePlots_datacardsTauEsStudies.output_dir = output_dir,

tuple makePlots_datacardsTauEsStudies.output_file

Initial value:

 = os.path.join(args.output_dir, input_root_filename_template.replace("$", "").format(
                         ANALYSIS="ztt",
                         CHANNEL=channel,
                         BIN=category,
                         ERA="13TeV"
                 ))

list makePlots_datacardsTauEsStudies.output_filenames = []

tuple makePlots_datacardsTauEsStudies.output_files = list(set([os.path.join(config["output_dir"], config["filename"]+".root") for config in input_plot_configs[:args.n_plots[0]]]))

string makePlots_datacardsTauEsStudies.output_root_filename_template = "datacards/common/${ANALYSIS}.input_${ERA}.root"

list makePlots_datacardsTauEsStudies.parabola_plot_configs = []

tuple makePlots_datacardsTauEsStudies.parser

Initial value:

1 = argparse.ArgumentParser(description="Create ROOT inputs and datacards for tau energy scale measurement.",

2 parents=[logger.loggingParser])

tuple makePlots_datacardsTauEsStudies.polOne_file = ROOT.TFile(polOne_filename, "RECREATE")

tuple makePlots_datacardsTauEsStudies.polOne_filename = os.path.join(args.output_dir, "datacards/result_fit_" + ("eta" if args.eta_binning else "pt") + "_pol1_" + decayMode + "_" + quantity + ".root")

string makePlots_datacardsTauEsStudies.polOne_string1 = "%1.2f"

string makePlots_datacardsTauEsStudies.polOne_string2 = "%1.2f"

tuple makePlots_datacardsTauEsStudies.polZero_file = ROOT.TFile(polZero_filename, "RECREATE")

tuple makePlots_datacardsTauEsStudies.polZero_filename = os.path.join(args.output_dir, "datacards/result_fit_" + ("eta" if args.eta_binning else "pt") + "_pol0_" + decayMode + "_" + quantity + ".root")

string makePlots_datacardsTauEsStudies.polZero_string1 = "%1.2f"

string makePlots_datacardsTauEsStudies.polZero_string2 = "%1.2f"

list makePlots_datacardsTauEsStudies.postfit_plot_configs = []

tuple makePlots_datacardsTauEsStudies.postfit_shapes = datacards_postfit_shapes.get("fit_s", {})

tuple makePlots_datacardsTauEsStudies.pp = pprint.PrettyPrinter(indent=4)

tuple makePlots_datacardsTauEsStudies.PROCESS = datacards.configs.sample2process(sample)

list makePlots_datacardsTauEsStudies.processes = datacards.cb.cp()

list makePlots_datacardsTauEsStudies.processes_to_plot = list(processes)

list makePlots_datacardsTauEsStudies.pt_bins = [str(x) for x in range(0, len(pt_ranges))]

list makePlots_datacardsTauEsStudies.pt_ranges = ["0.0"]

list makePlots_datacardsTauEsStudies.pt_strings = ["p_{T}(#tau_{h}) > 20 GeV"]

list makePlots_datacardsTauEsStudies.pt_weights = ["(pt_2>20)"]

makePlots_datacardsTauEsStudies.quantity = args.quantity

tuple makePlots_datacardsTauEsStudies.RANGE = str(args.shift_ranges[0])

tuple makePlots_datacardsTauEsStudies.RooFitGraph_Linear

Initial value:

 = ROOT.TGraphAsymmErrors(
                                 len(xbinsF),
                                 array.array("d", xbinsF),
                                 array.array("d", ybinsF),
                                 array.array("d", xerrsF),
                                 array.array("d", xerrsF),
                                 array.array("d", yerrsloF),
                                 array.array("d", yerrshiF)
                         )

tuple makePlots_datacardsTauEsStudies.RooFitGraph_Parabola

Initial value:

 = ROOT.TGraphErrors(
                                 len(xvaluesF),
                                 array.array("d", xvaluesF),
                                 array.array("d", deltaNLLshifted_list),
                                 array.array("d", [0.1]*len(xvaluesF)),
                                 array.array("d", [1.0*nllMax/10.0]*len(xvaluesF)) # this is an arbitrary value in order to be able to fit also not so smooth parabolas
                         )

string makePlots_datacardsTauEsStudies.row_format = "{:^22}"

tuple makePlots_datacardsTauEsStudies.sample_settings = samples.Samples()

string makePlots_datacardsTauEsStudies.samples = "\", \""

string makePlots_datacardsTauEsStudies.sig_histogram_name_template = "${BIN}/${PROCESS}${MASS}"

list makePlots_datacardsTauEsStudies.sig_process = datacards_cbs[datacard]

string makePlots_datacardsTauEsStudies.sig_syst_histogram_name_template = "${BIN}/${PROCESS}${MASS}_${SYSTEMATIC}"

tuple makePlots_datacardsTauEsStudies.sigmaScanFit = abs(fitf.GetX(minimumScanFitY+1)-minimumScanFit)

string makePlots_datacardsTauEsStudies.SRC = " "

dictionary makePlots_datacardsTauEsStudies.ss_os_factors

Initial value:

 = {
                 "mt" : 1.06,
                 "et" : 1.0
         }

makePlots_datacardsTauEsStudies.STABLE = datacards.stable_options

tuple makePlots_datacardsTauEsStudies.subpath = os.path.normpath(output_dir)

makePlots_datacardsTauEsStudies.systematic = "nominal"

makePlots_datacardsTauEsStudies.SYSTEMATIC = systematic

tuple makePlots_datacardsTauEsStudies.systematics_factory = systematics.SystematicsFactory()

tuple makePlots_datacardsTauEsStudies.systematics_settings = systematics_factory.get(shape_systematic)

string makePlots_datacardsTauEsStudies.tmp_input_root_filename_template = "input/${ANALYSIS}_${CHANNEL}_${BIN}_${SYSTEMATIC}_${ERA}.root"

tuple makePlots_datacardsTauEsStudies.tmp_output_file

Initial value:

 = os.path.join(args.output_dir, tmp_input_root_filename_template.replace("$", "").format(
                                         ANALYSIS="ztt",
                                         CHANNEL=channel,
                                         BIN=category,
                                         SYSTEMATIC=systematic,
                                         ERA="13TeV"
                                 ))

list makePlots_datacardsTauEsStudies.tmp_output_files = []

tuple makePlots_datacardsTauEsStudies.tree_mlfit = file_mlfit.Get("tree_fit_sb")

tuple makePlots_datacardsTauEsStudies.tree_multidimfit = file_multidimfit.Get("limit")

makePlots_datacardsTauEsStudies.update_systematics = True

int makePlots_datacardsTauEsStudies.useRelaxedIsolation = weight_index>0

makePlots_datacardsTauEsStudies.VERBOSITY = args.combine_verbosity,

tuple makePlots_datacardsTauEsStudies.weight_bins = (eta_bins if args.eta_binning else pt_bins)

list makePlots_datacardsTauEsStudies.weight_bins_loop = weight_binsifargs.no_inclusiveelseweight_bins[1:]

int makePlots_datacardsTauEsStudies.weight_index = int(category.split("_")[-1].split(weight_type + "bin")[-1])

tuple makePlots_datacardsTauEsStudies.weight_ranges = (eta_ranges if args.eta_binning else pt_ranges)

list makePlots_datacardsTauEsStudies.weight_ranges_loop = weight_rangesifargs.no_inclusiveelseweight_ranges[1:]

tuple makePlots_datacardsTauEsStudies.weight_strings = (eta_strings if args.eta_binning else pt_strings)

tuple makePlots_datacardsTauEsStudies.weight_type = ("eta" if args.eta_binning else "pt")

tuple makePlots_datacardsTauEsStudies.weightBin = int(category.split("_")[-1].split(weight_type+"bin")[-1])

list makePlots_datacardsTauEsStudies.weightbin_plot_configs = []

float makePlots_datacardsTauEsStudies.wj_sf_shift = 0.0

tuple makePlots_datacardsTauEsStudies.www = args.wwwif(subpath == "tauEsStudies_datacards")

list makePlots_datacardsTauEsStudies.www_output_dirs_parabola = []

list makePlots_datacardsTauEsStudies.www_output_dirs_postfit = []

list makePlots_datacardsTauEsStudies.www_output_dirs_weightbin = []

list makePlots_datacardsTauEsStudies.xbinsF = [0.7395, 2.2185]

list makePlots_datacardsTauEsStudies.xerrsF = [0.7395, 0.7395]

string makePlots_datacardsTauEsStudies.xerrsval = "0.7395 0.7395"

string makePlots_datacardsTauEsStudies.xval = "0.7395 2.2185"

string makePlots_datacardsTauEsStudies.xvalues = ""

list makePlots_datacardsTauEsStudies.xvaluesF = []

list makePlots_datacardsTauEsStudies.xvaluesF_belowX = []

string makePlots_datacardsTauEsStudies.yvalues = ""

Functions

Variables

Function Documentation

Variable Documentation