def histo_wrapperize(stk_wrps):
data_lumi = settings.data_lumi_sum_wrp()
for s_w in stk_wrps:
h_w = wrp.HistoWrapper(s_w.histo, **s_w.all_info())
h_w = gen.op.prod((h_w, data_lumi))
h_w.sub_tot_list = s_w.sub_tot_list
yield h_w
def get_input_histos(self):
mcee = gen.gen_prod( # need to norm to lumi
itertools.izip(
gen.gen_norm_to_lumi(
gen.filter(
settings.post_proc_dict["CutflowHistos"],
{"is_data": False}
)
),
itertools.repeat(
settings.data_lumi_sum_wrp()
)
)
)
data = gen.filter(
settings.post_proc_dict["CutflowHistos"],
{"is_data": True}
)
self.input_mc = sorted(mcee, key = legend_key_func)
self.input_data = sorted(data, key = legend_key_func)
def configure(self):
data_lumi = settings.data_lumi_sum_wrp()
self.data_sihih = gen.op.prod((
gen.op.merge(
gen.fs_filter_active_sort_load({
"analyzer" : "dataTemplateFitHistoSihih",
"name" : "sihihEB",
"is_data" : False,
})
),
data_lumi
))
self.data_sihih_bkg = gen.op.prod((
gen.op.merge(
gen.fs_filter_active_sort_load({
"analyzer" : "Nm1PlotSihihChHadIsoInv",
"name" : "histo",
"is_data" : False,
})
),
data_lumi
))
