def run(self):
wrp = next(rebin_chhadiso(
gen.gen_sum(
[
gen.fs_filter_active_sort_load({
"analyzer" : sb_anzlrs,
"is_data" : True
})
]
)
))
# multiply with weight
if do_dist_reweighting:
wrp = gen.op.prod((
settings.post_proc_dict["TemplateFitToolChHadIsoSbBkgInputBkgWeight"],
wrp,
))
wrp.lumi = settings.data_lumi_sum()
self.result = [wrp]
gen.consume_n_count(
gen.save(
gen.canvas((self.result,)),
lambda c: self.plot_output_dir + c.name
)
)
def run(self):
wrp = next(rebin_chhadiso(
gen.gen_sum(
[gen.fs_filter_active_sort_load({
"analyzer" : "TemplateRandConereal",
"is_data" : True
})]
)
))
# normalize to mc expectation
integral_real = next(
gen.gen_integral(
gen.gen_norm_to_data_lumi(
gen.filter(
settings.post_proc_dict["TemplateStacks"],
{"analyzer": "TemplateRandConereal"}
)
)
)
)
print integral_real
wrp = gen.op.prod((
gen.op.norm_to_integral(wrp),
integral_real
))
# multiply with weight
if do_dist_reweighting:
wrp = gen.op.prod((
settings.post_proc_dict["TemplateFitToolRandConeIsoInputSigWeight"],
wrp,
))
wrp.lumi = settings.data_lumi_sum()
self.result = [wrp]
gen.consume_n_count(
gen.save(
gen.canvas((self.result,)),
lambda c: self.plot_output_dir + c.name
)
)
