def set_up_stacking(self):
key_func = lambda w: w.analyzer[:-4]
mc_tmplts = itertools.chain(*list(
gen.get_from_post_proc_dict(k)
for k in settings.post_proc_dict.keys()
if ("TemplateStacks" in k
)
))
mc_tmplts = histo_wrapperize(mc_tmplts)
mc_tmplts = gen.gen_norm_to_lumi(mc_tmplts)
mc_tmplts = cosmetica1(mc_tmplts)
mc_tmplts = sorted(mc_tmplts, key=key_func)
mc_tmplts = gen.group(mc_tmplts, key_func=key_func)
self.stream_stack = mc_tmplts
def run(self):
kicked = gen.fs_filter_active_sort_load(
{"sample":"TTJetsSignal",
"analyzer":"ttbarPhotonMergerSingleCall",
"name":re.compile("\S*Kicked")}
)
whizard = gen.fs_filter_active_sort_load(
{"sample":"whiz2to5",
"analyzer":"photonsSignalMEanalyzer"}
)
zipped = itertools.izip(kicked, whizard)
zipped = (gen.callback(z, lambda x: x.histo.SetBinContent(1,0.)) for z in zipped) # remove first bin
zipped = (gen.apply_histo_linecolor(z) for z in zipped)
zipped = (gen.apply_histo_linewidth(z) for z in zipped)
zipped = list(list(z) for z in zipped) # load all to memory
if not (zipped and zipped[0]):
self.message("WARNING Histograms not found!! Quitting..")
return
zipped[0][0].legend = "removed (madgraph)"
zipped[0][1].legend = "tt#gamma (whizard)"
def save_canvas(wrps, postfix):
canvas = gen.canvas(
wrps,
[rnd.BottomPlotRatio, rnd.LegendRight, com.SimpleTitleBox]
)
canvas = gen.save(
canvas,
lambda c: self.plot_output_dir + c.name + postfix
)
canvas = gen.switch_log_scale(canvas)
canvas = gen.save(
canvas,
lambda c: self.plot_output_dir + c.name + postfix + "_log"
)
gen.consume_n_count(canvas)
# norm to integral / lumi and save
save_canvas(
(gen.gen_norm_to_lumi(z) for z in zipped),
"_lumi"
)
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 set_up_stacking(self):
mc_tmplts = rebin_chhadiso(
gen.fs_filter_active_sort_load({
"analyzer" : all_analyzers,
})
)
mc_tmplts = gen.gen_norm_to_lumi(mc_tmplts)
mc_tmplts = gen.group(mc_tmplts)
def stack_with_purity_info(grps):
for grp in grps:
sub_tot_list = [0., 0.]
grp = list(com.count_ttgamma_photons(grp,sub_tot_list))
grp = gen.mc_stack((grp,))
grp = grp.next()
grp.sub_tot_list = sub_tot_list
yield grp
mc_tmplts = list(stack_with_purity_info(mc_tmplts))
mc_tmplts_plot = list(
gen.filter(mc_tmplts, {"analyzer": analyzers_mc})
)
self.result = mc_tmplts_plot
self.stream_stack = mc_tmplts_plot
