def set_up_stacking(self):
mc_tmplts = self.__dict__["input_func"]()
mc_tmplts = gen.gen_norm_to_integral(mc_tmplts)
mc_tmplts = cosmetica1(mc_tmplts)
mc_tmplts = rebin_chhadiso(mc_tmplts)
mc_tmplts = gen.apply_histo_linecolor(mc_tmplts, [409, 625, 618, 596, 430])
mc_tmplts = gen.group(mc_tmplts, key_func=lambda w: w.sample)
self.stream_stack = mc_tmplts
def set_up_stacking(self):
mc_tmplts = gen.fs_filter_sort_load({
"sample" : self.sample_name,
"analyzer" : ("TemplateChHadIsofake", "PlotSBID")
})
sb_wrp = get_merged_sbbkg_histo(self.sample_name)
mc_tmplts = [sb_wrp] + list(mc_tmplts)
mc_tmplts = gen.gen_norm_to_integral(mc_tmplts)
mc_tmplts = cosmetica1(mc_tmplts)
mc_tmplts = rebin_chhadiso(mc_tmplts)
mc_tmplts = gen.apply_histo_linecolor(mc_tmplts, [625, 618, 596])
mc_tmplts = apply_overlay_draw_mode(mc_tmplts)
mc_tmplts = gen.group(mc_tmplts, key_func=lambda w: w.sample)
self.stream_stack = mc_tmplts
def run(self):
RandCone = gen.fs_filter_active_sort_load(
{"sample":"whiz2to5",
"analyzer":"PlotRandCone"}
)
ChHad = gen.fs_filter_active_sort_load(
{ "sample":"whiz2to5",
"analyzer":"TemplateChHadIsoreal"}
)
zipped = itertools.izip(RandCone, ChHad)
#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 = "Rand. Cone Iso."
zipped[0][1].legend = "Charged Had. Iso."
zipped[0][1].primary_object().SetLineColor(1)
def save_canvas(wrps, postfix):
canvas = gen.canvas(
wrps,
[rnd.BottomPlotRatio, rnd.Legend, 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"
# )
save_canvas(
(gen.gen_norm_to_integral(z) for z in zipped),
"_int"
)
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 set_up_stacking(self):
mc_tmplts = gen.fs_filter_sort_load({
"sample" : ("whiz2to5", "TTGamRD1"),
"analyzer" : "TemplateChHadIsoreal",
})
mc_tmplts = gen.gen_norm_to_integral(mc_tmplts)
mc_tmplts = cosmetica1(mc_tmplts)
def leg(wrps):
for w in wrps:
w.legend = w.sample
w.draw_option = "E1"
w.histo.SetMarkerStyle(24)
yield w
mc_tmplts = leg(mc_tmplts)
mc_tmplts = rebin_chhadiso(mc_tmplts)
mc_tmplts = gen.apply_histo_linecolor(mc_tmplts, [409, 625, 618, 596, 430])
mc_tmplts = gen.group(mc_tmplts, key_func=lambda w: w.analyzer)
self.stream_stack = mc_tmplts
def set_up_stacking(self):
def sum_up_two(wrps):
while True:
try:
h = gen.op.sum((next(wrps), next(wrps)))
except StopIteration:
return
yield h
mc_tmplts = list(sum_up_two(gen.fs_filter_sort_load({
"sample" : self.sample_name,
"analyzer" : re.compile("PlotLooseIDSliceSihihSB"),
})))
mc_tmplts = itertools.chain(gen.fs_filter_sort_load({
"sample" : self.sample_name,
"analyzer" : "TemplateChHadIsofake",
}),
mc_tmplts
)
mc_tmplts = gen.gen_norm_to_integral(mc_tmplts)
mc_tmplts = cosmetica1(mc_tmplts)
mc_tmplts = rebin_chhadiso(mc_tmplts)
mc_tmplts = gen.apply_histo_linecolor(mc_tmplts, [409, 625, 618, 596, 430])
mc_tmplts = gen.group(mc_tmplts, key_func=lambda w: w.sample)
self.stream_stack = mc_tmplts
