def run(self):
top_sample = next(s for s in settings.active_samples if s[:2] == "TT")
wrp_fake = next(rebin_chhadiso(gen.fs_filter_sort_load({
"analyzer": "TemplateChHadIsoreal",
"sample": top_sample,#"TTMadG",
})))
wrp_sb = gen.op.merge(rebin_chhadiso(gen.fs_filter_sort_load({
"analyzer": "TemplateRandConereal",
"sample": top_sample,#"TTMadG",
})))
wrp = gen.op.div((
gen.op.norm_to_integral(wrp_fake),
gen.op.norm_to_integral(wrp_sb),
))
wrp.lumi = 1.
wrp.draw_option = "E1"
self.result = wrp
cnvs = list(gen.canvas(((wrp,),)),)
cnvs[0].canvas.SetGridy(1)
gen.consume_n_count(
gen.save(
cnvs,
lambda c: self.plot_output_dir + c.name
)
)
del wrp.draw_option
def test_gen_fs_filter_sort_load(self):
wrps = list(gen.fs_filter_sort_load({"name": "cutflow", "sample": ["ttgamma", "tt"]}))
s_is_data = map(lambda x: x.is_data, wrps)
# just check for sorting and overall length
self.assertTrue(s_is_data.index(False) < s_is_data.index(True))
self.assertEqual(len(wrps), 2)
self.assertEqual(wrps[1].lumi, 3.0)
def test_gen_fs_filter_sort_load(self):
wrps = list(
gen.fs_filter_sort_load({
"name": "cutflow",
"sample": ["ttgamma", "tt"]
}))
s_is_data = map(lambda x: x.is_data, wrps)
# just check for sorting and overall length
self.assertTrue(s_is_data.index(False) < s_is_data.index(True))
self.assertEqual(len(wrps), 2)
self.assertEqual(wrps[1].lumi, 3.0)
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 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
def test_gen_save(self):
wrps = gen.fs_filter_sort_load({"name": "cutflow", "sample": ["zjets", "ttgamma"]})
# create dir and go
if not os.path.exists("test"):
os.mkdir("test")
gen.consume_n_count(gen.save(wrps, lambda w: "test/" + w.name + "_" + w.sample))
# check the new files
self.assertTrue(os.path.exists("test/cutflow_ttgamma.root"))
self.assertTrue(os.path.exists("test/cutflow_ttgamma.info"))
self.assertTrue(os.path.exists("test/cutflow_zjets.root"))
self.assertTrue(os.path.exists("test/cutflow_zjets.info"))
self.tfile = TFile.Open("test/cutflow_ttgamma.root")
self.assertTrue(self.tfile.GetKey("histo"))
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 test_gen_save(self):
wrps = gen.fs_filter_sort_load({
"name": "cutflow",
"sample": ["zjets", "ttgamma"]
})
# create dir and go
if not os.path.exists("test"):
os.mkdir("test")
gen.consume_n_count(
gen.save(wrps, lambda w: "test/" + w.name + "_" + w.sample))
# check the new files
self.assertTrue(os.path.exists("test/cutflow_ttgamma.root"))
self.assertTrue(os.path.exists("test/cutflow_ttgamma.info"))
self.assertTrue(os.path.exists("test/cutflow_zjets.root"))
self.assertTrue(os.path.exists("test/cutflow_zjets.info"))
self.tfile = TFile.Open("test/cutflow_ttgamma.root")
self.assertTrue(self.tfile.GetKey("histo"))
def run(self):
wrps = tmpl_fit.rebin_chhadiso(gen.fs_filter_sort_load({
"analyzer": "PlotSBID",
"sample": sample,
}))
wrp = gen.op.merge(wrps)
# multiply with weight
if tmpl_fit.do_dist_reweighting:
wrp = gen.op.prod((
settings.post_proc_dict["TemplateFitToolChHadIsoSBIDInputBkgWeight"],
wrp,
))
wrps = gen.gen_norm_to_data_lumi((wrp,))
wrps = list(wrps)
self.result = wrps
gen.consume_n_count(
gen.save(
gen.canvas((wrps,)),
lambda c: self.plot_output_dir + c.name
)
)
def get_merged_sbbkg_histo(sample):
wrps = rebin_chhadiso(gen.fs_filter_sort_load({
"analyzer": sb_anzlrs,
"sample": sample,
}))
return gen.op.merge(wrps)
