Exemplo n.º 1
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 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
Exemplo n.º 2
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 def set_up_stacking(self):
     wrps = gen.pool_content()
     wrps = gen.filter(
         wrps,
         {"analyzer": re.compile("CutFlow")}
     )
     wrps = gen.group(wrps)
     stream_stack = gen.mc_stack_n_data_sum(
         wrps,
         use_all_data_lumi=True
     )
     def assign_name(wrp): wrp.name = "CombinedCutflow"
     self.stream_stack = gen.pool_store_items(stream_stack, assign_name)
Exemplo n.º 3
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 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
Exemplo n.º 4
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 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
Exemplo n.º 5
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    def test_gen_group(self):
        from_fs = gen.fs_content()
        filtered = gen.filter(from_fs, {"name": "histo"})
        sorted = gen.sort(filtered)
        grouped = gen.group(sorted)
        group_list = []
        for group in grouped:
            group_list.append(list(group))

        # length: 3 samples: 3 histos per group
        self.assertEqual(len(group_list), 26)
        for g in group_list:
            self.assertEqual(len(g), 3)
            self.assertEqual(g[0].analyzer, g[1].analyzer)
            self.assertEqual(g[0].analyzer, g[2].analyzer)
Exemplo n.º 6
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    def test_gen_group(self):
        from_fs = gen.fs_content()
        filtered = gen.filter(from_fs, {"name": "histo"})
        sorted = gen.sort(filtered)
        grouped = gen.group(sorted)
        group_list = []
        for group in grouped:
            group_list.append(list(group))

        # length: 3 samples: 3 histos per group
        self.assertEqual(len(group_list), 26)
        for g in group_list:
            self.assertEqual(len(g), 3)
            self.assertEqual(g[0].analyzer, g[1].analyzer)
            self.assertEqual(g[0].analyzer, g[2].analyzer)
Exemplo n.º 7
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    def run(self):
        wrps = gen.fs_content()
        wrps = gen.filter(
            wrps,
            {"analyzer": re.compile("CutFlow*")}
        )
        wrps = gen.filter_active_samples(wrps)
        wrps = sorted(wrps, key = sample_key_func)
        wrps = gen.load(wrps)
        grps = gen.group(wrps, sample_key_func)

        wrps = (self.combine_cutflow_histo(g) for g in grps)
        wrps = gen.pool_store_items(wrps)
        wrps = list(wrps)
        self.result = wrps
        count = len(wrps)
        self.message("INFO: "+self.name+" stored "+str(count)+" histos in pool.")
Exemplo n.º 8
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 def set_up_stacking(self):
     key_func = lambda w: w.post_proc_key
     mc_tmplts = itertools.chain(*list(
         gen.get_from_post_proc_dict(k)
         for k in settings.post_proc_dict.keys()
         if ("_mc_tmplts" in k
         )
     ))
     mc_tmplts = self.norm_func(mc_tmplts)
     mc_tmplts = cosmetica1(mc_tmplts)
     def histo_namer(wrp):
         wrp.analyzer = wrp.post_proc_key[:-10]
         return wrp
     mc_tmplts = (histo_namer(w) for w in 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
Exemplo n.º 9
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 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
Exemplo n.º 10
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    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
Exemplo n.º 11
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 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