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