def make_fakes_view(weight_type, scale): scaled_bare_data = views.ScaleView(all_data_view, scale) scaled_wz_data = views.ScaleView(all_wz_view, scale) scaled_data = SubtractionView(scaled_bare_data, scaled_wz_data, restrict_positive=True) # View of weighted obj1-fails data obj1_view = views.SubdirectoryView( scaled_data, 'ss/%s/f1p2f3/%s1' % (tau_charge, weight_type)) # View of weighted obj2-fails data obj2_view = views.SubdirectoryView( scaled_data, 'ss/%s/p1f2f3/%s2' % (tau_charge, weight_type)) # View of weighted obj1&2-fails data obj12_view = views.SubdirectoryView( scaled_data, 'ss/%s/f1f2f3/%s12' % (tau_charge, weight_type)) # Give the individual object views nice colors obj1_view = views.TitleView( views.StyleView(obj1_view, **remove_name_entry(data_styles['TT*'])), 'Reducible bkg. 1') obj2_view = views.TitleView( views.StyleView(obj2_view, **remove_name_entry(data_styles['QCD*'])), 'Reducible bkg. 2') obj12_view = views.TitleView( views.StyleView(obj12_view, **remove_name_entry(data_styles['WW*'])), 'Reducible bkg. 12') subtract_obj12_view = views.ScaleView(obj12_view, -1) return obj1_view, obj2_view, obj12_view, subtract_obj12_view
def make_qcd_proj_views(self, control_region, rebin): ''' Make views when obj1 or obj2 fails, projecting QCD in QCD comes from the triple fake region ''' all_data_view = self.rebin_view(self.get_view('data'), rebin) mapping = { 1: { 'obs': 'ss/tau_os/f1p2p3', 'qcd': 'ss/tau_os/f1f2f3/w23', }, 2: { 'obs': 'ss/tau_os/p1f2p3', 'qcd': 'ss/tau_os/f1f2f3/w13', }, } data_view = views.TitleView(views.SubdirectoryView( all_data_view, mapping[control_region]['obs']), "Anti-iso obj %i" % control_region) qcd_view = views.TitleView(views.SubdirectoryView( all_data_view, mapping[control_region]['qcd']), "QCD") qcd_view = views.StyleView( qcd_view, drawstyle='hist', linecolor=colors['red'], fillstyle=0, legendstyle='l' ) return {'obs': data_view, 'qcd': qcd_view}
def make_signal_views(self, rebin, unblinded=True): ''' Make signal views with FR background estimation ''' wz_view = views.SubdirectoryView( self.rebin_view(self.get_view('WZ*'), rebin), 'os/All_Passed/') zz_view = views.SubdirectoryView( self.rebin_view(self.get_view('ZZ*'), rebin), 'os/All_Passed/') all_data_view = self.rebin_view(self.get_view('data'), rebin) if unblinded and self.blind: all_data_view = self.rebin_view( self.get_view('data', 'unblinded_view'), rebin) data_view = views.SubdirectoryView(all_data_view, 'os/All_Passed/') #Categories (to match Abdollah's naming convention) probes = [p + 'IsoFailed' for p in products_map[self.channel][1]] cat0 = 'os/' + '_'.join(probes) + '/all_weights_applied/' cat1 = 'os/' + probes[0] + '/obj1_weight/' cat2 = 'os/' + probes[1] + '/obj2_weight/' # View of weighted obj1-fails data cat1_view = views.SubdirectoryView(all_data_view, cat1) # View of weighted obj2-fails data cat2_view = views.SubdirectoryView(all_data_view, cat2) # View of weighted obj1&2-fails data cat0_view = views.SubdirectoryView(all_data_view, cat0) subtract_cat0_view = views.ScaleView(cat0_view, -1) # Corrected fake view Zjets_view = views.SumView(cat1_view, cat2_view, subtract_cat0_view) Zjets_view = views.TitleView( views.StyleView(Zjets_view, **data_styles['Zjets*']), 'Non-prompt') charge_fakes = views.TitleView( views.StyleView( views.SubdirectoryView(all_data_view, 'os/p1p2p3/c1'), **data_styles['TT*']), 'Charge mis-id') output = { 'wz': wz_view, 'zz': zz_view, 'data': data_view, 'cat1': cat1_view, 'cat2': cat2_view, 'Zjets': Zjets_view, 'charge_fakes': charge_fakes, } # Add signal for mass in [110, 120, 130, 140]: vh_view = views.SubdirectoryView( self.rebin_view(self.get_view('VH_H2Tau_M-%i' % mass), rebin), 'os/All_Passed/') output['vh%i' % mass] = vh_view ww_view = views.SubdirectoryView( self.rebin_view(self.get_view('VH_%i_HWW' % mass), rebin), 'os/All_Passed/') output['vh%i_hww' % mass] = ww_view output['signal%i' % mass] = views.SumView(ww_view, vh_view) return output
def make_signal_views(self, rebin, unblinded=True): ''' Make signal views with FR background estimation ''' wz_view = views.SubdirectoryView( self.rebin_view(self.get_view('WZJetsTo3LNu*'), rebin), 'ss/p1p2p3/') zz_view = views.SubdirectoryView( self.rebin_view(self.get_view('ZZJetsTo4L*'), rebin), 'ss/p1p2p3/') all_data_view = self.rebin_view(self.get_view('data'), rebin) if unblinded: all_data_view = self.rebin_view( self.get_view('data', 'unblinded_view'), rebin) data_view = views.SubdirectoryView(all_data_view, 'ss/p1p2p3/') # View of weighted obj1-fails data obj1_view = views.SubdirectoryView(all_data_view, 'ss/f1p2p3/w1') # View of weighted obj2-fails data obj2_view = views.SubdirectoryView(all_data_view, 'ss/p1f2p3/w2') # View of weighted obj1&2-fails data obj12_view = views.SubdirectoryView(all_data_view, 'ss/f1f2p3/w12') subtract_obj12_view = views.ScaleView(obj12_view, -1) # Corrected fake view fakes_view = views.SumView(obj1_view, obj2_view, subtract_obj12_view) fakes_view = views.TitleView( views.StyleView(fakes_view, **data_styles['Zjets*']), 'Non-prompt') charge_fakes = views.TitleView( views.StyleView( views.SubdirectoryView(all_data_view, 'os/p1p2p3/c1'), **data_styles['TT*']), 'Charge mis-id') output = { 'wz': wz_view, 'zz': zz_view, 'data': data_view, 'obj1': obj1_view, 'obj2': obj2_view, 'fakes': fakes_view, 'charge_fakes': charge_fakes, } # Add signal for mass in [110, 120, 130, 140]: vh_view = views.SubdirectoryView( self.rebin_view(self.get_view('VH_*%i' % mass), rebin), 'ss/p1p2p3/') output['vh%i' % mass] = vh_view ww_view = views.SubdirectoryView( self.rebin_view(self.get_view('WH_%i*' % mass), rebin), 'ss/p1p2p3/') output['vh%i_hww' % mass] = ww_view output['signal%i' % mass] = views.SumView(ww_view, vh_view) return output
def make_view(inview, title, color): return views.TitleView( views.StyleView(inview, linecolor=color, drawstyle='hist', linewidth=3, legendstyle='l'), title)
def make_view(tf, subdir, title, colour): return urviews.NormalizedView( views.TitleView( views.StyleView(views.SubdirectoryView(tf, subdir), linecolor=colour, drawstyle='hist', linewidth=3, legendstyle='l'), title))
def Getter(view, histoname, title=None): def doot(x): #print "doot", histoname return histoname if title is not None: return views.FunctorView(views.TitleView(views.PathModifierView(view, doot), title), set_line_width) else: return views.FunctorView(views.PathModifierView(view, doot), set_line_width)
def get_flip_data(self, rebin=1, xaxis='', data_type='data'): data_view = self.get_view(data_type) data_view = self.rebin_view(data_view, rebin) if rebin != 1 else data_view #Get ss/p1p2 views ss_p1p2_view = views.SubdirectoryView(data_view, 'ss/p1p2') ss_p1p2_view = views.TitleView( views.StyleView(ss_p1p2_view, **data_styles['data*']), 'observed;%s' % xaxis) #def make_fakes_view(sign, weight_type): # # View of weighted obj1-fails data # obj1_view = views.SubdirectoryView(data_view, '%s/f1p2/%s' % (sign, weight_type)) # # View of weighted obj2-fails data # obj2_view = views.SubdirectoryView(data_view, '%s/p1f2/%s' % (sign, weight_type)) # # View of weighted obj1&2-fails data # obj12_view = views.SubdirectoryView(data_view, '%s/f1f2/%s' % (sign, weight_type)) # # Give the individual object views nice colors # subtract_obj12_view = views.ScaleView(obj12_view, -1) # return obj1_view, obj2_view, subtract_obj12_view #Get fakes according to WJets or QCD #ss_f1p2_qcd_view, ss_p1f2_qcd_view, ss_f1f2_qcd_view = self.make_fakes_view(data_view, 'ss','qcd_w') ss_f1p2_wje_view, ss_p1f2_wje_view, ss_f1f2_wje_view = self.make_fakes_view( data_view, 'ss', 'wjet_w') ss_fakes_1 = ss_f1p2_wje_view #MedianView(lowv=ss_f1p2_qcd_view, highv=ss_f1p2_wje_view) ss_fakes_2 = ss_p1f2_wje_view #MedianView(lowv=ss_p1f2_qcd_view, highv=ss_p1f2_wje_view) ss_fakes_12 = ss_f1f2_wje_view #MedianView(lowv=ss_f1f2_qcd_view, highv=ss_f1f2_wje_view) ss_fakes_est = views.SumView(ss_fakes_1, ss_fakes_2, ss_fakes_12) ss_fakes_est = views.TitleView( views.StyleView(ss_fakes_est, **data_styles['Zjets*']), 'Fakes;%s' % xaxis) os_flip_est_up = views.SubdirectoryView(data_view, 'os/p1p2/charge_weightSysUp') os_flip_est = views.SubdirectoryView(data_view, 'os/p1p2/charge_weight') #os_flip_est = MedianView(highv=os_flip_est_up, centv=os_flip_est) os_flip_est_nofake = os_flip_est #views.SumView(os_flip_est, neg_os_fakes) os_flip_est_nofake = views.TitleView( views.StyleView(os_flip_est_nofake, **data_styles['WZ*']), 'charge-fakes;%s' % xaxis) return ss_p1p2_view, ss_fakes_est, os_flip_est_nofake
def make_obj3_fail_cr_views(self, rebin): ''' Make views when obj3 fails, estimating the bkg in obj1 pass using f1p2f3 ''' wz_view = views.SubdirectoryView( self.rebin_view(self.get_view('WZJetsTo3LNu*'), rebin), 'ss/p1p2f3/') zz_view = views.SubdirectoryView( self.rebin_view(self.get_view('ZZJetsTo4L*'), rebin), 'ss/p1p2f3/') all_data_view = self.rebin_view(self.get_view('data'), rebin) data_view = views.SubdirectoryView(all_data_view, 'ss/p1p2f3/') # View of weighted obj1-fails data obj1_view = views.SubdirectoryView(all_data_view, 'ss/f1p2f3/w1') # View of weighted obj2-fails data obj2_view = views.SubdirectoryView(all_data_view, 'ss/p1f2f3/w2') # View of weighted obj1&2-fails data obj12_view = views.SubdirectoryView(all_data_view, 'ss/f1f2f3/w12') subtract_obj12_view = views.ScaleView(obj12_view, -1) # Corrected fake view fakes_view = views.SumView(obj1_view, obj2_view, subtract_obj12_view) fakes_view = views.TitleView( views.StyleView(fakes_view, **data_styles['Zjets*']), 'Non-prompt') charge_fakes = views.TitleView( views.StyleView( views.SubdirectoryView(all_data_view, 'os/p1p2f3/c1'), **data_styles['TT*']), 'Charge mis-id') output = { 'wz': wz_view, 'zz': zz_view, 'data': data_view, 'obj1': obj1_view, 'obj2': obj2_view, 'fakes': fakes_view, 'charge_fakes': charge_fakes, } return output
def plot_final(self, variable, rebin=1, xaxis='', maxy=10, show_error=False, magnifyHiggs=5): ''' Plot the final output - with bkg. estimation ''' sig_view = self.make_signal_views(rebin) vh_nx = views.TitleView( views.StyleView( views.ScaleView(sig_view['signal120'], magnifyHiggs), **data_styles['VH*']), "(%s#times) m_{H} = 120" % magnifyHiggs) stack = views.StackView( sig_view['wz'], sig_view['zz'], sig_view['fakes'], vh_10x, ) histo = stack.Get(variable) histo.Draw() histo.GetHistogram().GetXaxis().SetTitle(xaxis) histo.SetMaximum(maxy) self.keep.append(histo) # Add legend legend = self.add_legend(histo, leftside=False, entries=4) if show_error: bkg_error_view = BackgroundErrorView( sig_view['fakes'], sig_view['wz'], sig_view['zz'], ) bkg_error = bkg_error_view.Get(variable) self.keep.append(bkg_error) bkg_error.Draw('pe2,same') legend.AddEntry(bkg_error) # Use poisson error bars on the data sig_view['data'] = PoissonView(sig_view['data'], x_err=False) data = sig_view['data'].Get(variable) data.Draw('pe,same') self.keep.append(data) #legend.AddEntry(data) legend.Draw()
def make_wz_cr_views(self, rebin): ''' Make WZ control region views with FR background estimation ''' wz_view = views.SubdirectoryView( self.rebin_view(self.get_view('WZJetsTo3LNu*'), rebin), 'ss/p1p2p3_enhance_wz/') zz_view = views.SubdirectoryView( self.rebin_view(self.get_view('ZZJetsTo4L*'), rebin), 'ss/p1p2p3_enhance_wz/') all_data_view = self.rebin_view(self.get_view('data'), rebin) data_view = views.SubdirectoryView(all_data_view, 'ss/p1p2p3_enhance_wz/') # View of weighted obj2-fails data fakes_view = views.SubdirectoryView(all_data_view, 'ss/p1f2p3_enhance_wz/w2') fakes_view = views.StyleView(fakes_view, **data_styles['Zjets*']) # Correct wz_in_fakes_view = views.SubdirectoryView( self.rebin_view(self.get_view('WZJetsTo3LNu*'), rebin), 'ss/p1f2p3_enhance_wz/w2') zz_in_fakes_view = views.SubdirectoryView( self.rebin_view(self.get_view('ZZJetsTo4L*'), rebin), 'ss/p1f2p3_enhance_wz/w2') diboson_view = views.SumView(wz_in_fakes_view, zz_in_fakes_view) inverted_diboson_view = views.ScaleView(diboson_view, -1) fakes_view = views.SumView(fakes_view, inverted_diboson_view) fakes_view = views.TitleView(fakes_view, 'Non-prompt') output = { 'wz': wz_view, 'zz': zz_view, 'data': data_view, 'fakes': fakes_view } # Add signal for mass in [110, 120, 130, 140]: vh_view = views.SubdirectoryView( self.rebin_view(self.get_view('VH_*%i' % mass), rebin), 'ss/p1p2p3/') output['vh%i' % mass] = vh_view return output
def make_wz_cr_views(self, rebin=1, project=None, project_axis=None): ''' Make WZ control region views with FR background estimation ''' def preprocess(view): ret = view if project and project_axis: ret = ProjectionView(ret, project_axis, project) return RebinView( ret, rebin ) wz_view_tautau_all = preprocess( self.get_view('WZJetsTo3LNu*ZToTauTau*') ) wz_view_tautau = views.SubdirectoryView(wz_view_tautau_all, 'ss/tau_os/p1p2p3_enhance_wz/') tomatch = 'WZJetsTo3LNu' if self.sqrts == 7 else 'WZJetsTo3LNu_pythia' wz_view_3l_all = preprocess( self.get_view(tomatch) ) wz_view_3l = views.SubdirectoryView(wz_view_3l_all, 'ss/tau_os/p1p2p3_enhance_wz/') wz_view_all = views.SumView(wz_view_tautau_all, wz_view_3l_all) zz_view_all = preprocess( self.get_view('ZZJetsTo4L*') ) zz_view = views.SubdirectoryView(zz_view_all, 'ss/tau_os/p1p2p3_enhance_wz/') all_data_view = preprocess( self.get_view('data') ) data_view = views.SubdirectoryView( all_data_view, 'ss/tau_os/p1p2p3_enhance_wz/') # View of weighted obj2-fails data fakes_view = views.SubdirectoryView( all_data_view, 'ss/tau_os/p1f2p3_enhance_wz/w2') fakes_view = views.StyleView(fakes_view, **remove_name_entry(data_styles['Zjets*'])) # Correct wz_in_fakes_view = views.SubdirectoryView(wz_view_all, 'ss/tau_os/p1f2p3_enhance_wz/w2') zz_in_fakes_view = views.SubdirectoryView(zz_view_all, 'ss/tau_os/p1f2p3_enhance_wz/w2') diboson_view = views.SumView(wz_in_fakes_view, zz_in_fakes_view) inverted_diboson_view = views.ScaleView(diboson_view, -1) fakes_view = views.SumView(fakes_view, inverted_diboson_view) fakes_view = views.TitleView(fakes_view, 'Reducible bkg.') output = { 'wz_ztt': wz_view_tautau, 'wz_3l' : wz_view_3l, 'zz' : zz_view, 'data' : data_view, 'fakes' : fakes_view } return output
def make_fakes(qcd_fraction): def make_fakes_view(weight_type, scale): scaled_bare_data = views.ScaleView(all_data_view, scale) scaled_wz_data = views.ScaleView(all_wz_view, scale) scaled_data = SubtractionView(scaled_bare_data, scaled_wz_data, restrict_positive=True) # View of weighted obj1-fails data obj1_view = views.SubdirectoryView( scaled_data, 'ss/%s/f1p2f3/%s1' % (tau_charge, weight_type)) # View of weighted obj2-fails data obj2_view = views.SubdirectoryView( scaled_data, 'ss/%s/p1f2f3/%s2' % (tau_charge, weight_type)) # View of weighted obj1&2-fails data obj12_view = views.SubdirectoryView( scaled_data, 'ss/%s/f1f2f3/%s12' % (tau_charge, weight_type)) # Give the individual object views nice colors obj1_view = views.TitleView( views.StyleView(obj1_view, **remove_name_entry(data_styles['TT*'])), 'Reducible bkg. 1') obj2_view = views.TitleView( views.StyleView(obj2_view, **remove_name_entry(data_styles['QCD*'])), 'Reducible bkg. 2') obj12_view = views.TitleView( views.StyleView(obj12_view, **remove_name_entry(data_styles['WW*'])), 'Reducible bkg. 12') subtract_obj12_view = views.ScaleView(obj12_view, -1) return obj1_view, obj2_view, obj12_view, subtract_obj12_view qcd1, qcd2, qcd12, negqcd12 = make_fakes_view('q', qcd_fraction) wjet1, wjet2, wjet12, negwjet12 = make_fakes_view( 'w', 1 - qcd_fraction) obj1_view = views.SumView(qcd1, wjet1) obj2_view = views.SumView(qcd2, wjet2) obj12_view = views.SumView(qcd12, wjet12) subtract_obj12_view = views.SumView(negqcd12, negwjet12) # Corrected fake view fakes_view = views.SumView(obj1_view, obj2_view, subtract_obj12_view) fakes_view = views.TitleView( views.StyleView(fakes_view, **remove_name_entry(data_styles['Zjets*'])), 'Reducible bkg.') return obj1_view, obj2_view, obj12_view, fakes_view
def data_views(files, lumifiles, styles, forceLumi=-1): ''' Builds views of files. [files] gives an iterator of .root files with histograms to build. [lumifiles] gives the correspond list of .lumisum files which contain the effective integrated luminosity of the samples. The lumi to normalize to is taken as the sum of the data file int. lumis. ''' files = list(files) log.info("Creating views from %i files", len(files)) # Map sample_name => root file histo_files = dict((extract_sample(x), io.open(x)) for x in files) # Map sample_name => lumi file lumi_files = dict((extract_sample(x), read_lumi(x)) for x in lumifiles) # Identify data files datafiles = set([name for name in histo_files.keys() if 'data' in name]) log.info("Found the following data samples:") log.info(" ".join(datafiles)) datalumi = 0 for x in datafiles: if x not in lumi_files: raise KeyError( "Can't find a lumi file for %s - I have these ones: " % x + repr(lumi_files.keys())) datalumi += lumi_files[x] log.warning("-> total int. lumi = %0.0fpb-1", datalumi) if forceLumi > 0: datalumi = forceLumi log.warning("-> forcing lumi to = %0.0fpb-1", datalumi) # Figure out the dataset for each file, and the int lumi. # Key = dataset name # Value = {intlumi, rootpy file, weight, weighted view} output = {} has_data = False for sample in histo_files.keys(): raw_file = histo_files[sample] intlumi = lumi_files[sample] weight = 1 if intlumi: weight = datalumi / intlumi if 'data' in sample: has_data = True weight = 1 log.warning( "Building sample: %s => int lumi: %0.f pb-1. Weight => %0.2E", sample, intlumi, weight) view = views.ScaleView(raw_file, weight) unweighted_view = raw_file # Find the longest (i.e. most specific) matching style pattern style = get_best_style(sample, styles) if style: log.info("Found style for %s - applying Style View", sample) # Set style and title # title = the name of the sample, rootpy Legend uses this. nicename = copy.copy(style['name']) log.debug("sample name %s", nicename) style_dict_no_name = dict( [i for i in style.iteritems() if i[0] != 'name']) view = views.TitleView(views.StyleView(view, **style_dict_no_name), nicename) unweighted_view = views.TitleView( views.StyleView(unweighted_view, **style_dict_no_name), nicename) else: log.warning("No matching style found for %s", sample) output[sample] = { 'intlumi': intlumi, 'file': raw_file, 'weight': weight, 'view': view, 'unweighted_view': unweighted_view } if not has_data: return output # Merge the data into just 'data' log.info("Merging data together") output['data'] = { 'intlumi': datalumi, 'weight': 1, 'view': views.SumView(*[output[x]['view'] for x in datafiles]), 'unweighted_view': views.SumView(*[output[x]['unweighted_view'] for x in datafiles]), } return output
'WplusJets_madgraph', 'TTplusJets_madgraph', 'Zjets_M50', ]] ) #mc_inverted = views.ScaleView(mc_view, -1) mc_inverted = views.ScaleView(mc_view, -1) sqrts = 7 if '7TeV' in jobid else 8 qcd_view = views.StyleView( views.TitleView( views.ScaleView( views.SumView(views.PathModifierView(plotter.data, get_ss), mc_inverted), 1.4 if sqrts == 8 else 1.28 # OS/SS from Valentina ), 'QCD'), **data_styles['WZ*']) def get_fakes(x): return x.replace('em/', 'em/f2/w2/') fakes_view = views.StyleView( views.TitleView( views.PathModifierView(plotter.data, get_fakes), 'Fakes'), **data_styles['WZ*'] )
def plot_zee_control(self, variable, xaxis='', rebin=1, legend_on_the_left=False, x_range=None, show_ratio=False, logscale=False): data_view = self.get_view('data') data_view = self.rebin_view(data_view, rebin) if rebin != 1 else data_view mc_views = [ self.get_view(i) for i in ['ZZ*', 'WZ*', 'WW*', 'TT*', 'Zjets_M50'] ] if rebin != 1: mc_views = [self.rebin_view(i, rebin) for i in mc_views] zee_data = views.SubdirectoryView(data_view, 'os/p1p2/') zee_mcs = [views.SubdirectoryView(i, 'os/p1p2/') for i in mc_views] #os_f1p2_qcd_view, os_p1f2_qcd_view, os_f1f2_qcd_view = self.make_fakes_view(data_view, 'os','qcd_w') os_f1p2_wje_view, os_p1f2_wje_view, os_f1f2_wje_view = self.make_fakes_view( data_view, 'os', 'wjet_w') os_fakes_1 = os_f1p2_wje_view #MedianView(lowv=os_f1p2_qcd_view, highv=os_f1p2_wje_view) os_fakes_2 = os_p1f2_wje_view #MedianView(lowv=os_p1f2_qcd_view, highv=os_p1f2_wje_view) os_fakes_12 = os_f1f2_wje_view #MedianView(lowv=os_f1f2_qcd_view, highv=os_f1f2_wje_view) os_fakes_est = views.SumView(os_fakes_1, os_fakes_2, os_fakes_12) os_fakes_est = views.TitleView( views.StyleView(os_fakes_est, **data_styles['WplusJets*']), 'Fakes;%s' % xaxis) zee_mcs = zee_mcs[:-1] + [os_fakes_est] + zee_mcs[-1:] events_estimate = views.StackView(*zee_mcs) estimate_hist = events_estimate.Get(variable) obs_hist = zee_data.Get(variable) hmax = max([estimate_hist.GetMaximum(), max(list(obs_hist))]) if logscale: obs_hist.GetYaxis().SetRangeUser(10**-2, hmax * 10**4) self.pad.SetLogy(True) else: obs_hist.GetYaxis().SetRangeUser(0., hmax * 1.3) if x_range: obs_hist.GetXaxis().SetRangeUser(x_range[0], x_range[1]) obs_hist.Draw() estimate_hist.Draw('same') obs_hist.Draw('same') self.canvas.Update() self.keep.extend([estimate_hist, obs_hist]) legend = self.add_legend([obs_hist], leftside=legend_on_the_left, entries=len(zee_mcs) + 1) legend.AddEntry(estimate_hist, 'f') #legend.AddEntry(estimate_error,'f') legend.Draw() if show_ratio: self.add_ratio_plot(obs_hist, estimate_hist, x_range, ratio_range=0.2) self.add_cms_blurb(self.sqrts)
'pdf': False }}) ttjets = urviews.NormalizedView( root_open('results/%s/permProbComputer/ttJets.root' % jobid)) subs_and_col = [ ('semilep_visible_right', 'violet'), ('other_tt_decay', 'blue'), ('semilep_right_thad', 'cyan'), ('semilep_right_tlep', 'red'), ('semilep_wrong', '#00960a'), ] samples = [ views.TitleView( views.StyleView(views.SubdirectoryView(ttjets, i), linecolor=j, drawstyle='hist', legendstyle='l'), i) for i, j in subs_and_col ] plots = ['nusolver_chi2', 'thfr', 'tlfr', 'wfr_jcosth_delta'] #plotter.set_subdir('shapes') #for var in plots: # shapes = [i.Get('nosys/%s' % var) for i in samples] # legend = LegendDefinition(position='NE') # plotter.overlay(shapes, legend_def=legend, ytitle='a.u.', y_range='shape', ignore_style=True) # plotter.save(var) systematics = [ ('nosys', 'violet'), ('jes_down', 'blue'),
postfix = '_TEST_' ROOT.gStyle.SetPaintTextFormat('.2g') jobid = os.environ['jobid'] channels = ['eet', 'emt', 'mmt'] public = os.environ['pub'] chan_hists = {} for ch, color in zip(channels, ['darkgreen', 'blue', 'red']): view = views.TitleView( views.StyleView( views.SumView( # io.open('results/%s/WHAnalyze%s/VH_120_HWW.root' % (jobid, ch.upper()) ), io.open('results/%s/WHAnalyze%s/VH_H2Tau_M-120.root' % (jobid, ch.upper()))), drawstyle='hist TEXT00', linecolor=color, linewidth=2, fillstyle='hollow', legendstyle='l', ), ch) chan_hists[ch] = view.Get('ss/CUT_FLOW') chan_hists[ch].SetLabelSize(0.035) canvas = plotting.Canvas(name='adsf', title='asdf') canvas.SetGridx(True) canvas.SetGridy(True) canvas.SetLogy(True) legend = plotting.Legend(len(channels), rightmargin=0.07,
def make_obj3_fail_cr_views(self, qcd_correction=False, qcd_weight_fraction=0, tau_charge='tau_os'): ''' Make views when obj3 fails, estimating the bkg in obj1 pass using f1p2f3 ''' other_tau_sign = 'tau_os' if tau_charge == 'tau_ss' else 'tau_ss' all_wz_ztt_view = self.get_view('WZJetsTo3LNu*ZToTauTau*') wz_view = views.SubdirectoryView( all_wz_ztt_view, 'ss/%s/p1p2f3/' % tau_charge ) tomatch = 'WZJetsTo3LNu' if self.sqrts == 7 else 'WZJetsTo3LNu_pythia' all_wz_3l_view = self.get_view(tomatch) wz_view_3l = views.SubdirectoryView( all_wz_3l_view, 'ss/%s/p1p2f3/' % tau_charge ) all_wz_view = views.SumView(all_wz_ztt_view, all_wz_3l_view) zz_view = views.SubdirectoryView( self.get_view('ZZJetsTo4L*'), 'ss/%s/p1p2f3/' % tau_charge ) all_data_view = self.get_view('data') data_view = views.SubdirectoryView(all_data_view, 'ss/%s/p1p2f3/' % tau_charge) def make_fakes(qcd_fraction): def make_fakes_view(weight_type, scale): scaled_bare_data = views.ScaleView(all_data_view, scale) scaled_wz_data = views.ScaleView(all_wz_view, scale) scaled_data = SubtractionView(scaled_bare_data, scaled_wz_data, restrict_positive=True) # View of weighted obj1-fails data obj1_view = views.SubdirectoryView( scaled_data, 'ss/%s/f1p2f3/%s1' % (tau_charge, weight_type)) # View of weighted obj2-fails data obj2_view = views.SubdirectoryView( scaled_data, 'ss/%s/p1f2f3/%s2' % (tau_charge, weight_type)) # View of weighted obj1&2-fails data obj12_view = views.SubdirectoryView( scaled_data, 'ss/%s/f1f2f3/%s12' % (tau_charge, weight_type)) # Give the individual object views nice colors obj1_view = views.TitleView( views.StyleView(obj1_view, **remove_name_entry(data_styles['TT*'])), 'Reducible bkg. 1') obj2_view = views.TitleView( views.StyleView(obj2_view, **remove_name_entry(data_styles['QCD*'])), 'Reducible bkg. 2') obj12_view = views.TitleView( views.StyleView(obj12_view, **remove_name_entry(data_styles['WW*'])), 'Reducible bkg. 12') subtract_obj12_view = views.ScaleView(obj12_view, -1) return obj1_view, obj2_view, obj12_view, subtract_obj12_view qcd1, qcd2, qcd12, negqcd12 = make_fakes_view('q', qcd_fraction) wjet1, wjet2, wjet12, negwjet12 = make_fakes_view( 'w', 1 - qcd_fraction) obj1_view = views.SumView(qcd1, wjet1) obj2_view = views.SumView(qcd2, wjet2) obj12_view = views.SumView(qcd12, wjet12) subtract_obj12_view = views.SumView(negqcd12, negwjet12) # Corrected fake view fakes_view = views.SumView(obj1_view, obj2_view, subtract_obj12_view) fakes_view = views.TitleView( views.StyleView(fakes_view, **remove_name_entry(data_styles['Zjets*'])), 'Reducible bkg.') return obj1_view, obj2_view, obj12_view, fakes_view obj1_view, obj2_view, obj12_view, fakes_view = make_fakes(qcd_weight_fraction) fakes_view_05 = make_fakes(0.5)[-1] fakes_view_0 = make_fakes(0)[-1] fakes_view_1 = make_fakes(1)[-1] style_dict_no_name = remove_name_entry(data_styles['TT*']) charge_fakes = views.TitleView( #FIXME views.StyleView( views.SumView( views.PathModifierView( views.SubdirectoryView(all_data_view, 'os/%s/p1p2f3/c1' % other_tau_sign), create_mapper(self.obj1_charge_mapper) ), views.PathModifierView( views.SubdirectoryView(all_data_view, 'os/%s/p1p2f3/c2' % tau_charge), create_mapper(self.obj2_charge_mapper) ), ), **style_dict_no_name), 'Charge mis-id') charge_fakes_sysup = views.TitleView( views.StyleView( views.SumView( views.PathModifierView( views.SubdirectoryView(all_data_view, 'os/%s/p1p2f3/c1_sysup' % other_tau_sign), create_mapper(self.obj1_charge_mapper) ), views.PathModifierView( views.SubdirectoryView(all_data_view, 'os/%s/p1p2f3/c2_sysup' % tau_charge), create_mapper(self.obj2_charge_mapper) ), ), **style_dict_no_name), 'Charge mis-id') #charge_fakes = MedianView(highv=charge_fakes_sysup, centv=charge_fakes) output = { 'wz': wz_view, 'wz_3l': wz_view_3l, 'zz': zz_view, 'data': data_view, 'obj1': obj1_view, 'obj2': obj2_view, 'obj12': obj12_view, 'fakes': fakes_view, 'weighted_fakes' : { 0. : fakes_view_0, 0.5 : fakes_view_05, 1. : fakes_view_1, }, 'charge_fakes': { 'central' : charge_fakes, 'sys_up' : charge_fakes_sysup, } } #Add signal @ 120, just mo make bkg fitting easier mass = 120 vh_view = views.SubdirectoryView( self.get_view('VH_*%i' % mass), 'ss/tau_os/p1p2f3/' ) output['vh%i' % mass] = vh_view try: ww_view = views.SubdirectoryView( self.get_view('VH_%i_HWW*' % mass), 'ss/tau_os/p1p2f3/' ) except KeyError: #logging.warning('No sample found matching VH_%i_HWW*' % mass) ww_view = None output['vh%i_hww' % mass] = ww_view output['signal%i' % mass] = views.SumView(ww_view, vh_view) if ww_view else vh_view return output
def data_views(files, lumifiles): ''' Builds views of files. [files] gives an iterator of .root files with histograms to build. [lumifiles] gives the correspond list of .lumisum files which contain the effective integrated luminosity of the samples. The lumi to normalize to is taken as the sum of the data file int. lumis. ''' files = list(files) log.info("Creating views from %i files", len(files)) # Map sample_name => root file histo_files = dict((extract_sample(x), io.open(x)) for x in files) # Map sample_name => lumi file lumi_files = dict((extract_sample(x), read_lumi(x)) for x in lumifiles) # Identify data files datafiles = set([name for name in histo_files.keys() if 'data' in name]) log.info("Found the following data samples:") log.info(" ".join(datafiles)) datalumi = 0 for x in datafiles: if x not in lumi_files: raise KeyError( "Can't find a lumi file for %s - I have these ones: " % x + repr(lumi_files.keys())) datalumi += lumi_files[x] log.info("-> total int. lumi = %0.0fpb-1", datalumi) # Figure out the dataset for each file, and the int lumi. # Key = dataset name # Value = {intlumi, rootpy file, weight, weighted view} output = {} for sample in histo_files.keys(): raw_file = histo_files[sample] intlumi = lumi_files[sample] log.info("Building sample: %s => int lumi: %0.f pb-1", sample, intlumi) weight = 1 if intlumi: weight = datalumi/intlumi if 'data' in sample: weight = 1 log.debug("Weight: %0.2f", weight) view = views.ScaleView(raw_file, weight) unweighted_view = raw_file # Find the longest (i.e. most specific) matching style pattern best_pattern = '' for pattern, style_dict in data_styles.iteritems(): log.debug("Checking pattern: %s against %s", pattern, sample) if fnmatch.fnmatch(sample, pattern): log.debug("-> it matches!") if len(pattern) > len(best_pattern): best_pattern = pattern log.info("Found new best style for %s: %s", sample, pattern) if best_pattern: style_dict = data_styles[best_pattern] log.info("Found style for %s - applying Style View", sample) # Set style and title # title = the name of the sample, rootpy Legend uses this. nicename = copy.copy(style_dict['name']) view = views.TitleView( views.StyleView(view, **style_dict), nicename ) unweighted_view = views.TitleView( views.StyleView(unweighted_view, **style_dict), nicename ) output[sample] = { 'intlumi': intlumi, 'file' : raw_file, 'weight' : weight, 'view' : view, 'unweighted_view' : unweighted_view } # Merge the data into just 'data' log.info("Merging data together") output['data'] = { 'intlumi' : datalumi, 'weight' : 1, 'view' : views.SumView(*[output[x]['view'] for x in datafiles]), 'unweighted_view' : views.SumView(*[output[x]['unweighted_view'] for x in datafiles]), } return output
from pdb import set_trace from argparse import ArgumentParser parser = ArgumentParser() parser.add_argument('input', help='input root file') parser.add_argument('out', help='output dir') args = parser.parse_args() tfile = root_open(args.input) plotter = BasePlotter( args.out, defaults={'save': { 'pdf': False }}, ) b_plots = views.StyleView(views.TitleView(views.SubdirectoryView(tfile, 'B'), 'B'), linewidth=2, linecolor='#2aa198', legendstyle='l', drawstyle='hist') c_plots = views.StyleView( views.TitleView(views.SubdirectoryView(tfile, 'C'), 'C'), linewidth=2, linecolor='#0055ff', legendstyle='l', drawstyle='hist', ) l_plots = views.StyleView( views.TitleView(views.SubdirectoryView(tfile, 'DUSG'), 'DUSG'),
def plot_final(self, variable, rebin=1, xaxis='', maxy=24, show_error=False, qcd_correction=False, stack_higgs=True, qcd_weight_fraction=0., x_range=None, show_charge_fakes=False, leftside_legend=False, higgs_xsec_multiplier=1, project=None, project_axis=None, differential=False, yaxis='Events', tau_charge='tau_os', **kwargs): ''' Plot the final output - with bkg. estimation ''' show_charge_fakes = show_charge_fakes if 'show_charge_fakes' not in self.defaults else self.defaults['show_charge_fakes'] sig_view = self.make_signal_views(unblinded=(not self.blind), qcd_weight_fraction=qcd_weight_fraction, rebin=rebin, project=project, project_axis=project_axis, tau_charge=tau_charge) if differential: sig_view = self.apply_to_dict(sig_view, DifferentialView) vh_10x = views.TitleView( views.StyleView( views.ScaleView(sig_view['vh125'], higgs_xsec_multiplier), **remove_name_entry(data_styles['VH*']) ), "(%i#times) m_{H} = 125" % higgs_xsec_multiplier ) charge_fakes_view = MedianView(highv=sig_view['charge_fakes']['sys_up'], centv=sig_view['charge_fakes']['central']) # Fudge factor to go from 120->125 - change in xsec*BR #vh_10x = views.ScaleView(vh_10x), .783) tostack = [sig_view['wz_3l'], sig_view['zz'], sig_view['wz'], sig_view['fakes'], vh_10x] if stack_higgs else \ [sig_view['wz_3l'], sig_view['zz'], sig_view['wz'], sig_view['fakes']] if show_charge_fakes: tostack = tostack[:2]+[charge_fakes_view]+tostack[2:] vh_hww = views.ScaleView(sig_view['vh120_hww'], .783) if 'vh120_hww' in sig_view else None if vh_hww: tostack = tostack[:-1] + [vh_hww] + tostack[-1:] stack = views.StackView( *tostack ) histo = stack.Get(variable) histo.Draw() histo.GetHistogram().GetXaxis().SetTitle(xaxis) histo.GetHistogram().GetYaxis().SetTitle(yaxis) if x_range: histo.GetHistogram().GetXaxis().SetRangeUser(x_range[0], x_range[1]) self.keep.append(histo) # Add legend entries = len(tostack)+1 if show_error: entries += 1 legend = self.add_legend(histo, leftside=leftside_legend, entries=entries) if show_error: #correct_qcd_view = None #if qcd_weight_fraction == 0: # fakes05 = sig_view['weighted_fakes'][1.] # correct_qcd_view = MedianView(lowv=fakes05, centv=sig_view['fakes']) # #elif qcd_weight_fraction == 0.5: # fakes1 = sig_view['weighted_fakes'][1.] # correct_qcd_view = MedianView(highv=fakes1, centv=sig_view['fakes']) # #elif qcd_weight_fraction == 1: # fakes05 = sig_view['weighted_fakes'][0.5] # correct_qcd_view = MedianView(lowv=fakes05, centv=sig_view['fakes']) bkg_error_view = BackgroundErrorView( sig_view['fakes'], #correct_qcd_view, #sig_view['fakes'], views.SumView( sig_view['wz'], sig_view['wz_3l']), sig_view['zz'], charge_fakes_view, fake_error=0.3, **kwargs ) bkg_error = bkg_error_view.Get(variable) self.keep.append(bkg_error) bkg_error.Draw('pe2,same') legend.AddEntry(bkg_error) # Use poisson error bars on the data sig_view['data'] = PoissonView(sig_view['data'], x_err=False, is_scaled=differential) #PoissonView(, x_err=False) data = sig_view['data'].Get(variable) ymax = histo.GetMaximum() if not self.blind or tau_charge != 'tau_os': #print "drawing", data.Integral() data.Draw('pe,same') legend.AddEntry(data) ymax = max(ymax, data.GetMaximum()) self.keep.append(data) if isinstance(maxy, (int, long, float)): #print "setting maxy to %s" % maxy histo.SetMaximum(maxy) self.canvas.Update() else: histo.SetMaximum(ymax*1.2) if not stack_higgs: higgs_plot = vh_10x.Get(variable) higgs_plot.Draw('same') self.keep.append(higgs_plot) legend.Draw()
print foldernames mymapper = { "os/": "ss/", "os/0/": "ss/0/", "os/1": "ss/1", "os/2": "ss/2", "os/3": "ss/3" } QCD = views.TitleView( views.StyleView( SubtractionView(views.PathModifierView(plotter.data, get_ss), views.PathModifierView(TT, get_ss), views.PathModifierView(singleT, get_ss), views.PathModifierView(SMH, get_ss), views.PathModifierView(DYTT, get_ss), views.PathModifierView(DYLL, get_ss), views.PathModifierView(Wplus, get_ss), views.PathModifierView(EWKDiboson, get_ss)), **data_styles['QCD*']), 'QCD') plotter.views['QCD'] = {'view': QCD} plotter.mc_samples.extend(['QCD']) for foldername in foldernames: if foldername.startswith("ss") and bool( 'QCD' in plotter.mc_samples) == True: plotter.mc_samples.remove('QCD') if foldername.startswith("os") and bool( 'QCD' in plotter.mc_samples) == False:
def make_closure_plots(self, var, testDir, refDir, rebin=1, xaxis=''): '''helper function to make comparison between data and data (closure test for fakerates etc.)''' self.canvas.cd() data_view = self.rebin_view(self.data, rebin) test_view = views.StyleView(views.TitleView( views.SubdirectoryView(data_view, testDir), 'Weighted data'), fillcolor=ROOT.EColor.kRed, drawstyle='hist') #.Get(var) refData = views.SubdirectoryView(data_view, refDir).Get(var) testSampleName = '_'.join(testDir.split('/')[1:]).replace( 'IsoFailed', 'fail').replace('_weight', 'w') refSampleName = refDir.split('/')[1].replace('IsoFailed', 'fail').replace( '_weight', 'w') #testData.SetTitle(testSampleName) refData.SetTitle(refSampleName) diboson_views = [ InflateErrorView( views.SubdirectoryView( self.rebin_view(self.get_view(pattern), rebin), refDir), 0.16) for pattern in ['WZ*'] ] #, 'ZZ*', 'WW*'] ] to_stack_views = diboson_views + [test_view] #+ stack_hist = views.StackView(*to_stack_views).Get(var) refData.drawstyle = "ep" stack_hist.drawstyle = "HIST same" # same" #"HISTe same " hmax = max([ max([(b.content + b.error) for b in zipBins(refData)]), stack_hist.GetMaximum() ]) refData.GetYaxis().SetRangeUser(0, hmax * 1.3) refData.GetXaxis().SetTitle(xaxis) tgTest = HistStackToTGRaphErrors(stack_hist) tgTest.SetFillStyle(3013) tgTest.GetXaxis().SetTitle(xaxis) tgTest.GetYaxis().SetRangeUser(0, hmax * 1.3) self.keep.append(tgTest) refData.SetMarkerStyle(20) refData.SetMarkerSize(1) self.keep.append(refData) self.keep.append(stack_hist) refData.Draw() stack_hist.Draw('same') stack_hist.GetXaxis().SetTitle(xaxis) stack_hist.GetYaxis().SetRangeUser(0, hmax * 1.3) refData.Draw('same') tgTest.Draw('2 same') #stack_hist.Draw() #self.canvas.SetLogy() legend = self.add_legend([refData], leftside=False, entries=len(to_stack_views) + 1) legend.AddEntry(stack_hist, 'f') legend.Draw() self.add_cms_blurb(self.sqrts)
'SMH', 'singleT',#'Wplus', 'TT'#, #'DYLL', #'DYTT' ]) def get_fakeTaus(x): y=x if x.startswith('os') or x.startswith('ss'): y = x.replace('.*s/', 'tLoose/*s/') return y print mc_samples #myFake = views.TitleView(views.StyleView(views.SumView( *[ plotter.get_view(regex) for regex in filter(lambda x : x.startswith('data'), mc_samples)]),**remove_name_entry(data_styles['Fakes*'])), 'Fakes') Fakes = views.SubdirectoryView(views.TitleView(views.StyleView(views.SumView( *[ plotter.get_view(regex) for regex in filter(lambda x : 'Fake*' in x, mc_samples)]), **remove_name_entry(data_styles['Fakes*'])),'Fakes'), 'tLoose/') plotter.views['Fakes']= {'view': Fakes} new_mc_samples.extend(['Fakes']) print new_mc_samples histoname = [('tPt', 'p_T(#tau) (GeV)', 5), ('tEta', '#eta(#tau)', 2), ('tPhi', '#phi(#tau)', 5), ('ePt', 'p_T(e) (GeV)', 5), ('eEta', '#eta(e)', 2), ('ePhi', '#phi(e)', 5), ('et_DeltaPhi', 'e#tau #Delta#phi', 1.), ('et_DeltaR', 'e#tau #Delta{R}', 1.), ('h_collmass_pfmet', 'M_{coll}(e#tau) (GeV)', 1.), ('h_vismass', 'M_{vis} (GeV)', 1.), ('jetN_30', 'number of jets (p_T > 30 GeV)', 1.) ] plotter.mc_samples = new_mc_samples
def make_signal_views(self, unblinded=False, qcd_weight_fraction=0, #MARK rebin=1, project=None, project_axis=None, tau_charge='tau_os' ): ''' Make signal views with FR background estimation ''' other_tau_sign = 'tau_os' if tau_charge == 'tau_ss' else 'tau_ss' def preprocess(view): ret = view if project and project_axis: ret = ProjectionView(ret, project_axis, project) return RebinView( ret, rebin ) all_wz_view_tautau = preprocess( self.get_view('WZJetsTo3LNu*ZToTauTau*') ) wz_view_tautau = views.SubdirectoryView( all_wz_view_tautau, 'ss/%s/p1p2p3/' % tau_charge ) tomatch = 'WZJetsTo3LNu' if self.sqrts == 7 else 'WZJetsTo3LNu_pythia' all_wz_view_3l = preprocess( self.get_view(tomatch) ) wz_view_3l = views.SubdirectoryView( all_wz_view_3l, 'ss/%s/p1p2p3/' % tau_charge ) all_wz_view = views.SumView(all_wz_view_tautau, all_wz_view_3l) zz_view = preprocess( views.SubdirectoryView( self.get_view('ZZJetsTo4L*'), 'ss/%s/p1p2p3/' % tau_charge ) ) all_data_view = self.get_view('data') #if unblinded: # all_data_view = self.get_view('data', 'unblinded_view') all_data_view = preprocess(all_data_view) data_view = views.SubdirectoryView(all_data_view, 'ss/%s/p1p2p3/' % tau_charge) def make_fakes(qcd_fraction): def make_fakes_view(weight_type, scale): scaled_bare_data = views.ScaleView(all_data_view, scale) scaled_wz_data = views.ScaleView(all_wz_view, scale) scaled_data = SubtractionView(scaled_bare_data, scaled_wz_data, restrict_positive=True) # View of weighted obj1-fails data obj1_view = views.SubdirectoryView( scaled_data, 'ss/%s/f1p2p3/%s1' % (tau_charge, weight_type)) # View of weighted obj2-fails data obj2_view = views.SubdirectoryView( scaled_data, 'ss/%s/p1f2p3/%s2' % (tau_charge, weight_type)) # View of weighted obj1&2-fails data obj12_view = views.SubdirectoryView( scaled_data, 'ss/%s/f1f2p3/%s12' % (tau_charge, weight_type)) # Give the individual object views nice colors obj1_view = views.TitleView( views.StyleView(obj1_view, **remove_name_entry(data_styles['TT*'])), 'Reducible bkg. 1') obj2_view = views.TitleView( views.StyleView(obj2_view, **remove_name_entry(data_styles['QCD*'])), 'Reducible bkg. 2') obj12_view = views.TitleView( views.StyleView(obj12_view, **remove_name_entry(data_styles['WW*'])), 'Reducible bkg. 12') return obj1_view, obj2_view, obj12_view qcd1, qcd2, qcd12 = make_fakes_view('q', qcd_fraction) wjet1, wjet2, wjet12 = make_fakes_view( 'w', 1 - qcd_fraction) obj1_view = views.SumView(qcd1, wjet1) obj2_view = views.SumView(qcd2, wjet2) obj12_view = views.SumView(qcd12, wjet12) # Corrected fake view fakes_view = views.MultiFunctorView(fake_rate_estimate, obj1_view, obj2_view, obj12_view) fakes_view = views.TitleView( views.StyleView(fakes_view, **remove_name_entry(data_styles['Zjets*'])), 'Reducible bkg.') return obj1_view, obj2_view, obj12_view, fakes_view obj1_view, obj2_view, obj12_view, fakes_view = make_fakes(qcd_weight_fraction) fakes_view_05 = make_fakes(0.5)[-1] fakes_view_0 = make_fakes(0)[-1] fakes_view_1 = make_fakes(1)[-1] charge_fakes = views.TitleView( views.StyleView( views.SumView( views.PathModifierView( views.SubdirectoryView(all_data_view, 'os/%s/p1p2p3/c1' % other_tau_sign), #FIXME: needs to be fixed for charge 3 region create_mapper(self.obj1_charge_mapper) ), views.PathModifierView( views.SubdirectoryView(all_data_view, 'os/%s/p1p2p3/c2' % tau_charge), create_mapper(self.obj2_charge_mapper) ), ), **remove_name_entry(data_styles['TT*'])), 'Charge mis-id') charge_fakes_sysup = views.TitleView( views.StyleView( views.SumView( views.PathModifierView( views.SubdirectoryView(all_data_view, 'os/%s/p1p2p3/c1_sysup' % other_tau_sign), create_mapper(self.obj1_charge_mapper) ), views.PathModifierView( views.SubdirectoryView(all_data_view, 'os/%s/p1p2p3/c2_sysup' % tau_charge), create_mapper(self.obj2_charge_mapper) ), ), **remove_name_entry(data_styles['TT*'])), 'Charge mis-id') #charge_fakes = MedianView(highv=charge_fakes_sysup, centv=charge_fakes) output = { 'wz': wz_view_tautau, 'wz_3l': wz_view_3l, 'zz': zz_view, 'data': data_view, 'obj1': obj1_view, 'obj2': obj2_view, 'obj12': obj12_view, 'fakes': fakes_view, 'weighted_fakes' : { 0. : fakes_view_0, 0.5 : fakes_view_05, 1. : fakes_view_1, }, 'charge_fakes': { 'central' : charge_fakes, 'sys_up' : charge_fakes_sysup, } } # Add signal data_total_lumi = self.views['data']['intlumi'] for mass in range(90, 165, 5): try: vh_base_name = 'VH_%s' % mass if self.sqrts == 7 else 'VH_H2Tau_M-%s' % mass vh_base_name = 'VHtautau_lepdecay_%s' % mass \ if 'VHtautau_lepdecay_%s' % mass in self.views else \ vh_base_name #print 'using %s' % vh_base_name vh_base_view = self.views[vh_base_name]['view'] vh_view = views.SubdirectoryView( vh_base_view, #self.get_view('VH_*%i' % mass), 'ss/%s/p1p2p3/' % tau_charge ) output['vh%i' % mass] = preprocess(vh_view) except KeyError: #logging.warning('No sample found matching VH_*%i' % mass) continue if mass % 10 == 0 and mass < 150: # Only have 10 GeV steps for WW try: ww_view = views.SubdirectoryView( self.get_view('VH_%i_HWW*' % mass), 'ss/%s/p1p2p3/' % tau_charge ) output['vh%i_hww' % mass] = preprocess(ww_view) except KeyError: #logging.warning('No sample found matching VH_%i_HWW*' % mass) continue #output['signal%i' % mass] = views.SumView(ww_view, vh_view) if ww_view else vh_view return output