def plot_npcorrections(args=None,cut='_jet1pt10'):
cutstring = generate_basiccutstring(args,cut)
plots = []
d = ({
'files': [ #'/ceph/tberger/excalibur_results/2019-09-03/mc16_mm_BCDEFGH_DYtoLLmadgraph.root',
'/ceph/tberger/excalibur_results/2019-09-03/mc16_mm_BCDEFGH_DYtoLLamcatnlo.root',
'/portal/ekpbms1/home/mschnepf/QCD/NP_corrections/runtime/CMSSW_10_6_2/src/nonNP_1mio.root',
'/portal/ekpbms1/home/mschnepf/QCD/NP_corrections/runtime/CMSSW_10_6_2/src/official_1mio.root',
],
'folders': ['genzjetcuts_L1L2L3/ntuple'],
'nicks': ['amc','nonNP','official'],
'weights': ['abs(genmupluseta)<2.4&&abs(genmuminuseta)<2.4&&genmupluspt>25&&genmuminuspt>20&&genjet1pt>20&&abs(genjet1y)<2.4&&abs(genzmass-91.2)<20&&genystar<0.5&&genyboost<0.5']
+2*['abs(genmupluseta)<2.4&&abs(genmuminuseta)<2.4&&genmupluspt>25&&genmuminuspt>25&&genjetpt >20&&abs(genjety )<2.4&&abs(genzmass-91.2)<20&&genystar<0.5&&genyboost<0.5'],
'no_weight': True,
'x_expressions': ['genzpt'],
'x_bins': 'zpt',
#'x_expressions': ['genjet1pt']+2*['genjetpt'],
#'x_bins': 'jet1pt',
#'x_label': 'genjet1pt',
'x_log': True,
'www': 'NPC',
'analysis_modules': ['NormalizeToFirstHisto','Ratio'],
'ratio_numerator_nicks': ['nonNP','official'],
'ratio_denominator_nicks': ['amc'],
'y_log': True,
#'y_subplot_lims': [0.9,1.1],
'lumis': [35.9],
})
plots.append(d)
return [PlottingJob(plots=plots, args=args)]
def plot_yb_ystar_correlation(args=None, cut='_jet1pt20', mc='mad', postfix=''):
plots=[]
gen = 'gen'
cutstring = generate_basiccutstring(args,gen+cut)
d = ({
'corrections': [''],
'files': [DATASETS[mc]],
'y_expressions': [gen+'ystar'],
'y_bins': 'ystar',
'y_label': gen+'ystar',
'x_expressions': [gen+'yboost'],
'x_bins': 'yboost',
'x_label': gen+'yboost',
'z_log': True,
'z_lims': [1e2,4e4],
'filename': gen+'yboost_'+gen+'ystar',
'www': 'responses_'+mc+cut+postfix,
'nicks': ['correlation'],
'weights': [cutstring+'&&('+gen+'yboost+'+gen+'ystar<2.5)'],
'zjetfolders': [gen+'zjetcuts_L1L2L3'],
'figsize': [8,6.5],
'no_energy_label': True,
'texts': [r"$\\bf{CMS} \\hspace{0.5} \\it{Simulation} \\hspace{0.2} \\it{Preliminary}$" if CMSLABEL else ""],
#'plot_modules': ['ExportRoot'],
'texts_size': [20],
'texts_y': [1.06],
'texts_x': [0.03],
})
plots.append(d)
return [PlottingJob(plots=plots, args=args)]
def plot_responses_inclusive(args=None, cut='_jet1pt20', mc='mad', postfix=''):
plots=[]
cutstring = generate_basiccutstring(args,cut)
gencutstring = generate_basiccutstring(args,'gen'+cut)
for obs in ['zpt','zy','phistareta','jet1y','yboost','ystar','mupluspt','muminuspt','mupluseta','muminuseta','muplusphi','muminusphi']:
d = ({
'corrections': [''],
'files': [DATASETS[mc].replace('.root',postfix+'.root')],
'x_expressions': ['gen'+obs],
'x_bins': obs,
'x_log': obs in ['zpt','phistareta'],
'x_label': 'gen'+obs,
'y_expressions': [obs],
'y_bins': obs,
'y_log': obs in ['zpt','phistareta'],
'y_label': 'reco'+obs,
'z_log': True,
'z_lims': [1e-3,1e0],
'z_label': 'Fraction of events',
'analysis_modules': ['NormalizeRowsToUnity'],
'filename': obs,
'www': 'responses_'+mc+cut+postfix,
'nicks': [obs],
'weights': [cutstring+'*'+gencutstring],
'zjetfolders': ['zjetcuts_L1L2L3'],
'colormap': 'summer_r',
'no_energy_label': True,
'texts': [r"$\\bf{CMS} \\hspace{0.5} \\it{Simulation} \\hspace{0.2} \\it{Preliminary}$" if CMSLABEL else ""],
'texts_x': [0.05],
'texts_y': [1.06],
'texts_size': [20],
'figsize': [8,6.5],
})
if obs == 'zpt':
d['x_ticks'] = [30,60,100,200,400,1000]
d['y_ticks'] = [30,60,100,200,400,1000]
elif obs == 'phistareta':
d['x_ticks'] = [0.5,1.0,2.0,4.0,10,30]
d['y_ticks'] = [0.5,1.0,2.0,4.0,10,30]
d['y_lims'] = [0.4,50]
plots.append(d)
return [PlottingJob(plots=plots, args=args)]
def plot_zpt_phistareta_correlation(args=None, cut='_jet1pt20', mc='mad', postfix=''):
plots=[]
gen = 'gen'
cutstring = generate_basiccutstring(args,gen+cut)
d = ({
'corrections': [''],
'files': [DATASETS[mc]],
'y_expressions': [gen+'zpt'],
'y_bins': 'zpt',
'y_log': True,
'y_label': gen+'zpt',
'y_ticks': [30,60,100,200,400,1000],
'y_lims': [25,1000],
'x_expressions': [gen+'phistareta'],
'x_bins': 'phistareta',
'x_log': True,
'x_label': gen+'phistareta',
'x_ticks': [0.5,1.0,2.0,4.0,10,30],
'x_lims': [0.4,50],
'z_log': True,
'z_lims': [1e0,1e4],
#'analysis_modules': ['GetCorrelationFactor'],
'filename': gen+'phistareta_'+gen+'zpt',
'www': 'responses_'+mc+cut+postfix,
'nicks': ['correlation'],
'weights': [cutstring],
'zjetfolders': [gen+'zjetcuts_L1L2L3'],
'figsize': [8,6.5],
'no_energy_label': True,
'texts': [r"$\\bf{CMS} \\hspace{0.5} \\it{Simulation} \\hspace{0.2} \\it{Preliminary}$" if CMSLABEL else ""],
#'plot_modules': ['ExportRoot'],
'texts_size': [20],
'texts_y': [1.06,0.1],
'texts_x': [0.03,0.15],
})
plots.append(d)
return [PlottingJob(plots=plots, args=args)]
def plot_something_here(args=None,cut='_jet1pt10'):
cutstring = generate_basiccutstring(args,cut)
weightstring = '(leptonIDSFWeight)*(leptonIsoSFWeight)*(leptonTriggerSFWeight)'
plots = []
d = ({
'files': [ #'/storage/8/tberger/excalibur_results/2019-06-17/data16_mm_BCDEFGH_SiMu17Jul2018.root',
'/storage/8/tberger/excalibur_results/2019-06-17/data16_mm_BCDEFGH_SiMu07Aug17.root',
'/storage/8/tberger/excalibur_results/2019-06-17/mc16_mm_BCDEFGH_DYtoLLamcatnlo.root',
],
'folders': ['nocuts_L1L2L3Res/ntuple','nocuts_L1L2L3/ntuple'],
#'folders': ['zjetcuts_L1L2L3Res/ntuple','zjetcuts_L1L2L3/ntuple'],
#'weights': ['(abs(zmass-91.1876)<20)'],#,'(abs(zmass-91.1876)<20)/puWeight'],
'weights': [weightstring,'1'],#+'/puWeight'],
'x_expressions': ['npumean'],
'x_bins': 'npumean',
#'www': 'test_noPU',
'www': 'test_inclPU',
'analysis_modules': ['Ratio'],
'y_log': True,
'y_subplot_lims': [0.5,1.5],
'lumis': [35.9],
})
plots.append(d)
return [PlottingJob(plots=plots, args=args)]
def plot_mc_comparison_inclusive(args=None, cut='_jet1pt20', data='17Jul2018', mc='mad', postfix=''):
#def plot_mc_comparison_inclusive(args=None, cut='_jet1pt20', data='17Jul2018', mc='mad', postfix='_noPURW'):
plots=[]
#cutstring = '1'
cutstring = generate_basiccutstring(args,cut)
#weightstring = '1'
weightstring = '(leptonIDSFWeight)*(leptonIsoSFWeight)*(leptonTriggerSFWeight)'#/6225.42*4963.0'
samples = [data,'mad','amc','hpp']
#backgrounds = ['TT','WZ','ZZ','WW','TW']
backgrounds = ['TT','WZ','ZZ','TW','WW']
#for obs in ['zl1pt','zl2pt','zl1eta','zl2eta','npumean','npv','rho','zpt','phistareta','zy','zmass','mupluspt','muminuspt','muminuseta','mupluseta','jet1pt','jet1y','yboost','ystar']:
#for obs in ['npv','rho','npumean']:
for obs in ['zpt','phistareta']:
d = ({
'corrections': [''],
'x_expressions': [obs],
'x_bins': obs,
'x_log': obs in ['zpt','phistareta'],
'x_errors': [1],
'x_label': obs,
'y_log': True,
'y_label': 'Events per binwidth',
'ratio_denominator_no_errors': False,
'filename': obs,
'lumis': [35.9],
#'no_energy_label': True,
#'figsize': [12,8],
#'legend_cols': 8,
#'y_lims': [1e5,1e10],
'texts': [r"$\\bf{CMS} \\hspace{0.5} \\it{Preliminary}$" if CMSLABEL else ""],
'texts_x': [0.05],
'texts_y': [1.07],
'texts_size': [20],
'www': 'datamc_comparison_'+data+cut+postfix,
})
d1 = deepcopy(d)
d1.update({
'files': [DATASETS[x] for x in samples+backgrounds],
'nicks': [obs+x for x in samples+backgrounds],
'weights': [cutstring+'*'+weightstring]+(len(samples+backgrounds)-1)*[cutstring],
'zjetfolders': ['zjetcuts_L1L2L3Res']+(len(samples+backgrounds)-1)*['zjetcuts_L1L2L3'],
'sum_result_nicks': [obs+'signal'],
'sum_nicks': [obs+data+' '+obs+(' '+obs).join(backgrounds)],
'sum_scale_factors': ['1'+' -1'*len(backgrounds)],
'ratio_numerator_nicks': [obs+'signal'],
'ratio_denominator_nicks': [obs+x for x in samples[1:]],
'ratio_result_nicks': ['ratio'+x for x in samples[1:]],
'colors': ['black']+[(COLORDICT[x],COLORDICT[x]) for x in samples[1:]],
'markers': ['.']+[(MARKERDICT[x],MARKERDICT[x]) for x in samples[1:]],
'step': True,
'line_styles': ['']+(len(samples)-1)*['-',''],
'y_subplot_label': '(Data$-$Bkg)/MC',
'y_subplot_lims': [0.75,1.25],
'analysis_modules': ['SumOfHistograms','NormalizeByBinWidth','NormalizeToFirstHisto','Ratio'],
#'normalization_base_histo': obs+'signal',
#'histograms_to_normalize': obs+'hpp',
'labels': ['Data $-$ Bkg']+[(LABELDICT[x],LABELDICT[x]) for x in samples[1:]],
'nicks_whitelist': ['signal']+samples[1:],
})
d1['www']+='_all_bkgsubtracted'
d2 = deepcopy(d)
d2.update({
'files': [DATASETS[x] for x in [data,mc]+backgrounds],
'analysis_modules': ['SumOfHistograms','NormalizeByBinWidth','Ratio'],
'nicks': [obs+x for x in [data,mc]+backgrounds],
'weights': [cutstring+'*'+weightstring]+(len(backgrounds)+1)*[cutstring],
'zjetfolders': ['zjetcuts_L1L2L3Res']+(len(backgrounds)+1)*['zjetcuts_L1L2L3'],
'sum_result_nicks': [obs+'sim'],
'sum_nicks': [obs+mc+' '+obs+(' '+obs).join(backgrounds)],
'stacks': ['data']+(len(backgrounds)+1)*['MC']+['ratio'],
'ratio_numerator_nicks': [obs+data],
'ratio_denominator_nicks': [obs+'sim'],
'ratio_result_nicks': ['ratio'],
'y_subplot_label': 'Data/Sim',
'y_subplot_lims': [0.75,1.25],
#'y_subplot_lims': [0.5,1.5],
'labels': ['Data','DY ('+LABELDICT[mc]+')']+backgrounds+[''],
'nicks_blacklist': ['sim'],
'labelsize': 25,
'legend': None,
#'title': 'Before PU reweighting',
})
if postfix == '_noPURW':
d2['weights'] = [cutstring+'*'+weightstring]+(len(backgrounds)+1)*[cutstring+'/puWeight'],
d2['www'] += '_'+mc+'_bkgadded'
#d2.update({
# 'plot_modules': ['ExportRoot'],
# 'nicks_whitelist': ['ratio'],
# 'labels': ['pileupweight'],
#})
plots.append(d1)
plots.append(d2)
return [PlottingJob(plots=plots, args=args)]
