for category in categoryNames:
if category == 'inclusive':
continue
#yieldTable._rowList = ['Initial', '.', '.', '.', '.']
yieldTable._rowList = ['.', '.', '.', '.', '.']
if category[:2] == '3l' and do3l:
yieldTable._rowList.extend(['3 lepton', 'Z removal', 'MET \& HT ', 'b-jet']) #, '1 jet'])
#yieldTable._rowList.extend(['.', '.', '.', '.', '.', '.', 'BDT > -0.3'])
elif category[:2] == 'ss' and doSS:
yieldTable._rowList.extend(['ss lepton', '.', 'MET \& HT', '1 b-jet']) #, '1 jet'])
elif category[:2] == 'os' and doOS:
yieldTable._rowList.extend(['2 os leptons', 'MET cut', '1 b-jet/1 jet', 'Z removal'])
yieldTable._category = category
histDict = yieldTable.get_hist_dict('YieldByCut')
if category[:2] == 'os':
continue
#yieldTable.print_table(histDict, doErrors = False, doEff = False, startBin = 1)
else:
yieldTable.print_table(histDict, doErrors = False, doEff = False, startBin = 1)
outFile.close()
subprocess.call('pdflatex -output-dir=yields yields/yields.tex', shell = True)
subprocess.call('cp yields/yields.pdf plots/{0}/{1}_{2}/.'.format(currentDate, selection, suffix), shell = True)
subprocess.call('cp yields/.yields_tmp.tex plots/{0}/{1}_{2}/yields.tex'.format(currentDate, selection, suffix), shell = True)
#yieldTable._columnList = ['BG', 'DATA', 'FCNHWW', 'FCNHZZ', 'FCNHTauTau']
#yieldTable._columnList = ['BG', 'DATA', 'FCNH']#, 'Significance']
yieldTable.add_datasets(samples['3l_inclusive'], Clear = True)
#yieldTable.add_datasets('TTH_M-125')
yieldTable.add_datasets('FCNH')
#yieldTable.add_datasets('FCNHWW')
#yieldTable.add_datasets('FCNHZZ')
#yieldTable.add_datasets('FCNHTauTau')
yieldTable.add_datasets('DATA')
yieldTable._rowList = 5*['.'] + ['ss dilepton', 'Z removal', '2+ jets', 'MET/jet']
for category in cat3l:
yieldTable._category = category
histDict = yieldTable.get_hist_dict('YieldByCut')
yieldTable.print_table(histDict, doErrors = True, doEff = False, startBin = 1)
if doSS:
#yieldTable.add_datasets(['Irreducible', 'Fakes', 'QFlips'], Clear = True)
yieldTable._rowList = 5*['.'] + ['ss dilepton', 'Z removal', '2+ jets', 'MET']
yieldTable._columnList = ['Rare', 'WZJets3LNu', 'QFlips', 'Fakes', 'BG', 'DATA', 'FCNH']
#yieldTable._columnList = ['Rare', 'WZJets3LNu', 'QFlips', 'Fakes', 'BG', 'DATA', 'FCNHWW', 'FCNHTauTau', 'FCNHZZ']#, 'Significance']
#yieldTable._columnList = ['Rare', 'WZJets3LNu', 'QFlips', 'Fakes', 'BG', 'DATA', 'TTH_M-125']
#yieldTable._columnList = ['Rare', 'WZJets3LNu', 'QFlips', 'Fakes', 'BG', 'DATA', 'FCNHUp', 'FCNH']
for category in catSS:
yieldTable.add_datasets(samples[category], Clear = True)
