def __init__(self, inputfile, year, ijob, njobs):
if inputfile.endswith('.txt'):
infiles = SplitUp(inputfile, njobs)[ijob - 1]
else:
infiles = inputfile
self.a = analyzer(infiles)
if inputfile.endswith('.txt'):
self.setname = inputfile.split('/')[-1].split('_')[0]
else:
self.setname = inputfile.split('/')[-1].split('_')[1]
self.year = year
self.ijob = ijob
self.njobs = njobs
self.config = OpenJSON('THconfig.json')
self.cuts = self.config['CUTS']
# self.dijetIdxs = [0,1]
self.trigs = {
16: ['HLT_PFHT800', 'HLT_PFHT900'],
17: ['HLT_PFHT1050', 'HLT_AK8PFJet500'],
18: [
'HLT_AK8PFJet400_TrimMass30', 'HLT_AK8PFHT850_TrimMass50',
'HLT_PFHT1050'
]
}
if 'Data' in inputfile:
self.a.isData = True
else:
self.a.isData = False
def CombineCommonSets(groupname,doStudies=False,modstr=''):
'''Which stitch together either QCD or ttbar (ttbar-allhad+ttbar-semilep)
@param groupname (str, optional): "QCD" or "ttbar".
'''
if groupname not in ["QCD","ttbar"]:
raise ValueError('Can only combine QCD or ttbar')
config = OpenJSON('THconfig.json')
for y in ['16','17','18']:
baseStr = 'rootfiles/TH%s_{0}{2}_{1}{3}.root'%('studies' if doStudies else 'selection')
if groupname == 'ttbar':
to_loop = [''] if doStudies else ['','JES','JER','JMS','JMR']
for v in to_loop:
if v == '':
ExecuteCmd('hadd -f %s %s %s'%(
baseStr.format('ttbar',y,modstr,''),
baseStr.format('ttbar-allhad',y,modstr,''),
baseStr.format('ttbar-semilep',y,modstr,''))
)
else:
for v2 in ['up','down']:
v3 = '_%s_%s'%(v,v2)
ExecuteCmd('hadd -f %s %s %s'%(
baseStr.format('ttbar',y,modstr,v3),
baseStr.format('ttbar-allhad',y,modstr,v3),
baseStr.format('ttbar-semilep',y,modstr,v3))
)
elif groupname == 'QCD':
ExecuteCmd('hadd -f %s %s %s %s %s'%(
baseStr.format('QCD',y,modstr,''),
baseStr.format('QCDHT700',y,modstr,''),
baseStr.format('QCDHT1000',y,modstr,''),
baseStr.format('QCDHT1500',y,modstr,''),
baseStr.format('QCDHT2000',y,modstr,''))
)
def getNormFactor(setname, year, configPath, genEventCount):
# Config loading - will have cuts, xsec, and lumi
if isinstance(configPath, str): config = OpenJSON(configPath)
else: config = configPath
cuts = config['CUTS'][year]
lumi = config['lumi']
if setname in config['XSECS'].keys():
xsec = config['XSECS'][setname]
else:
raise KeyError('Key "%s" does not exist in config["XSECS"]' % setname)
norm = (xsec * lumi) / genEventCount
return norm
def getNormFactor(setname, year, configPath):
# Config loading - will have cuts, xsec, and lumi
if isinstance(configPath, str): config = OpenJSON(configPath)
else: config = configPath
cuts = config['CUTS'][year]
lumi = config['lumi' + str(year)]
geneEventCount = config['NEVENTS'][str(year)]
# Deal with unique ttbar cases
if setname == 'ttbar' and year == '16':
setname = 'ttbar'
elif setname == 'ttbar' and (year == '17' or year == '18'):
setname = 'ttbar-allhad'
if setname in config['XSECS'].keys():
xsec = config['XSECS'][setname]
else:
raise KeyError('Key "%s" does not exist in config["XSECS"]' % setname)
norm = (xsec * lumi) / genEventCount
return norm
default=False,
dest='select',
help=
'Whether to run the selection. If False, will attempt to recycle previous run histograms.'
)
(options, args) = parser.parse_args()
###########################################
# Establish some global variables for use #
###########################################
plotdir = 'plots/' # this is where we'll save your plots
if not os.path.exists(plotdir):
os.makedirs(plotdir)
rootfile_path = 'root://cmsxrootd.fnal.gov///store/user/cmsdas/2021/long_exercises/BstarTW/rootfiles'
config = OpenJSON('bstar_config.json')
cuts = config['CUTS'][options.year]
CompileCpp("TIMBER/Framework/include/common.h")
CompileCpp(
'bstar.cc') # has the c++ functions we need when looping of the RDataFrame
# Sets we want to process and some nice naming for our plots
signal_names = ['signalLH%s' % (mass)
for mass in [2000]] #range(1400,4200,600)]
bkg_names = [
'singletop_tW', 'singletop_tWB', 'ttbar', 'QCDHT700', 'QCDHT1000',
'QCDHT1500', 'QCDHT2000'
]
##########MY ASSIGNED BACKGROUNDS##############
import json
from TIMBER.Tools.Common import OpenJSON, DictCopy
def polyStrGen(xorder,yorder):
xparts = ['@0']
yparts = ['1']
totalParams = 0
for i in range(1,xorder+1):
xparts.append('@{0}*x**{1}'.format(totalParams,i))
totalParams += 1
for i in range(1,yorder+1):
yparts.append('@{0}*y**{1}'.format(totalParams,i))
totalParams += 1
return 'max(0,0.1*(%s)*(%s))'%('+'.join(xparts),'+'.join(yparts)),totalParams
template = OpenJSON('template.json')
parameterDict = {
"NOMINAL": 0.1,
"MIN":-10.0,
"MAX":10.0,
"ERROR":0.05
}
parameterDict0 = DictCopy(parameterDict)
parameterDict0['MIN'] = -10.0
shortNames = {
'deepTag':'DAK8',
'particleNet':'PN'
}
for tagger in ['deepTag','particleNet']:
default='',
help='"Keep and drop" file for NanoAOD-tools')
parser.add_argument('--payload',
metavar='IN',
dest='payload',
default='',
help='Payload which bypasses other command line options')
parser.add_argument('--dry-run',
action='store_true',
dest='dryrun',
default=False,
help='Dry-run will not save to database')
args = parser.parse_args()
if args.payload != '':
payload = OpenJSON(args.payload)
for o in payload.keys():
if hasattr(args, o):
setattr(args, o, payload[o])
run_data = {
"timestamp": GetTimeStamp(),
"conditions": args.tag,
"process_time": None,
"process_maxmem": None,
"rootfile": None
}
start_time = time.time()
if args.framework == "TIMBER":