def getsamples(era,channel="",tag="",dtype=[],filter=[],veto=[],moddict={},verb=0):
"""Help function to get samples from a sample list and filter if needed."""
import TauFW.PicoProducer.tools.config as GLOB
CONFIG = GLOB.getconfig(verb=verb)
filters = filter if not filter or isinstance(filter,list) else [filter]
vetoes = veto if not veto or isinstance(veto,list) else [veto]
dtypes = dtype if not dtype or isinstance(dtype,list) else [dtype]
sampfile = ensurefile("samples",repkey(CONFIG.eras[era],ERA=era,CHANNEL=channel,TAG=tag))
samppath = sampfile.replace('.py','').replace('/','.')
if samppath not in moddict:
moddict[samppath] = importlib.import_module(samppath) # save time by loading once
if not hasattr(moddict[samppath],'samples'):
LOG.throw(IOError,"Module '%s' must have a list of Sample objects called 'samples'!"%(samppath))
samplelist = moddict[samppath].samples
samples = [ ]
sampledict = { } # ensure for unique names
LOG.verb("getsamples: samplelist=%r"%(samplelist),verb,3)
for sample in samplelist:
if filters and not sample.match(filters,verb): continue
if vetoes and sample.match(vetoes,verb): continue
if dtypes and sample.dtype not in dtypes: continue
if channel and sample.channels and not any(fnmatch(channel,c) for c in sample.channels): continue
if sample.name in sampledict:
LOG.throw(IOError,"Sample short names should be unique. Found two samples '%s'!\n\t%s\n\t%s"%(
sample.name,','.join(sampledict[sample.name].paths),','.join(sample.paths)))
if 'skim' in channel and sample.dosplit: # split samples with multiple DAS dataset paths, and submit as separate jobs
for subsample in sample.split():
samples.append(subsample) # keep correspondence sample to one sample in DAS
else:
samples.append(sample)
sampledict[sample.name] = sample
return samples
dest='verbosity',
type=int,
nargs='?',
const=1,
default=0,
action='store')
args = parser.parse_args()
# SETTING
era = args.era # e.g. '2017', 'UL2017', ...
year = getyear(era) # integer year, e.g. 2017
modname = args.module # main module to run
channel = args.channel # channel
if channel:
import TauFW.PicoProducer.tools.config as GLOB
CONFIG = GLOB.getconfig(verb=0)
if not modname:
assert channel in CONFIG.channels, "Did not find channel '%s' in configuration. Available channels: %s" % (
channel, CONFIG.channels)
modname = CONFIG.channels[args.channel]
else:
if not modname:
modname = "ModuleMuTauSimple"
channel = modname
dtype = args.dtype # data type ('data', 'mc', 'embed')
outdir = ensuredir(args.outdir) # directory to create output
copydir = args.copydir # directory to copy output to at end
firstevt = args.firstevt # index of first event to run
maxevts = args.maxevts # maximum number of events to run
nfiles = 1 if maxevts > 0 else -1 # maximum number of files to run
tag = args.tag # postfix tag of job output file
def main():
eras = args.eras
periods = cleanEras(args.periods)
channel = args.channel
types = args.types
verbosity = args.verbosity
minbiases = [69.2] if periods else [69.2, 80.0, 69.2 * 1.046, 69.2 * 0.954]
for era in args.eras:
year = getyear(era)
mcfilename = "MC_PileUp_%s.root" % (era)
jsondir = os.path.join(datadir, 'json', str(year))
pileup = os.path.join(jsondir, "pileup_latest.txt")
CMSStyle.setCMSEra(year)
if era == '2016':
# https://twiki.cern.ch/twiki/bin/viewauth/CMS/PdmV2017Analysis
# /afs/cern.ch/cms/CAF/CMSCOMM/COMM_DQM/certification/Collisions16/13TeV/ReReco/Final/Cert_271036-284044_13TeV_23Sep2016ReReco_Collisions16_JSON.txt"
# /afs/cern.ch/cms/CAF/CMSCOMM/COMM_DQM/certification/Collisions16/13TeV/Final/Cert_271036-284044_13TeV_PromptReco_Collisions16_JSON.txt
# /afs/cern.ch/cms/CAF/CMSCOMM/COMM_DQM/certification/Collisions16/13TeV/PileUp/pileup_latest.txt
JSON = os.path.join(
jsondir,
"Cert_271036-284044_13TeV_ReReco_07Aug2017_Collisions16_JSON.txt"
)
datasets = {
'B': (272007, 275376),
'C': (275657, 276283),
'D': (276315, 276811),
'E': (276831, 277420),
'F': (277772, 278808),
'G': (278820, 280385),
'H': (280919, 284044),
}
campaign = "Moriond17"
samples = [
(
'TT',
"TT",
),
(
'DY',
"DYJetsToLL_M-10to50",
),
(
'DY',
"DYJetsToLL_M-50",
),
(
'DY',
"DY1JetsToLL_M-50",
),
(
'DY',
"DY2JetsToLL_M-50",
),
(
'DY',
"DY3JetsToLL_M-50",
),
(
'WJ',
"WJetsToLNu",
),
(
'WJ',
"W1JetsToLNu",
),
(
'WJ',
"W2JetsToLNu",
),
(
'WJ',
"W3JetsToLNu",
),
(
'WJ',
"W4JetsToLNu",
),
(
'ST',
"ST_tW_top",
),
(
'ST',
"ST_tW_antitop",
),
(
'ST',
"ST_t-channel_top",
),
(
'ST',
"ST_t-channel_antitop",
),
#( 'ST', "ST_s-channel", ),
(
'VV',
"WW",
),
(
'VV',
"WZ",
),
(
'VV',
"ZZ",
),
]
elif '2017' in era:
# https://twiki.cern.ch/twiki/bin/viewauth/CMS/PdmV2017Analysis
# /afs/cern.ch/cms/CAF/CMSCOMM/COMM_DQM/certification/Collisions16/13TeV/Final/Cert_271036-284044_13TeV_PromptReco_Collisions16_JSON.txt
# /afs/cern.ch/cms/CAF/CMSCOMM/COMM_DQM/certification/Collisions17/13TeV/PileUp/pileup_latest.txt
JSON = os.path.join(
jsondir,
"Cert_294927-306462_13TeV_PromptReco_Collisions17_JSON.txt")
datasets = {
'B': (297020, 299329),
'C': (299337, 302029),
'D': (302030, 303434),
'E': (303435, 304826),
'F': (304911, 306462),
}
samples_bug = []
samples_fix = []
if 'UL' in era:
campaign = "Summer19"
samples_fix = [
#( 'DY', "DYJetsToLL_M-10to50", ),
(
'DY',
"DYJetsToLL_M-50",
),
(
'DY',
"DY1JetsToLL_M-50",
),
(
'DY',
"DY2JetsToLL_M-50",
),
(
'DY',
"DY3JetsToLL_M-50",
),
(
'DY',
"DY4JetsToLL_M-50",
),
#( 'TT', "TTTo2L2Nu", ),
(
'TT',
"TTToHadronic",
),
#( 'TT', "TTToSemiLeptonic", ),
(
'WJ',
"WJetsToLNu",
),
(
'WJ',
"W1JetsToLNu",
),
(
'WJ',
"W2JetsToLNu",
),
(
'WJ',
"W3JetsToLNu",
),
(
'WJ',
"W4JetsToLNu",
),
(
'ST',
"ST_tW_top",
),
(
'ST',
"ST_tW_antitop",
),
(
'ST',
"ST_t-channel_top",
),
(
'ST',
"ST_t-channel_antitop",
),
#( 'ST', "ST_s-channel", ),
#( 'VV', "WW", ),
#( 'VV', "WZ", ),
#( 'VV', "ZZ", ),
]
else:
campaign = "Winter17_V2"
samples_bug = [
(
'DY',
"DYJetsToLL_M-50",
),
(
'WJ',
"W3JetsToLNu",
),
(
'VV',
"WZ",
),
]
samples_fix = [
(
'DY',
"DYJetsToLL_M-10to50",
),
(
'DY',
"DY1JetsToLL_M-50",
),
(
'DY',
"DY2JetsToLL_M-50",
),
(
'DY',
"DY3JetsToLL_M-50",
),
(
'DY',
"DY4JetsToLL_M-50",
),
(
'TT',
"TTTo2L2Nu",
),
(
'TT',
"TTToHadronic",
),
(
'TT',
"TTToSemiLeptonic",
),
(
'WJ',
"WJetsToLNu",
),
(
'WJ',
"W1JetsToLNu",
),
(
'WJ',
"W2JetsToLNu",
),
(
'WJ',
"W4JetsToLNu",
),
(
'ST',
"ST_tW_top",
),
(
'ST',
"ST_tW_antitop",
),
(
'ST',
"ST_t-channel_top",
),
(
'ST',
"ST_t-channel_antitop",
),
#( 'ST', "ST_s-channel", ),
(
'VV',
"WW",
),
(
'VV',
"ZZ",
),
]
samples = samples_bug + samples_fix
else:
# https://twiki.cern.ch/twiki/bin/viewauth/CMS/PdmV2018Analysis
# /afs/cern.ch/cms/CAF/CMSCOMM/COMM_DQM/certification/Collisions18/13TeV/PromptReco
# /afs/cern.ch/cms/CAF/CMSCOMM/COMM_DQM/certification/Collisions18/13TeV/PileUp/pileup_latest.txt
JSON = os.path.join(
jsondir,
"Cert_314472-325175_13TeV_PromptReco_Collisions18_JSON.txt")
datasets = {
'A': (315252, 316995),
'B': (317080, 319310),
'C': (319337, 320065),
'D': (320673, 325175),
}
campaign = "Autumn18"
samples = [
(
'TT',
"TTTo2L2Nu",
),
(
'TT',
"TTToHadronic",
),
(
'TT',
"TTToSemiLeptonic",
),
(
'DY',
"DYJetsToLL_M-10to50",
),
(
'DY',
"DYJetsToLL_M-50",
),
(
'DY',
"DY1JetsToLL_M-50",
),
(
'DY',
"DY2JetsToLL_M-50",
),
(
'DY',
"DY3JetsToLL_M-50",
),
(
'DY',
"DY4JetsToLL_M-50",
),
#( 'WJ', "WJetsToLNu", ),
(
'WJ',
"W1JetsToLNu",
),
(
'WJ',
"W2JetsToLNu",
),
(
'WJ',
"W3JetsToLNu",
),
(
'WJ',
"W4JetsToLNu",
),
(
'ST',
"ST_tW_top",
),
(
'ST',
"ST_tW_antitop",
),
(
'ST',
"ST_t-channel_top",
),
(
'ST',
"ST_t-channel_antitop",
),
#( 'ST', "ST_s-channel", ),
(
'VV',
"WW",
),
(
'VV',
"WZ",
),
(
'VV',
"ZZ",
),
]
# SAMPLES FILENAMES
fname = "$PICODIR/$SAMPLE_$CHANNEL.root"
if '$PICODIR' in fname:
import TauFW.PicoProducer.tools.config as GLOB
CONFIG = GLOB.getconfig(verb=verbosity)
fname = repkey(fname, PICODIR=CONFIG['picodir'])
for i, (group, sample) in enumerate(samples):
fname = repkey(fname,
ERA=era,
GROUP=group,
SAMPLE=sample,
CHANNEL=channel)
samples[i] = (sample, fname)
if verbosity >= 1:
print ">>> samples = %r" % (samples)
# JSON
jsons = {}
if periods:
outdir = ensuredir("json")
for period in periods:
start, end = getPeriodRunNumbers(period, datasets)
erarun = "Run%d%s" % (era, period)
jsonout = "json/" + re.sub(r"\d{6}-\d{6}", erarun,
JSON.split('/')[-1])
filterJSONByRunNumberRange(JSON,
jsonout,
start,
end,
verb=verbosity)
jsons[erarun] = jsonout
else:
jsons[era] = JSON
# DATA
datahists = {period: [] for period in jsons}
if 'data' in types:
for period, json in jsons.iteritems():
for minbias in minbiases:
filename = "Data_PileUp_%s_%s.root" % (
period, str(minbias).replace('.', 'p'))
datahist = getDataProfile(filename, json, pileup, 100, era,
minbias)
datahists[period].append((minbias, datahist))
elif args.plot:
for era in jsons:
for minbias in minbiases:
filename = "Data_PileUp_%s_%s.root" % (
era, str(minbias).replace('.', 'p'))
file, hist = gethist(filename, 'pileup', retfile=True)
if not file or not hist: continue
hist.SetDirectory(0)
file.Close()
datahists[era].append((minbias, hist))
# MC
if 'mc' in types:
mcfilename = "MC_PileUp_%s.root" % (era)
#mcfilename = "MC_PileUp_%s_%s.root"%(era,campaign)
getMCProfile(mcfilename, samples, channel, era)
if args.plot:
mchist = compareMCProfiles(samples, channel, era)
for era in jsons:
for minbias, datahist in datahists[era]:
compareDataMCProfiles(datahist, mchist, era, minbias)
deletehist(mchist) # clean memory
if era == '2017': # also check new/old pmx separately
mcfilename_bug = mcfilename.replace(".root", "_old_pmx.root")
mcfilename_fix = mcfilename.replace(".root", "_new_pmx.root")
getMCProfile(mcfilename_bug, samples_bug, channel, era)
getMCProfile(mcfilename_fix, samples_fix, channel, era)
if args.plot:
mchist_bug = compareMCProfiles(samples_bug,
channel,
era,
tag="old_pmx")
mchist_fix = compareMCProfiles(samples_fix,
channel,
era,
tag="new_pmx")
for era in jsons:
for minbias, datahist in datahists[era]:
compareDataMCProfiles(datahist,
mchist_bug,
era,
minbias,
tag="old_pmx")
compareDataMCProfiles(datahist,
mchist_fix,
era,
minbias,
tag="new_pmx")
# FLAT
if 'flat' in types:
filename = "MC_PileUp_%d_FlatPU0to75.root" % era
hist_flat = getFlatProfile(filename, 75)
for era in jsons:
for minbias, datahist in datahists[era]:
compareDataMCProfiles(datahist,
hist_flat,
era,
minbias,
tag="FlatPU0to75",
rmin=0.0,
rmax=3.1)
def getsampleset(datasample, expsamples, sigsamples=[], **kwargs):
"""Create sample set from a table of data and MC samples."""
channel = kwargs.get('channel', "")
era = kwargs.get('era', "")
fpattern = kwargs.get(
'file',
None) # file name pattern, e.g. $PICODIR/$SAMPLE_$CHANNEL$TAG.root
weight = kwargs.pop('weight', "") # common weight for MC samples
dataweight = kwargs.pop('dataweight', "") # weight for data samples
url = kwargs.pop('url', "") # XRootD url
tag = kwargs.pop('tag', "") # extra tag for file name
if not fpattern:
fpattern = "$PICODIR/$SAMPLE_$CHANNEL$TAG.root"
if '$PICODIR' in fpattern:
import TauFW.PicoProducer.tools.config as GLOB
CONFIG = GLOB.getconfig(verb=0)
picodir = CONFIG['picodir']
fpattern = repkey(fpattern, PICODIR=picodir)
if url:
fpattern = "%s/%s" % (fpattern, url)
LOG.verb("getsampleset: fpattern=%r" % (fpattern), level=1)
# MC (EXPECTED)
for i, info in enumerate(expsamples[:]):
expkwargs = kwargs.copy()
expkwargs['weight'] = weight
if len(info) == 4:
group, name, title, xsec = info
elif len(info) == 5 and isinstance(info[4], dict):
group, name, title, xsec, newkwargs = info
expkwargs.update(newkwargs)
else:
LOG.throw(IOError, "Did not recognize mc row %s" % (info))
fname = repkey(fpattern,
ERA=era,
GROUP=group,
SAMPLE=name,
CHANNEL=channel,
TAG=tag)
#print fname
sample = MC(name, title, fname, xsec, **expkwargs)
expsamples[i] = sample
# DATA (OBSERVED)
title = 'Observed'
datakwargs = kwargs.copy()
datakwargs['weight'] = dataweight
if isinstance(datasample, dict) and channel:
datasample = datasample[channel]
if len(datasample) == 2:
group, name = datasample
elif len(datasample) == 3:
group, name = datasample[:2]
if isinstance(datasample[2], dict): # dictionary
datakwargs.update(datasample[2])
else: # string
title = datasample[2]
elif len(datasample) == 4 and isinstance(datasample[3], dict):
group, name, title, newkwargs = datasample
datakwargs.update(newkwargs)
else:
LOG.throw(IOError, "Did not recognize data row %s" % (datasample))
fpattern = repkey(fpattern,
ERA=era,
GROUP=group,
SAMPLE=name,
CHANNEL=channel,
TAG=tag)
fnames = glob.glob(fpattern)
#print fnames
if len(fnames) == 1:
datasample = Data(name, title, fnames[0])
elif len(fnames) > 1:
namerexp = re.compile(name.replace('?', '.').replace('*', '.*'))
name = name.replace('?', '').replace('*', '')
datasample = MergedSample(name, 'Observed', data=True)
for fname in fnames:
setname = namerexp.findall(fname)[0]
#print setname
datasample.add(Data(setname, 'Observed', fname, **datakwargs))
else:
LOG.throw(IOError, "Did not find data file %r" % (fpattern))
# SAMPLE SET
sampleset = SampleSet(datasample, expsamples, sigsamples, **kwargs)
return sampleset
def main():
eras = args.eras
periods = cleanPeriods(args.periods)
channel = args.channel
types = args.types
verbosity = args.verbosity
minbiases = [ 69.2 ] if periods else [ 69.2, 69.2*1.046, 69.2*0.954, 80.0 ]
fname_ = "$PICODIR/$SAMPLE_$CHANNEL.root" # sample file name
if 'mc' in types and '$PICODIR' in fname_:
import TauFW.PicoProducer.tools.config as GLOB
CONFIG = GLOB.getconfig(verb=verbosity)
fname_ = repkey(fname_,PICODIR=CONFIG['picodir'])
for era in args.eras:
year = getyear(era)
mcfilename = "MC_PileUp_%s.root"%(era)
jsondir = os.path.join(datadir,'json',str(year))
pileup = os.path.join(jsondir,"pileup_latest.txt")
jname = getJSON(era)
CMSStyle.setCMSEra(era)
samples_bug = [ ] # buggy samples in (pre-UL) 2017 with "old pmx" library
samples_fix = [ ] # fixed samples in (pre-UL) 2017 with "new pmx" library
samples = [ # default set of samples
( 'DY', "DYJetsToMuTauh_M-50" ),
( 'DY', "DYJetsToLL_M-50" ),
( 'DY', "DY4JetsToLL_M-50" ),
( 'DY', "DY3JetsToLL_M-50" ),
( 'DY', "DY2JetsToLL_M-50" ),
( 'DY', "DY1JetsToLL_M-50" ),
( 'WJ', "WJetsToLNu" ),
( 'WJ', "W4JetsToLNu" ),
( 'WJ', "W3JetsToLNu" ),
( 'WJ', "W2JetsToLNu" ),
( 'WJ', "W1JetsToLNu" ),
( 'TT', "TTToHadronic" ),
( 'TT', "TTTo2L2Nu" ),
( 'TT', "TTToSemiLeptonic" ),
( 'ST', "ST_tW_top" ),
( 'ST', "ST_tW_antitop" ),
( 'ST', "ST_t-channel_top" ),
( 'ST', "ST_t-channel_antitop" ),
( 'VV', "WW" ),
( 'VV', "WZ" ),
( 'VV', "ZZ" ),
]
if era=='2016':
campaign = "Moriond17"
if 'UL' in era and 'preVFP' in era:
campaign = "Summer19"
elif 'UL' in era:
campaign = "Summer19"
else:
samples = [
( 'TT', "TT", ),
( 'DY', "DYJetsToLL_M-10to50", ),
( 'DY', "DYJetsToLL_M-50", ),
( 'DY', "DY1JetsToLL_M-50", ),
( 'DY', "DY2JetsToLL_M-50", ),
( 'DY', "DY3JetsToLL_M-50", ),
( 'WJ', "WJetsToLNu", ),
( 'WJ', "W1JetsToLNu", ),
( 'WJ', "W2JetsToLNu", ),
( 'WJ', "W3JetsToLNu", ),
( 'WJ', "W4JetsToLNu", ),
( 'ST', "ST_tW_top", ),
( 'ST', "ST_tW_antitop", ),
( 'ST', "ST_t-channel_top", ),
( 'ST', "ST_t-channel_antitop", ),
#( 'ST', "ST_s-channel", ),
( 'VV', "WW", ),
( 'VV', "WZ", ),
( 'VV', "ZZ", ),
]
elif '2017' in era:
if 'UL' in era:
campaign = "Summer19"
else:
campaign = "Winter17_V2"
samples_bug = [ # buggy samples in (pre-UL) 2017
( 'DY', "DYJetsToLL_M-50", ),
( 'WJ', "W3JetsToLNu", ),
( 'VV', "WZ", ),
]
samples_fix = [ # fixed samples in (pre-UL) 2017
( 'DY', "DYJetsToLL_M-10to50", ),
( 'DY', "DY1JetsToLL_M-50", ),
( 'DY', "DY2JetsToLL_M-50", ),
( 'DY', "DY3JetsToLL_M-50", ),
( 'DY', "DY4JetsToLL_M-50", ),
( 'TT', "TTTo2L2Nu", ),
( 'TT', "TTToHadronic", ),
( 'TT', "TTToSemiLeptonic", ),
( 'WJ', "WJetsToLNu", ),
( 'WJ', "W1JetsToLNu", ),
( 'WJ', "W2JetsToLNu", ),
( 'WJ', "W4JetsToLNu", ),
( 'ST', "ST_tW_top", ),
( 'ST', "ST_tW_antitop", ),
( 'ST', "ST_t-channel_top", ),
( 'ST', "ST_t-channel_antitop", ),
#( 'ST', "ST_s-channel", ),
( 'VV', "WW", ),
( 'VV', "ZZ", ),
]
samples = samples_bug + samples_fix
else:
if 'UL' in era:
campaign = "Summer19"
else:
campaign = "Autumn18"
samples = [
( 'TT', "TTTo2L2Nu", ),
( 'TT', "TTToHadronic", ),
( 'TT', "TTToSemiLeptonic", ),
( 'DY', "DYJetsToLL_M-10to50", ),
( 'DY', "DYJetsToLL_M-50", ),
( 'DY', "DY1JetsToLL_M-50", ),
( 'DY', "DY2JetsToLL_M-50", ),
( 'DY', "DY3JetsToLL_M-50", ),
( 'DY', "DY4JetsToLL_M-50", ),
#( 'WJ', "WJetsToLNu", ),
( 'WJ', "W1JetsToLNu", ),
( 'WJ', "W2JetsToLNu", ),
( 'WJ', "W3JetsToLNu", ),
( 'WJ', "W4JetsToLNu", ),
( 'ST', "ST_tW_top", ),
( 'ST', "ST_tW_antitop", ),
( 'ST', "ST_t-channel_top", ),
( 'ST', "ST_t-channel_antitop", ),
#( 'ST', "ST_s-channel", ),
( 'VV', "WW", ),
( 'VV', "WZ", ),
( 'VV', "ZZ", ),
]
# SAMPLES FILENAMES
samples_ = [ ]
suberas = [era+"_preVFP",era+"_postVFP"] if era=='UL2016' else [era]
for subera in suberas:
for i, (group,sample) in enumerate(samples):
fname = repkey(fname_,ERA=subera,GROUP=group,SAMPLE=sample,CHANNEL=channel)
samples_.append((sample,fname))
samples = samples_ # replace sample list
if verbosity>=1:
print ">>> samples = %r"%(samples)
# JSON
jsons = { }
if periods:
for period in periods:
jsonout = filterJSONByRunNumberRange(jname,era,period=period,outdir='json',verb=verbosity)
jsons[erarun] = jsonout
else:
jsons[era] = jname
# DATA
datahists = { period: [ ] for period in jsons }
if 'data' in types:
for period, json in jsons.iteritems():
for minbias in minbiases:
filename = "Data_PileUp_%s_%s.root"%(period,str(minbias).replace('.','p'))
datahist = getDataProfile(filename,json,pileup,100,era,minbias)
datahists[period].append((minbias,datahist))
elif args.plot: # do not create new data profiles, but just load them
for era in jsons:
for minbias in minbiases:
filename = "Data_PileUp_%s_%s.root"%(era,str(minbias).replace('.','p'))
file, hist = gethist(filename,'pileup',retfile=True)
if not file or not hist: continue
hist.SetDirectory(0)
file.Close()
datahists[era].append((minbias,hist))
# MC
if 'mc' in types:
assert samples, "compareMCProfiles: Did not find any samples for %r..."%(era)
mcfilename = "MC_PileUp_%s.root"%(era)
#mcfilename = "MC_PileUp_%s_%s.root"%(era,campaign)
getMCProfile(mcfilename,samples,channel,era)
if args.plot:
mchist = compareMCProfiles(samples,channel,era)
for era in jsons:
for minbias, datahist in datahists[era]:
compareDataMCProfiles(datahist,mchist,era,minbias)
compareDataMCProfiles(datahists[era],mchist,era,rmin=0.4,rmax=1.5,delete=True)
deletehist(mchist) # clean memory
if era=='2017': #and 'UL' not in era # buggy (pre-UL) 2017: also check new/old pmx separately
mcfilename_bug = mcfilename.replace(".root","_old_pmx.root")
mcfilename_fix = mcfilename.replace(".root","_new_pmx.root")
getMCProfile(mcfilename_bug,samples_bug,channel,era)
getMCProfile(mcfilename_fix,samples_fix,channel,era)
if args.plot:
mchist_bug = compareMCProfiles(samples_bug,channel,era,tag="old_pmx")
mchist_fix = compareMCProfiles(samples_fix,channel,era,tag="new_pmx")
for era in jsons:
for minbias, datahist in datahists[era]:
compareDataMCProfiles(datahist,mchist_bug,era,minbias,tag="old_pmx")
compareDataMCProfiles(datahist,mchist_fix,era,minbias,tag="new_pmx")
# FLAT
if 'flat' in types:
filename = "MC_PileUp_%d_FlatPU0to75.root"%era
hist_flat = getFlatProfile(filename,75)
for era in jsons:
for minbias, datahist in datahists[era]:
compareDataMCProfiles(datahist,hist_flat,era,minbias,tag="FlatPU0to75",rmin=0.0,rmax=3.1)
