def fn(input_name, isData, full_path):
PInfo(sname + '.fn', 'Starting to process ' + input_name)
# now we instantiate and configure the analyzer
skimmer = root.PandaAnalyzer()
analysis = gghbb(True)
analysis.processType = utils.classify_sample(full_path, isData)
skimmer.SetAnalysis(analysis)
skimmer.isData = isData
return utils.run_PandaAnalyzer(skimmer, isData, input_name)
def fn(input_name, isData, full_path):
a = analysis('jes', varyJES=True, rerunJES=True)
a.inpath = input_name
a.outpath = utils.input_to_output(input_name)
a.datapath = data_dir
a.isData = isData
utils.set_year(a, 2016)
a.processType = utils.classify_sample(full_path, isData)
skimmer = root.pa.PandaAnalyzer(a)
return utils.run_PandaAnalyzer(skimmer, isData, a.outpath)
def fn(input_name, isData, full_path):
a = analysis('graph', ak=True, ak8=True, puppiJets=True)
a.inpath = input_name
a.outpath = utils.input_to_output(input_name)
a.datapath = data_dir
a.isData = isData
utils.set_year(a, 2016)
a.processType = utils.classify_sample(full_path, isData)
skimmer = root.pa.JGAnalyzer(a)
return utils.run_PandaAnalyzer(skimmer, isData, a.outpath)
def fn(input_name, isData, full_path):
a = monotop(True)
a.inpath = input_name
a.outpath = utils.input_to_output(input_name)
a.datapath = data_dir
a.isData = isData
utils.set_year(a, 2016)
a.processType = utils.classify_sample(full_path, isData)
skimmer = root.pa.PandaAnalyzer(a)
skimmer.AddPresel(root.pa.RecoilSel())
return utils.run_PandaAnalyzer(skimmer, isData, a.outpath)
def fn(input_name, isData, full_path):
logger.info(sname + '.fn', 'Starting to process ' + input_name)
# now we instantiate and configure the analyzer
skimmer = root.PandaAnalyzer()
analysis = vbf(True)
analysis.processType = utils.classify_sample(full_path, isData)
analysis.genOnly = True
skimmer.SetAnalysis(analysis)
skimmer.isData = isData
skimmer.AddPresel(root.GenBosonSel())
return utils.run_PandaAnalyzer(skimmer, isData, input_name)
def fn(input_name, isData, full_path):
logger.info(sname + '.fn', 'Starting to process ' + input_name)
# now we instantiate and configure the analyzer
skimmer = root.PandaAnalyzer()
analysis = wlnhbb_ca15(True)
analysis.processType = utils.classify_sample(full_path, isData)
analysis.reclusterGen = False
skimmer.SetAnalysis(analysis)
skimmer.isData = isData
skimmer.AddPresel(root.VHbbSel())
skimmer.AddPresel(root.TriggerSel())
return utils.run_PandaAnalyzer(skimmer, isData, input_name)
def fn(input_name, isData, full_path):
# now we instantiate and configure the analyzer
a = monotop()
a.inpath = input_name
a.outpath = utils.input_to_output(input_name)
a.datapath = data_dir
a.isData = isData
utils.set_year(a, 2016)
a.processType = utils.classify_sample(full_path, isData)
skimmer = root.pa.PandaAnalyzer(a)
skimmer.AddPresel(root.pa.MonotopSel())
return utils.run_PandaAnalyzer(skimmer, isData, a.outpath)
def fn(input_name, isData, full_path):
a = analysis('substructure',
recalcECF=False,
reclusterFJ=True,
ak=False)
a.inpath = input_name
a.outpath = utils.input_to_output(input_name)
a.datapath = data_dir
a.isData = isData
utils.set_year(a, 2016)
a.processType = utils.classify_sample(full_path, isData)
skimmer = root.pa.HRAnalyzer(a)
return utils.run_HRAnalyzer(skimmer, isData, a.outpath)
def fn(input_name, isData, full_path):
PInfo(sname + '.fn', 'Starting to process ' + input_name)
# now we instantiate and configure the analyzer
skimmer = root.PandaAnalyzer()
skimmer.isData = isData
skimmer.SetFlag('firstGen', True)
skimmer.SetFlag('fatjet', False)
skimmer.SetFlag('vbf', True)
skimmer.SetFlag('puppi', False)
skimmer.SetPreselectionBit(root.PandaAnalyzer.kRecoil50)
processType = utils.classify_sample(full_path, isData)
skimmer.processType = processType
return utils.run_PandaAnalyzer(skimmer, isData, input_name)
def fn(input_name, isData, full_path):
PInfo(sname + '.fn', 'Starting to process ' + input_name)
# now we instantiate and configure the analyzer
skimmer = root.PandaAnalyzer()
skimmer.SetAnalysis(wlnhbb(True))
analysis = wlnhbb(True)
analysis.processType = utils.classify_sample(full_path, isData)
if analysis.processType == root.kTT or analysis.processType == root.kSignal:
analysis.reclusterGen = True # only turn on if necessary
skimmer.isData = isData
skimmer.SetPreselectionBit(root.PandaAnalyzer.kVHBB)
skimmer.SetPreselectionBit(root.PandaAnalyzer.kPassTrig)
return utils.run_PandaAnalyzer(skimmer, isData, input_name)
def fn(input_name, isData, full_path):
logger.info(sname + '.fn', 'Starting to process ' + input_name)
# now we instantiate and configure the analyzer
a = breg()
a.inpath = input_name
a.outpath = utils.input_to_output(input_name)
a.datapath = data_dir
a.isData = isData
utils.set_year(a, 2017)
a.processType = utils.classify_sample(full_path, isData)
skimmer = root.pa.PandaAnalyzer(a)
return utils.run_PandaAnalyzer(skimmer, isData, a.outpath)
def fn(input_name, isData, full_path):
a = wlnhbb(True)
a.inpath = input_name
a.outpath = utils.input_to_output(input_name)
a.datapath = data_dir
a.isData = isData
utils.set_year(a, 2017)
a.processType = utils.classify_sample(full_path, isData)
if a.processType in {root.pa.kTT, root.pa.kH}:
a.reclusterGen = True # only turn on if necessary
skimmer = root.pa.PandaAnalyzer(a)
skimmer.AddPresel(root.pa.VHbbSel())
skimmer.AddPresel(root.pa.TriggerSel())
return utils.run_PandaAnalyzer(skimmer, isData, a.outpath)
def fn(input_name, isData, full_path):
logger.info(sname+'.fn','Starting to process '+input_name)
# now we instantiate and configure the analyzer
skimmer = root.PandaAnalyzer()
processType = utils.classify_sample(full_path, isData)
analysis = monotop()
analysis.processType = processType
analysis.dump()
skimmer.SetAnalysis(analysis)
skimmer.isData=isData
skimmer.AddPresel(root.MonotopSel())
outpath = utils.run_PandaAnalyzer(skimmer, isData, input_name)
if not outpath:
return False
return True
def fn(input_name, isData, full_path):
logger.info(sname + '.fn', 'Starting to process ' + input_name)
# now we instantiate and configure the analyzer
a = wlnhbb2017(True)
a.inpath = input_name
a.outpath = utils.input_to_output(input_name)
a.datapath = data_dir
a.isData = isData
utils.set_year(a, 2017)
a.processType = utils.classify_sample(full_path, isData)
if a.processType in {root.pa.kTT, root.pa.kH}:
a.reclusterGen = True # only turn on if necessary
skimmer = root.pa.PandaAnalyzer(a)
skimmer.AddPresel(root.pa.VHbbSel())
skimmer.AddPresel(root.pa.TriggerSel())
return utils.run_PandaAnalyzer(skimmer, isData, a.outpath)
def fn(input_name, isData, full_path):
logger.info(sname + '.fn', 'Starting to process ' + input_name)
# now we instantiate and configure the analyzer
skimmer = root.PandaAnalyzer()
processType = utils.classify_sample(full_path, isData)
if processType in {root.kSignal, root.kTT}:
processType = root.kTop
analysis = deepgen()
analysis.deepExC = True
analysis.processType = processType
analysis.dump()
skimmer.SetAnalysis(analysis)
skimmer.isData = isData
outpath = utils.run_PandaAnalyzer(skimmer, isData, input_name)
if not outpath:
return False
deep_utils.run_model(outpath.replace('.root', '_gen_%i.root'), outpath)
return True
def fn(input_name, isData, full_path):
PInfo(sname + '.fn', 'Starting to process ' + input_name)
# now we instantiate and configure the analyzer
skimmer = root.PandaAnalyzer()
processType = utils.classify_sample(full_path, isData)
if processType == root.kSignal:
processType = root.kTop
analysis = deepgen()
analysis.processType = processType
# analysis.deepAntiKtSort = True
analysis.dump()
skimmer.SetAnalysis(analysis)
skimmer.isData = isData
skimmer.SetPreselectionBit(root.PandaAnalyzer.kGenFatJet)
outpath = utils.run_PandaAnalyzer(skimmer, isData, input_name)
if not outpath:
return False
deep_utils.run_model(outpath.replace('.root', '_gen_%i.root'), outpath)
return True
def fn(input_name, isData, full_path):
PInfo(sname + '.fn', 'Starting to process ' + input_name)
# now we instantiate and configure the analyzer
skimmer = root.PandaAnalyzer()
processType = utils.classify_sample(full_path, isData)
if processType == root.kSignal:
processType = root.kTop
analysis = deep()
analysis.processType = processType
analysis.dump()
skimmer.SetAnalysis(analysis)
skimmer.isData = isData
skimmer.SetPreselectionBit(root.PandaAnalyzer.kFatjet450)
outpath = utils.run_PandaAnalyzer(skimmer, isData, input_name)
if not outpath:
return False
for f in glob('*_pf_*.root'):
add_bdt(f, 'inputs')
deep_utils.run_model(outpath.replace('.root', '_pf_%i.root'), outpath)
return True
argv = []
import ROOT as root
from PandaCore.Utils.load import *
from PandaAnalysis.Flat.analysis import vv
import PandaAnalysis.T3.job_utilities as utils
Load('PandaAnalyzer')
analysis = vv(True)
analysis.inpath = torun
analysis.outpath = output
analysis.datapath = getenv('CMSSW_BASE') + '/src/PandaAnalysis/data/'
analysis.isData = False
utils.set_year(analysis, 2017)
analysis.processType = utils.classify_sample(torun, analysis.isData)
print "Process: ", analysis.processType
skimmer = root.pa.PandaAnalyzer(analysis, debug_level)
skimmer.AddPresel(root.pa.LeptonSel())
skimmer.AddPresel(root.pa.TriggerSel())
skimmer.firstEvent = 0
skimmer.lastEvent = -1
skimmer.isData = False
if skimmer.isData:
with open(
getenv('CMSSW_BASE') +
'/src/PandaAnalysis/data/certs/Cert_271036-284044_13TeV_23Sep2016ReReco_Collisions16_JSON.txt'
) as jsonFile:
