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: