# dataset( "HLT_QCD_HT300to500" , QCD_HT300to500 , MC , 1 , 100 , splitting='FileBased' , priority=199 , label='signal' , doHLT=1 ) , # dataset( "HLT_QCD_HT500to700" , QCD_HT500to700 , MC , 1 , 100 , splitting='FileBased' , priority=199 , label='signal' , doHLT=1 ) , # dataset( "HLT_QCD_HT700to1000" , QCD_HT700to1000 , MC , 1 , 100 , splitting='FileBased' , priority=199 , label='signal' , doHLT=1 ) , # dataset( "HLT_QCD_HT1000to1500" , QCD_HT1000to1500 , MC , 1 , 100 , splitting='FileBased' , priority=199 , label='signal' , doHLT=1 ) , # dataset( "HLT_QCD_HT1500to2000" , QCD_HT1500to2000 , MC , 1 , 100 , splitting='FileBased' , priority=199 , label='signal' , doHLT=1 ) , # dataset( "HLT_QCD_HT2000toInf" , QCD_HT2000toInf , MC , 1 , 100 , splitting='FileBased' , priority=199 , label='signal' , doHLT=1 ) , # Data skim for trigger testing # dataset( "HLT_JetHT_G1" , JetHT_G1 , DATA , 1 , 1000 , splitting='LumiBased' , priority=199 , label='signal' , doHLT=1 ) , # dataset( "HLT_JetHT_H1" , JetHT_H1 , DATA , 1 , 1000 , splitting='LumiBased' , priority=199 , label='signal' , doHLT=1 ) , # No jobs generated with json file # dataset( "HLT_JetHT_H2" , JetHT_H2 , DATA , 1 , 1000 , splitting='LumiBased' , priority=199 , label='signal' , doHLT=1 ) , # dataset( "HLT_JetHT_H3" , JetHT_H3 , DATA , 1 , 1000 , splitting='LumiBased' , priority=199 , label='signal' , doHLT=1 ) , dataset("HLT_SingleMuon_G1", SingleMuon_G1, DATA, 20, 300000, splitting='LumiBased', priority=199, label='signal', doHLT=1), dataset("HLT_SingleMuon_H1", SingleMuon_H1, DATA, 20, 300000, splitting='LumiBased', priority=199, label='signal', doHLT=1), # No jobs generated with json file dataset("HLT_SingleMuon_H2", SingleMuon_H2,
postfix = 'v8' # Postfix to job, increment for each major version dryrun = 0 from datasets import dataset from wrappers import submit, submit_newthread datasets = [ #dataset( "WJetsToLNuInclusive" , "/WJetsToLNu_TuneCUETP8M1_13TeV-amcatnloFXFX-pythia8/RunIISpring15DR74-Asympt25ns_MCRUN2_74_V9-v1/AODSIM" , MC, 1, 1000, splitting='FileBased', priority=30, label='wjet' ), # dataset( "WJetSkimMuon" , "/SingleMuon/yoshin-WJetSkim-ede3f21fae18a825b193df32c86b780e/USER" , DATA , 10000 , 10000000 , splitting='EventAwareLumiBased' , priority=30 , label='wjet' , inputDBS='phys03' ) , #dataset( "GJet_Pt-15ToInf" , "/GJet_Pt-15ToInf_TuneCUETP8M1_13TeV-pythia8/RunIIFall15DR76-PU25nsData2015v1_76X_mcRun2_asymptotic_v12-v1/AODSIM" , MC, 1, 1000, splitting='FileBased', priority=30, label='gjet' ), #dataset( "GJetDataRun2015D-v3" , "/SinglePhoton/Run2015D-PromptReco-v3/AOD" , DATA, 1, 10000, splitting='FileBased', priority=30, label='gjet' ), #dataset( "GJetDataRun2015D-v4" , "/SinglePhoton/Run2015D-PromptReco-v4/AOD" , DATA, 1, 10000, splitting='FileBased', priority=30, label='gjet' ), dataset( "GJets_HT-600ToInf_RunIIFall15DR76", "/GJets_HT-600ToInf_TuneCUETP8M1_13TeV-madgraphMLM-pythia8/RunIIFall15DR76-PU25nsData2015v1_76X_mcRun2_asymptotic_v12-v1/AODSIM", MC, 1, 1000, splitting='FileBased', priority=30, label='gjet'), dataset( "GJets_HT-400To600_RunIIFall15DR76", "/GJets_HT-400To600_TuneCUETP8M1_13TeV-madgraphMLM-pythia8/RunIIFall15DR76-PU25nsData2015v1_76X_mcRun2_asymptotic_v12-v1/AODSIM", MC, 1, 1000, splitting='FileBased', priority=30, label='gjet'), dataset( "GJets_HT-200To400_RunIIFall15DR76",
# dataset( "mass_pi_d_10_tau_pi_d_150" , mass_pi_d_10_tau_pi_d_150 , MC , 1 , 10000 , splitting='FileBased' , priority=99 , inputDBS='phys03' , label='signal' , doHLT=0 ) , # dataset( "mass_pi_d_10_tau_pi_d_300" , mass_pi_d_10_tau_pi_d_300 , MC , 1 , 10000 , splitting='FileBased' , priority=99 , inputDBS='phys03' , label='signal' , doHLT=0 ) , # dataset( "ModelA" , ModelA , MC , 1 , 10000 , splitting='FileBased' , priority=99 , inputDBS='phys03' , label='signal' , doHLT=0 ) , # dataset( "ModelB" , ModelB , MC , 1 , 10000 , splitting='FileBased' , priority=99 , inputDBS='phys03' , label='signal' , doHLT=0 ) , # dataset( "QCD_HT50to100" , QCD_HT50to100 , MC , 10 , 10000 , splitting='FileBased' , priority=10 , label='signal' ) , # dataset( "QCD_HT100to200" , QCD_HT100to200 , MC , 10 , 10000 , splitting='FileBased' , priority=10 , label='signal' ) , # dataset( "QCD_HT200to300" , QCD_HT200to300 , MC , 10 , 10000 , splitting='FileBased' , priority=10 , label='signal' ) , # dataset( "QCD_HT300to500" , QCD_HT300to500 , MC , 10 , 10000 , splitting='FileBased' , priority=10 , label='signal' ) , # dataset( "QCD_HT500to700" , QCD_HT500to700 , MC , 2 , 10000 , splitting='FileBased' , priority=10 , label='signal' ) , # dataset( "QCD_HT700to1000" , QCD_HT700to1000 , MC , 2 , 10000 , splitting='FileBased' , priority=80 , label='signal' ) , # dataset( "QCD_HT1000to1500" , QCD_HT1000to1500 , MC , 1 , 10000 , splitting='FileBased' , priority=90 , label='signal' ) , # dataset( "QCD_HT1500to2000" , QCD_HT1500to2000 , MC , 1 , 10000 , splitting='FileBased' , priority=80 , label='signal' ) , dataset("QCD_HT2000toInf", QCD_HT2000toInf, MC, 1, 10000, splitting='FileBased', priority=99, label='signal'), # dataset( "WJet" , WJet , MC , 1 , 10000 , splitting='FileBased' , priority=70 , label='wjet' ) , # dataset( "QCD_HT700to1000x" , QCD_HT700to1000x , MC , 2 , 10000 , splitting='FileBased' , priority=80 , label='signal' ) , # dataset( "QCD_HT1000to1500x" , QCD_HT1000to1500x , MC , 1 , 10000 , splitting='FileBased' , priority=90 , label='signal' ) , # dataset( "QCD_HT1500to2000x" , QCD_HT1500to2000x , MC , 1 , 10000 , splitting='FileBased' , priority=80 , label='signal' ) , # dataset( "QCD_HT2000toInfx" , QCD_HT2000toInfx , MC , 1 , 10000 , splitting='FileBased' , priority=70 , label='signal' ) , ] import os crabTaskDir = 'crabTasks' if not os.path.exists(crabTaskDir): os.makedirs(crabTaskDir)
# dataset( "QCD_HT1000to1500" , QCD_HT1000to1500 , MC , 1 , 10000 , splitting='FileBased' , priority=90 , label='signal' ) , # dataset( "QCD_HT1500to2000" , QCD_HT1500to2000 , MC , 1 , 10000 , splitting='FileBased' , priority=80 , label='signal' ) , # dataset( "QCD_HT2000toInf" , QCD_HT2000toInf , MC , 1 , 10000 , splitting='FileBased' , priority=99 , label='signal' ) , # dataset( "WJet" , WJet , MC , 1 , 10000 , splitting='FileBased' , priority=70 , label='wjet' ) , # dataset( "QCD_HT700to1000x" , QCD_HT700to1000x , MC , 2 , 10000 , splitting='FileBased' , priority=80 , label='signal' ) , # dataset( "QCD_HT1000to1500x" , QCD_HT1000to1500x , MC , 1 , 10000 , splitting='FileBased' , priority=90 , label='signal' ) , # dataset( "QCD_HT1500to2000x" , QCD_HT1500to2000x , MC , 1 , 10000 , splitting='FileBased' , priority=80 , label='signal' ) , # dataset( "QCD_HT2000toInfx" , QCD_HT2000toInfx , MC , 1 , 10000 , splitting='FileBased' , priority=70 , label='signal' ) , # JetHT data # dataset( "JetHT_B1" , JetHT_B1 , DATA , 20 , 100000000 , splitting='LumiBased' , priority=199 , label='signal' , doHLT=1 ) , # dataset( "JetHT_B3" , JetHT_B3 , DATA , 20 , 100000000 , splitting='LumiBased' , priority=199 , label='signal' , doHLT=1 ) , # dataset( "JetHT_C1" , JetHT_C1 , DATA , 20 , 100000000 , splitting='LumiBased' , priority=199 , label='signal' , doHLT=1 ) , # dataset( "JetHT_D1" , JetHT_D1 , DATA , 20 , 100000000 , splitting='LumiBased' , priority=199 , label='signal' , doHLT=1 ) , # dataset( "JetHT_E1" , JetHT_E1 , DATA , 20 , 100000000 , splitting='LumiBased' , priority=199 , label='signal' , doHLT=1 ) , # dataset( "JetHT_F1" , JetHT_F1 , DATA , 20 , 100000000 , splitting='LumiBased' , priority=199 , label='signal' , doHLT=1 ) , dataset( "JetHT_G1" , JetHT_G1 , DATA , 20 , 100000000 , splitting='LumiBased' , priority=199 , label='signal' , doHLT=1 ) , # dataset( "JetHT_H1" , JetHT_H1 , DATA , 20 , 100000000 , splitting='LumiBased' , priority=199 , label='signal' , doHLT=1 ) , # No jobs generated with json file dataset( "JetHT_H2" , JetHT_H2 , DATA , 10 , 100000000 , splitting='LumiBased' , priority=199 , label='signal' , doHLT=1 ) , dataset( "JetHT_H3" , JetHT_H3 , DATA , 10 , 100000000 , splitting='LumiBased' , priority=199 , label='signal' , doHLT=1 ) , # dataset( "JetHT_H3-testing" , JetHT_H3 , DATA , 10 , 10 , splitting='LumiBased' , priority=199 , label='signal' , doHLT=1 ) , # For trigger testing # dataset( "HLT_QCD_HT300to500" , QCD_HT300to500 , MC , 1 , 100 , splitting='FileBased' , priority=199 , label='signal' , doHLT=0 ) , # dataset( "HLT_QCD_HT500to700" , QCD_HT500to700 , MC , 1 , 100 , splitting='FileBased' , priority=199 , label='signal' , doHLT=0 ) , # dataset( "HLT_QCD_HT700to1000" , QCD_HT700to1000 , MC , 1 , 100 , splitting='FileBased' , priority=199 , label='signal' , doHLT=0 ) , # dataset( "HLT_QCD_HT1000to1500" , QCD_HT1000to1500 , MC , 1 , 100 , splitting='FileBased' , priority=199 , label='signal' , doHLT=0 ) , # dataset( "HLT_QCD_HT1500to2000" , QCD_HT1500to2000 , MC , 1 , 100 , splitting='FileBased' , priority=199 , label='signal' , doHLT=0 ) , # dataset( "HLT_QCD_HT2000toInf" , QCD_HT2000toInf , MC , 1 , 100 , splitting='FileBased' , priority=199 , label='signal' , doHLT=0 ) , ] template = dataset( "ALIAS" , "/FULL/PATH-TO/DATSET" , MC , 1 , 1000000 , splitting='FileBased' , priority=99 , inputDBS='phys03' , label='signal' , doHLT=0 ) dataset_list = load_datasets('crabUtils/dataset_lists/list_RunIISummer16DR80Premix_private-AODSIM-v2017-09-11-longlifetime.txt', template)
datasets = [ # dataset( "ModelA" , "/EmergingJets_ModelA_TuneCUETP8M1_13TeV_pythia8Mod/yoshin-AODSIM-69070e02f00a6fbca8a74a9d93177037/USER" , MC , 1 , 10000000 , splitting='FileBased' , priority=99 , label='signal' , inputDBS='phys03' , doHLT=0 ) , # dataset( "ModelB" , "/EmergingJets_ModelB_TuneCUETP8M1_13TeV_pythia8Mod/yoshin-AODSIM-69070e02f00a6fbca8a74a9d93177037/USER" , MC , 1 , 10000000 , splitting='FileBased' , priority=99 , label='signal' , inputDBS='phys03' , doHLT=0 ) , # dataset( "QCD_HT500to700" , "/QCD_HT500to700_TuneCUETP8M1_13TeV-madgraphMLM-pythia8/RunIISpring15DR74-Asympt25ns_MCRUN2_74_V9-v1/AODSIM" , MC , 10 , 10000 , splitting='FileBased' , priority=10 , label='signal' ) , # dataset( "QCD_HT700to1000" , "/QCD_HT700to1000_TuneCUETP8M1_13TeV-madgraphMLM-pythia8/RunIISpring15DR74-Asympt25ns_MCRUN2_74_V9-v1/AODSIM" , MC , 10 , 10000 , splitting='FileBased' , priority=15 , label='signal' ) , # dataset( "QCD_HT1000to1500" , "/QCD_HT1000to1500_TuneCUETP8M1_13TeV-madgraphMLM-pythia8/RunIISpring15DR74-Asympt25ns_MCRUN2_74_V9-v2/AODSIM" , MC , 10 , 10000 , splitting='FileBased' , priority=30 , label='signal' ) , # dataset( "QCD_HT1500to2000" , "/QCD_HT1500to2000_TuneCUETP8M1_13TeV-madgraphMLM-pythia8/RunIISpring15DR74-Asympt25ns_MCRUN2_74_V9-v1/AODSIM" , MC , 10 , 10000 , splitting='FileBased' , priority=28 , label='signal' ) , # dataset( "QCD_HT2000toInf" , "/QCD_HT2000toInf_TuneCUETP8M1_13TeV-madgraphMLM-pythia8/RunIISpring15DR74-Asympt25ns_MCRUN2_74_V9-v1/AODSIM" , MC , 10 , 10000 , splitting='FileBased' , priority=25 , label='signal' ) , # dataset( "WJetsToLNuInclusive" , "/WJetsToLNu_TuneCUETP8M1_13TeV-amcatnloFXFX-pythia8/RunIISpring15DR74-Asympt25ns_MCRUN2_74_V9-v1/AODSIM" , MC, 1, 1000, splitting='FileBased', priority=30, label='wjet' ), ] datasets = [ # # def __init__(self, alias, fullpath, isData, unitsPerJob=1, totalUnits=1, splitting='FileBased', priority=1, inputDBS='global', label='', doHLT=1, doJetFilter=0): # # dataset( "Dummy" , Dummy , MC , 1 , 10000 , splitting='FileBased' , priority=99 , label='signal' ) , dataset( "mass_X_d_1000_mass_pi_d_1_tau_pi_d_0p001" , mass_X_d_1000_mass_pi_d_1_tau_pi_d_0p001 , MC , 1 , 10000 , splitting='FileBased' , priority=99 , inputDBS='phys03' , label='signal' , doHLT=0 ) , dataset( "mass_X_d_1000_mass_pi_d_1_tau_pi_d_0p1" , mass_X_d_1000_mass_pi_d_1_tau_pi_d_0p1 , MC , 1 , 10000 , splitting='FileBased' , priority=99 , inputDBS='phys03' , label='signal' , doHLT=0 ) , dataset( "mass_X_d_1000_mass_pi_d_1_tau_pi_d_1" , mass_X_d_1000_mass_pi_d_1_tau_pi_d_1 , MC , 1 , 10000 , splitting='FileBased' , priority=99 , inputDBS='phys03' , label='signal' , doHLT=0 ) , dataset( "mass_X_d_1000_mass_pi_d_1_tau_pi_d_5" , mass_X_d_1000_mass_pi_d_1_tau_pi_d_5 , MC , 1 , 10000 , splitting='FileBased' , priority=99 , inputDBS='phys03' , label='signal' , doHLT=0 ) , dataset( "mass_X_d_1000_mass_pi_d_1_tau_pi_d_25" , mass_X_d_1000_mass_pi_d_1_tau_pi_d_25 , MC , 1 , 10000 , splitting='FileBased' , priority=99 , inputDBS='phys03' , label='signal' , doHLT=0 ) , dataset( "mass_X_d_1000_mass_pi_d_1_tau_pi_d_60" , mass_X_d_1000_mass_pi_d_1_tau_pi_d_60 , MC , 1 , 10000 , splitting='FileBased' , priority=99 , inputDBS='phys03' , label='signal' , doHLT=0 ) , dataset( "mass_X_d_1000_mass_pi_d_1_tau_pi_d_100" , mass_X_d_1000_mass_pi_d_1_tau_pi_d_100 , MC , 1 , 10000 , splitting='FileBased' , priority=99 , inputDBS='phys03' , label='signal' , doHLT=0 ) , dataset( "mass_X_d_1000_mass_pi_d_1_tau_pi_d_150" , mass_X_d_1000_mass_pi_d_1_tau_pi_d_150 , MC , 1 , 10000 , splitting='FileBased' , priority=99 , inputDBS='phys03' , label='signal' , doHLT=0 ) , dataset( "mass_X_d_1000_mass_pi_d_1_tau_pi_d_300" , mass_X_d_1000_mass_pi_d_1_tau_pi_d_300 , MC , 1 , 10000 , splitting='FileBased' , priority=99 , inputDBS='phys03' , label='signal' , doHLT=0 ) , dataset( "mass_X_d_1000_mass_pi_d_2_tau_pi_d_0p001" , mass_X_d_1000_mass_pi_d_2_tau_pi_d_0p001 , MC , 1 , 10000 , splitting='FileBased' , priority=99 , inputDBS='phys03' , label='signal' , doHLT=0 ) , dataset( "mass_X_d_1000_mass_pi_d_2_tau_pi_d_0p1" , mass_X_d_1000_mass_pi_d_2_tau_pi_d_0p1 , MC , 1 , 10000 , splitting='FileBased' , priority=99 , inputDBS='phys03' , label='signal' , doHLT=0 ) , dataset( "mass_X_d_1000_mass_pi_d_2_tau_pi_d_1" , mass_X_d_1000_mass_pi_d_2_tau_pi_d_1 , MC , 1 , 10000 , splitting='FileBased' , priority=99 , inputDBS='phys03' , label='signal' , doHLT=0 ) , dataset( "mass_X_d_1000_mass_pi_d_2_tau_pi_d_5" , mass_X_d_1000_mass_pi_d_2_tau_pi_d_5 , MC , 1 , 10000 , splitting='FileBased' , priority=99 , inputDBS='phys03' , label='signal' , doHLT=0 ) , dataset( "mass_X_d_1000_mass_pi_d_2_tau_pi_d_25" , mass_X_d_1000_mass_pi_d_2_tau_pi_d_25 , MC , 1 , 10000 , splitting='FileBased' , priority=99 , inputDBS='phys03' , label='signal' , doHLT=0 ) , dataset( "mass_X_d_1000_mass_pi_d_2_tau_pi_d_60" , mass_X_d_1000_mass_pi_d_2_tau_pi_d_60 , MC , 1 , 10000 , splitting='FileBased' , priority=99 , inputDBS='phys03' , label='signal' , doHLT=0 ) , dataset( "mass_X_d_1000_mass_pi_d_2_tau_pi_d_100" , mass_X_d_1000_mass_pi_d_2_tau_pi_d_100 , MC , 1 , 10000 , splitting='FileBased' , priority=99 , inputDBS='phys03' , label='signal' , doHLT=0 ) ,
"""MultiCRAB script template for EmergingJet analysis""" MC=0 DATA=1 jobname = 'Analysis-20160615' # Jobname psetname = 'Configuration/test/test_cfg.py' # Path to pset postfix = 'v0' # Postfix to job, increment for each major version dryrun = 0 from datasets import dataset from wrappers import submit, submit_newthread datasets = [ # dataset( "WJetsToLNuInclusive" , "/WJetsToLNu_TuneCUETP8M1_13TeV-amcatnloFXFX-pythia8/RunIISpring15DR74-Asympt25ns_MCRUN2_74_V9-v1/AODSIM" , MC, 1, 1000, splitting='FileBased', priority=30, label='wjet' ), # dataset( "Dummy" , "/WJetsToLNu_TuneCUETP8M1_13TeV-amcatnloFXFX-pythia8/RunIISpring15DR74-Asympt25ns_MCRUN2_74_V9-v1/AODSIM" , MC , 1 , 1 , splitting='FileBased' , priority=99 , label='wjet' ) , dataset( "ModelA" , "/EmergingJets_ModelA_TuneCUETP8M1_13TeV_pythia8Mod/yoshin-AODSIM-69070e02f00a6fbca8a74a9d93177037/USER" , MC , 1 , 10000000 , splitting='FileBased' , priority=99 , label='signal' , inputDBS='phys03' ) , dataset( "ModelB" , "/EmergingJets_ModelB_TuneCUETP8M1_13TeV_pythia8Mod/yoshin-AODSIM-69070e02f00a6fbca8a74a9d93177037/USER" , MC , 1 , 10000000 , splitting='FileBased' , priority=99 , label='signal' , inputDBS='phys03' ) , dataset( "QCD_HT500to700" , "/QCD_HT500to700_TuneCUETP8M1_13TeV-madgraphMLM-pythia8/RunIISpring15DR74-Asympt25ns_MCRUN2_74_V9-v1/AODSIM" , MC , 1 , 100 , splitting='FileBased' , priority=10 , label='signal' ) , dataset( "QCD_HT700to1000" , "/QCD_HT700to1000_TuneCUETP8M1_13TeV-madgraphMLM-pythia8/RunIISpring15DR74-Asympt25ns_MCRUN2_74_V9-v1/AODSIM" , MC , 1 , 1000 , splitting='FileBased' , priority=15 , label='signal' ) , dataset( "QCD_HT1000to1500" , "/QCD_HT1000to1500_TuneCUETP8M1_13TeV-madgraphMLM-pythia8/RunIISpring15DR74-Asympt25ns_MCRUN2_74_V9-v2/AODSIM" , MC , 1 , 100 , splitting='FileBased' , priority=30 , label='signal' ) , dataset( "QCD_HT1500to2000" , "/QCD_HT1500to2000_TuneCUETP8M1_13TeV-madgraphMLM-pythia8/RunIISpring15DR74-Asympt25ns_MCRUN2_74_V9-v1/AODSIM" , MC , 1 , 100 , splitting='FileBased' , priority=28 , label='signal' ) , dataset( "QCD_HT2000toInf" , "/QCD_HT2000toInf_TuneCUETP8M1_13TeV-madgraphMLM-pythia8/RunIISpring15DR74-Asympt25ns_MCRUN2_74_V9-v1/AODSIM" , MC , 1 , 100 , splitting='FileBased' , priority=25 , label='signal' ) , dataset( "QCD_HT500to700_76X" , "/QCD_HT500to700_TuneCUETP8M1_13TeV-madgraphMLM-pythia8/RunIIFall15DR76-PU25nsData2015v1_76X_mcRun2_asymptotic_v12-v1/AODSIM" , MC , 1 , 100 , splitting='FileBased' , priority=10 , label='signal' ) , dataset( "QCD_HT700to1000_76X" , "/QCD_HT700to1000_TuneCUETP8M1_13TeV-madgraphMLM-pythia8/RunIIFall15DR76-PU25nsData2015v1_76X_mcRun2_asymptotic_v12-v1/AODSIM" , MC , 1 , 1000 , splitting='FileBased' , priority=15 , label='signal' ) , dataset( "QCD_HT1000to1500_76X" , "/QCD_HT1000to1500_TuneCUETP8M1_13TeV-madgraphMLM-pythia8/RunIIFall15DR76-PU25nsData2015v1_76X_mcRun2_asymptotic_v12-v1/AODSIM" , MC , 1 , 100 , splitting='FileBased' , priority=30 , label='signal' ) , dataset( "QCD_HT1500to2000_76X" , "/QCD_HT1500to2000_TuneCUETP8M1_13TeV-madgraphMLM-pythia8/RunIIFall15DR76-PU25nsData2015v1_76X_mcRun2_asymptotic_v12-v1/AODSIM" , MC , 1 , 100 , splitting='FileBased' , priority=28 , label='signal' ) , dataset( "QCD_HT2000toInf_76X" , "/QCD_HT2000toInf_TuneCUETP8M1_13TeV-madgraphMLM-pythia8/RunIIFall15DR76-PU25nsData2015v1_76X_mcRun2_asymptotic_v12-v1/AODSIM" , MC , 1 , 100 , splitting='FileBased' , priority=25 , label='signal' ) , dataset( "DataSkim_Run2015-PRv3" , "/JetHT/yoshin-DataSkim-20160302-80c51f15cd036b2256e94c207509265d/USER" , DATA , 1000 , 20000 , splitting='EventAwareLumiBased' , priority=35 , label='signal' , inputDBS='phys03' ) , ] if __name__ == '__main__':
jobname = 'Analysis-20160601' # Jobname psetname = 'Configuration/test/test_cfg.py' # Path to pset postfix = 'v0' # Postfix to job, increment for each major version dryrun = 0 from datasets import dataset from wrappers import submit, submit_newthread datasets = [ # dataset( "WJetsToLNuInclusive" , "/WJetsToLNu_TuneCUETP8M1_13TeV-amcatnloFXFX-pythia8/RunIISpring15DR74-Asympt25ns_MCRUN2_74_V9-v1/AODSIM" , MC, 1, 1000, splitting='FileBased', priority=30, label='wjet' ), # dataset( "Dummy" , "/WJetsToLNu_TuneCUETP8M1_13TeV-amcatnloFXFX-pythia8/RunIISpring15DR74-Asympt25ns_MCRUN2_74_V9-v1/AODSIM" , MC , 1 , 1 , splitting='FileBased' , priority=99 , label='wjet' ) , dataset( "ModelA", "/EmergingJets_ModelA_TuneCUETP8M1_13TeV_pythia8Mod/yoshin-AODSIM-69070e02f00a6fbca8a74a9d93177037/USER", MC, 1, 10000000, splitting='FileBased', priority=99, label='signal', inputDBS='phys03'), dataset( "ModelB", "/EmergingJets_ModelB_TuneCUETP8M1_13TeV_pythia8Mod/yoshin-AODSIM-69070e02f00a6fbca8a74a9d93177037/USER", MC, 1, 10000000, splitting='FileBased', priority=99, label='signal', inputDBS='phys03'), dataset(
# dataset( "mass_pi_d_5_tau_pi_d_150" , mass_pi_d_5_tau_pi_d_150 , MC , 1 , 10000 , splitting='FileBased' , priority=99 , inputDBS='phys03' , label='signal' , doHLT=0 ) , # dataset( "mass_pi_d_5_tau_pi_d_300" , mass_pi_d_5_tau_pi_d_300 , MC , 1 , 10000 , splitting='FileBased' , priority=99 , inputDBS='phys03' , label='signal' , doHLT=0 ) , # dataset( "mass_pi_d_10_tau_pi_d_0p001" , mass_pi_d_10_tau_pi_d_0p001 , MC , 1 , 10000 , splitting='FileBased' , priority=99 , inputDBS='phys03' , label='signal' , doHLT=0 ) , # dataset( "mass_pi_d_10_tau_pi_d_0p1" , mass_pi_d_10_tau_pi_d_0p1 , MC , 1 , 10000 , splitting='FileBased' , priority=99 , inputDBS='phys03' , label='signal' , doHLT=0 ) , # dataset( "mass_pi_d_10_tau_pi_d_1" , mass_pi_d_10_tau_pi_d_1 , MC , 1 , 10000 , splitting='FileBased' , priority=99 , inputDBS='phys03' , label='signal' , doHLT=0 ) , # dataset( "mass_pi_d_10_tau_pi_d_5" , mass_pi_d_10_tau_pi_d_5 , MC , 1 , 10000 , splitting='FileBased' , priority=99 , inputDBS='phys03' , label='signal' , doHLT=0 ) , # dataset( "mass_pi_d_10_tau_pi_d_25" , mass_pi_d_10_tau_pi_d_25 , MC , 1 , 10000 , splitting='FileBased' , priority=99 , inputDBS='phys03' , label='signal' , doHLT=0 ) , # dataset( "mass_pi_d_10_tau_pi_d_60" , mass_pi_d_10_tau_pi_d_60 , MC , 1 , 10000 , splitting='FileBased' , priority=99 , inputDBS='phys03' , label='signal' , doHLT=0 ) , # dataset( "mass_pi_d_10_tau_pi_d_100" , mass_pi_d_10_tau_pi_d_100 , MC , 1 , 10000 , splitting='FileBased' , priority=99 , inputDBS='phys03' , label='signal' , doHLT=0 ) , # dataset( "mass_pi_d_10_tau_pi_d_150" , mass_pi_d_10_tau_pi_d_150 , MC , 1 , 10000 , splitting='FileBased' , priority=99 , inputDBS='phys03' , label='signal' , doHLT=0 ) , # dataset( "mass_pi_d_10_tau_pi_d_300" , mass_pi_d_10_tau_pi_d_300 , MC , 1 , 10000 , splitting='FileBased' , priority=99 , inputDBS='phys03' , label='signal' , doHLT=0 ) , dataset("ModelA", ModelA, MC, 1, 10000, splitting='FileBased', priority=99, inputDBS='phys03', label='signal', doHLT=0), dataset("ModelB", ModelB, MC, 1, 10000, splitting='FileBased', priority=99, inputDBS='phys03', label='signal', doHLT=0), dataset("QCD_HT50to100",
# dataset( "mass_pi_d_10_tau_pi_d_100" , mass_pi_d_10_tau_pi_d_100 , MC , 1 , 10000 , splitting='FileBased' , priority=99 , inputDBS='phys03' , label='signal' , doHLT=0 ) , # dataset( "mass_pi_d_10_tau_pi_d_150" , mass_pi_d_10_tau_pi_d_150 , MC , 1 , 10000 , splitting='FileBased' , priority=99 , inputDBS='phys03' , label='signal' , doHLT=0 ) , # dataset( "mass_pi_d_10_tau_pi_d_300" , mass_pi_d_10_tau_pi_d_300 , MC , 1 , 10000 , splitting='FileBased' , priority=99 , inputDBS='phys03' , label='signal' , doHLT=0 ) , # dataset( "QCD80_HT50to100" , QCD_HT50to100 , MC , 10 , 10000 , splitting='FileBased' , priority=10 , label='signal' ) , # dataset( "QCD80_HT100to200" , QCD_HT100to200 , MC , 10 , 10000 , splitting='FileBased' , priority=10 , label='signal' ) , # dataset( "QCD80_HT200to300" , QCD_HT200to300 , MC , 10 , 10000 , splitting='FileBased' , priority=10 , label='signal' ) , # dataset( "QCD80_HT300to500" , QCD_HT300to500 , MC , 10 , 10000 , splitting='FileBased' , priority=10 , label='signal' ) , # dataset( "QCD80_HT500to700" , QCD_HT500to700 , MC , 10 , 10000 , splitting='FileBased' , priority=10 , label='signal' ) , # dataset( "QCD80_HT700to1000" , QCD_HT700to1000 , MC , 10 , 10000 , splitting='FileBased' , priority=80 , label='signal' ) , # dataset( "QCD80_HT1000to1500" , QCD_HT1000to1500 , MC , 10 , 10000 , splitting='FileBased' , priority=90 , label='signal' ) , # dataset( "QCD80_HT1500to2000" , QCD_HT1500to2000 , MC , 10 , 10000 , splitting='FileBased' , priority=80 , label='signal' ) , # dataset( "QCD80_HT2000toInf" , QCD_HT2000toInf , MC , 5 , 10000 , splitting='FileBased' , priority=70 , label='signal' ) , dataset("WJet80", WJet, MC, 10, 10000, splitting='FileBased', priority=70, label='wjet'), ] import os crabTaskDir = 'crabTasks' if not os.path.exists(crabTaskDir): os.makedirs(crabTaskDir) if __name__ == '__main__': ############################################################ ## Common settings
# dataset( "mass_pi_d_5_tau_pi_d_5" , mass_pi_d_5_tau_pi_d_5 , MC , 1 , 10000 , splitting='FileBased' , priority=99 , inputDBS='phys03' , label='signal' , doHLT=0 ) , # dataset( "mass_pi_d_5_tau_pi_d_25" , mass_pi_d_5_tau_pi_d_25 , MC , 1 , 10000 , splitting='FileBased' , priority=99 , inputDBS='phys03' , label='signal' , doHLT=0 ) , # dataset( "mass_pi_d_5_tau_pi_d_60" , mass_pi_d_5_tau_pi_d_60 , MC , 1 , 10000 , splitting='FileBased' , priority=99 , inputDBS='phys03' , label='signal' , doHLT=0 ) , # dataset( "mass_pi_d_5_tau_pi_d_100" , mass_pi_d_5_tau_pi_d_100 , MC , 1 , 10000 , splitting='FileBased' , priority=99 , inputDBS='phys03' , label='signal' , doHLT=0 ) , # dataset( "mass_pi_d_5_tau_pi_d_150" , mass_pi_d_5_tau_pi_d_150 , MC , 1 , 10000 , splitting='FileBased' , priority=99 , inputDBS='phys03' , label='signal' , doHLT=0 ) , # dataset( "mass_pi_d_5_tau_pi_d_300" , mass_pi_d_5_tau_pi_d_300 , MC , 1 , 10000 , splitting='FileBased' , priority=99 , inputDBS='phys03' , label='signal' , doHLT=0 ) , # dataset( "mass_pi_d_10_tau_pi_d_0p001" , mass_pi_d_10_tau_pi_d_0p001 , MC , 1 , 10000 , splitting='FileBased' , priority=99 , inputDBS='phys03' , label='signal' , doHLT=0 ) , # dataset( "mass_pi_d_10_tau_pi_d_0p1" , mass_pi_d_10_tau_pi_d_0p1 , MC , 1 , 10000 , splitting='FileBased' , priority=99 , inputDBS='phys03' , label='signal' , doHLT=0 ) , # dataset( "mass_pi_d_10_tau_pi_d_1" , mass_pi_d_10_tau_pi_d_1 , MC , 1 , 10000 , splitting='FileBased' , priority=99 , inputDBS='phys03' , label='signal' , doHLT=0 ) , # dataset( "mass_pi_d_10_tau_pi_d_5" , mass_pi_d_10_tau_pi_d_5 , MC , 1 , 10000 , splitting='FileBased' , priority=99 , inputDBS='phys03' , label='signal' , doHLT=0 ) , # dataset( "mass_pi_d_10_tau_pi_d_25" , mass_pi_d_10_tau_pi_d_25 , MC , 1 , 10000 , splitting='FileBased' , priority=99 , inputDBS='phys03' , label='signal' , doHLT=0 ) , # dataset( "mass_pi_d_10_tau_pi_d_60" , mass_pi_d_10_tau_pi_d_60 , MC , 1 , 10000 , splitting='FileBased' , priority=99 , inputDBS='phys03' , label='signal' , doHLT=0 ) , # dataset( "mass_pi_d_10_tau_pi_d_100" , mass_pi_d_10_tau_pi_d_100 , MC , 1 , 10000 , splitting='FileBased' , priority=99 , inputDBS='phys03' , label='signal' , doHLT=0 ) , # dataset( "mass_pi_d_10_tau_pi_d_150" , mass_pi_d_10_tau_pi_d_150 , MC , 1 , 10000 , splitting='FileBased' , priority=99 , inputDBS='phys03' , label='signal' , doHLT=0 ) , # dataset( "mass_pi_d_10_tau_pi_d_300" , mass_pi_d_10_tau_pi_d_300 , MC , 1 , 10000 , splitting='FileBased' , priority=99 , inputDBS='phys03' , label='signal' , doHLT=0 ) , dataset( "ModelA" , ModelA , MC , 1 , 10000 , splitting='FileBased' , priority=99 , inputDBS='phys03' , label='signal' , doHLT=0 ) , dataset( "ModelB" , ModelB , MC , 1 , 10000 , splitting='FileBased' , priority=99 , inputDBS='phys03' , label='signal' , doHLT=0 ) , dataset( "QCD_HT50to100" , QCD_HT50to100 , MC , 10 , 10000 , splitting='FileBased' , priority=10 , label='signal' ) , dataset( "QCD_HT100to200" , QCD_HT100to200 , MC , 10 , 10000 , splitting='FileBased' , priority=10 , label='signal' ) , dataset( "QCD_HT200to300" , QCD_HT200to300 , MC , 10 , 10000 , splitting='FileBased' , priority=10 , label='signal' ) , dataset( "QCD_HT300to500" , QCD_HT300to500 , MC , 10 , 10000 , splitting='FileBased' , priority=10 , label='signal' ) , dataset( "QCD_HT500to700" , QCD_HT500to700 , MC , 10 , 10000 , splitting='FileBased' , priority=10 , label='signal' ) , dataset( "QCD_HT700to1000" , QCD_HT700to1000 , MC , 10 , 10000 , splitting='FileBased' , priority=80 , label='signal' ) , dataset( "QCD_HT1000to1500" , QCD_HT1000to1500 , MC , 10 , 10000 , splitting='FileBased' , priority=90 , label='signal' ) , dataset( "QCD_HT1500to2000" , QCD_HT1500to2000 , MC , 10 , 10000 , splitting='FileBased' , priority=80 , label='signal' ) , dataset( "QCD_HT2000toInf" , QCD_HT2000toInf , MC , 5 , 10000 , splitting='FileBased' , priority=70 , label='signal' ) , dataset( "WJet" , WJet , MC , 10 , 10000 , splitting='FileBased' , priority=70 , label='wjet' ) , ] import os crabTaskDir = 'crabTasks'
# dataset( "HLT_QCD_HT300to500" , QCD_HT300to500 , MC , 1 , 100 , splitting='FileBased' , priority=199 , label='signal' , doHLT=1 ) , # dataset( "HLT_QCD_HT500to700" , QCD_HT500to700 , MC , 1 , 100 , splitting='FileBased' , priority=199 , label='signal' , doHLT=1 ) , # dataset( "HLT_QCD_HT700to1000" , QCD_HT700to1000 , MC , 1 , 100 , splitting='FileBased' , priority=199 , label='signal' , doHLT=1 ) , # dataset( "HLT_QCD_HT1000to1500" , QCD_HT1000to1500 , MC , 1 , 100 , splitting='FileBased' , priority=199 , label='signal' , doHLT=1 ) , # dataset( "HLT_QCD_HT1500to2000" , QCD_HT1500to2000 , MC , 1 , 100 , splitting='FileBased' , priority=199 , label='signal' , doHLT=1 ) , # dataset( "HLT_QCD_HT2000toInf" , QCD_HT2000toInf , MC , 1 , 100 , splitting='FileBased' , priority=199 , label='signal' , doHLT=1 ) , # Data skim for trigger testing # dataset( "HLT_JetHT_G1" , JetHT_G1 , DATA , 1 , 1000 , splitting='LumiBased' , priority=199 , label='signal' , doHLT=1 ) , # dataset( "HLT_JetHT_H1" , JetHT_H1 , DATA , 1 , 1000 , splitting='LumiBased' , priority=199 , label='signal' , doHLT=1 ) , # No jobs generated with json file # dataset( "HLT_JetHT_H2" , JetHT_H2 , DATA , 1 , 1000 , splitting='LumiBased' , priority=199 , label='signal' , doHLT=1 ) , # dataset( "HLT_JetHT_H3" , JetHT_H3 , DATA , 1 , 1000 , splitting='LumiBased' , priority=199 , label='signal' , doHLT=1 ) , dataset("HLT_JetHT_G1_b", JetHT_G1, DATA, 5, 10000, splitting='LumiBased', priority=199, label='signal', doHLT=1), dataset("HLT_JetHT_H1_b", JetHT_H1, DATA, 5, 10000, splitting='LumiBased', priority=199, label='signal', doHLT=1), # No jobs generated with json file dataset("HLT_JetHT_H2_b", JetHT_H2,
# dataset( "JetHT_F1" , JetHT_F1 , DATA , 20 , 100000000 , splitting='LumiBased' , priority=199 , label='signal' , doHLT=1 ) , # dataset( "JetHT_G1" , JetHT_G1 , DATA , 20 , 100000000 , splitting='LumiBased' , priority=199 , label='signal' , doHLT=1 ) , # dataset( "JetHT_H1" , JetHT_H1 , DATA , 20 , 100000000 , splitting='LumiBased' , priority=199 , label='signal' , doHLT=1 ) , # No jobs generated with json file # dataset( "JetHT_H2" , JetHT_H2 , DATA , 10 , 100000000 , splitting='LumiBased' , priority=199 , label='signal' , doHLT=1 ) , # dataset( "JetHT_H3" , JetHT_H3 , DATA , 10 , 100000000 , splitting='LumiBased' , priority=199 , label='signal' , doHLT=1 ) , # dataset( "JetHT_H3-testing" , JetHT_H3 , DATA , 10 , 10 , splitting='LumiBased' , priority=199 , label='signal' , doHLT=1 ) , # For trigger testing # dataset( "HLT_QCD_HT300to500" , QCD_HT300to500 , MC , 1 , 100 , splitting='FileBased' , priority=199 , label='signal' , doHLT=0 ) , # dataset( "HLT_QCD_HT500to700" , QCD_HT500to700 , MC , 1 , 100 , splitting='FileBased' , priority=199 , label='signal' , doHLT=0 ) , # dataset( "HLT_QCD_HT700to1000" , QCD_HT700to1000 , MC , 1 , 100 , splitting='FileBased' , priority=199 , label='signal' , doHLT=0 ) , # dataset( "HLT_QCD_HT1000to1500" , QCD_HT1000to1500 , MC , 1 , 100 , splitting='FileBased' , priority=199 , label='signal' , doHLT=0 ) , # dataset( "HLT_QCD_HT1500to2000" , QCD_HT1500to2000 , MC , 1 , 100 , splitting='FileBased' , priority=199 , label='signal' , doHLT=0 ) , # dataset( "HLT_QCD_HT2000toInf" , QCD_HT2000toInf , MC , 1 , 100 , splitting='FileBased' , priority=199 , label='signal' , doHLT=0 ) , ] template = dataset( "ALIAS" , "/FULL/PATH-TO/DATSET" , MC , 1 , 10000 , splitting='FileBased' , priority=99 , inputDBS='phys03' , label='signal' , doHLT=0 ) dataset_list = load_datasets('crabUtils/dataset_lists/list_RunIISummer16DR80Premix_private-AODSIM-v2017-09-11re.txt', template) print 'dataset_list' for i in dataset_list: print i.alias, i.fullpath datasets = dataset_list import os crabTaskDir = 'crabTasks' if not os.path.exists(crabTaskDir): os.makedirs(crabTaskDir) if __name__ == '__main__': ############################################################
jobname = 'Analysis-20161012' # Jobname psetname = 'Configuration/test/test_cfg.py' # Path to pset postfix = 'v0' # Postfix to job, increment for each major version dryrun = 0 from datasets import dataset from wrappers import submit, submit_newthread datasets = [ # dataset( "WJetsToLNuInclusive" , "/WJetsToLNu_TuneCUETP8M1_13TeV-amcatnloFXFX-pythia8/RunIISpring15DR74-Asympt25ns_MCRUN2_74_V9-v1/AODSIM" , MC, 1, 1000, splitting='FileBased', priority=30, label='wjet' ), # dataset( "Dummy" , "/WJetsToLNu_TuneCUETP8M1_13TeV-amcatnloFXFX-pythia8/RunIISpring15DR74-Asympt25ns_MCRUN2_74_V9-v1/AODSIM" , MC , 1 , 1 , splitting='FileBased' , priority=99 , label='wjet' ) , dataset( "ModelA", "/EmergingJets_ModelA_TuneCUETP8M1_13TeV_pythia8Mod/yoshin-AODSIM-69070e02f00a6fbca8a74a9d93177037/USER", MC, 1, 10000000, splitting='FileBased', priority=99, label='signal', inputDBS='phys03'), dataset( "ModelB", "/EmergingJets_ModelB_TuneCUETP8M1_13TeV_pythia8Mod/yoshin-AODSIM-69070e02f00a6fbca8a74a9d93177037/USER", MC, 1, 10000000, splitting='FileBased', priority=99, label='signal', inputDBS='phys03'), # dataset( "QCD_HT500to700" , "/QCD_HT500to700_TuneCUETP8M1_13TeV-madgraphMLM-pythia8/RunIISpring15DR74-Asympt25ns_MCRUN2_74_V9-v1/AODSIM" , MC , 1 , 100 , splitting='FileBased' , priority=10 , label='signal' ) ,
# dataset( "test-HLT_QCD_HT50to100" , QCD_HT50to100 , MC , 1 , 1 , splitting='FileBased' , priority=199 , label='signal' , doHLT=1 ) , # dataset( "HLT_QCD_HT50to100" , QCD_HT50to100 , MC , 1 , 100 , splitting='FileBased' , priority=199 , label='signal' , doHLT=1 ) , # dataset( "HLT_QCD_HT100to200" , QCD_HT100to200 , MC , 1 , 100 , splitting='FileBased' , priority=199 , label='signal' , doHLT=1 ) , # dataset( "HLT_QCD_HT200to300" , QCD_HT200to300 , MC , 1 , 100 , splitting='FileBased' , priority=199 , label='signal' , doHLT=1 ) , # dataset( "HLT_QCD_HT300to500" , QCD_HT300to500 , MC , 1 , 100 , splitting='FileBased' , priority=199 , label='signal' , doHLT=1 ) , # dataset( "HLT_QCD_HT500to700" , QCD_HT500to700 , MC , 1 , 100 , splitting='FileBased' , priority=199 , label='signal' , doHLT=1 ) , # dataset( "HLT_QCD_HT700to1000" , QCD_HT700to1000 , MC , 1 , 100 , splitting='FileBased' , priority=199 , label='signal' , doHLT=1 ) , # dataset( "HLT_QCD_HT1000to1500" , QCD_HT1000to1500 , MC , 1 , 100 , splitting='FileBased' , priority=199 , label='signal' , doHLT=1 ) , # dataset( "HLT_QCD_HT1500to2000" , QCD_HT1500to2000 , MC , 1 , 100 , splitting='FileBased' , priority=199 , label='signal' , doHLT=1 ) , # dataset( "HLT_QCD_HT2000toInf" , QCD_HT2000toInf , MC , 1 , 100 , splitting='FileBased' , priority=199 , label='signal' , doHLT=1 ) , # Data skim for trigger testing # dataset( "HLT_JetHT_G1" , JetHT_G1 , DATA , 1 , 1000 , splitting='LumiBased' , priority=199 , label='signal' , doHLT=1 ) , # dataset( "HLT_JetHT_H1" , JetHT_H1 , DATA , 1 , 1000 , splitting='LumiBased' , priority=199 , label='signal' , doHLT=1 ) , # No jobs generated with json file # dataset( "HLT_JetHT_H2" , JetHT_H2 , DATA , 1 , 1000 , splitting='LumiBased' , priority=199 , label='signal' , doHLT=1 ) , # dataset( "HLT_JetHT_H3" , JetHT_H3 , DATA , 1 , 1000 , splitting='LumiBased' , priority=199 , label='signal' , doHLT=1 ) , dataset( "HLT_SingleMuon_G1" , SingleMuon_G1 , DATA , 20 , 300000 , splitting='LumiBased' , priority=199 , label='signal' , doHLT=1 ) , dataset( "HLT_SingleMuon_H1" , SingleMuon_H1 , DATA , 20 , 300000 , splitting='LumiBased' , priority=199 , label='signal' , doHLT=1 ) , # No jobs generated with json file dataset( "HLT_SingleMuon_H2" , SingleMuon_H2 , DATA , 20 , 300000 , splitting='LumiBased' , priority=199 , label='signal' , doHLT=1 ) , dataset( "HLT_SingleMuon_H3" , SingleMuon_H3 , DATA , 20 , 300000 , splitting='LumiBased' , priority=199 , label='signal' , doHLT=1 ) , ] import os crabTaskDir = 'crabTasks' if not os.path.exists(crabTaskDir): os.makedirs(crabTaskDir) if __name__ == '__main__': ############################################################ ## Common settings ############################################################
# dataset( "mass_pi_d_10_tau_pi_d_5" , mass_pi_d_10_tau_pi_d_5 , MC , 1 , 10000 , splitting='FileBased' , priority=99 , inputDBS='phys03' , label='signal' , doHLT=0 ) , # dataset( "mass_pi_d_10_tau_pi_d_25" , mass_pi_d_10_tau_pi_d_25 , MC , 1 , 10000 , splitting='FileBased' , priority=99 , inputDBS='phys03' , label='signal' , doHLT=0 ) , # dataset( "mass_pi_d_10_tau_pi_d_60" , mass_pi_d_10_tau_pi_d_60 , MC , 1 , 10000 , splitting='FileBased' , priority=99 , inputDBS='phys03' , label='signal' , doHLT=0 ) , # dataset( "mass_pi_d_10_tau_pi_d_100" , mass_pi_d_10_tau_pi_d_100 , MC , 1 , 10000 , splitting='FileBased' , priority=99 , inputDBS='phys03' , label='signal' , doHLT=0 ) , # dataset( "mass_pi_d_10_tau_pi_d_150" , mass_pi_d_10_tau_pi_d_150 , MC , 1 , 10000 , splitting='FileBased' , priority=99 , inputDBS='phys03' , label='signal' , doHLT=0 ) , # dataset( "mass_pi_d_10_tau_pi_d_300" , mass_pi_d_10_tau_pi_d_300 , MC , 1 , 10000 , splitting='FileBased' , priority=99 , inputDBS='phys03' , label='signal' , doHLT=0 ) , # dataset( "QCD80_HT50to100" , QCD_HT50to100 , MC , 10 , 10000 , splitting='FileBased' , priority=10 , label='signal' ) , # dataset( "QCD80_HT100to200" , QCD_HT100to200 , MC , 10 , 10000 , splitting='FileBased' , priority=10 , label='signal' ) , # dataset( "QCD80_HT200to300" , QCD_HT200to300 , MC , 10 , 10000 , splitting='FileBased' , priority=10 , label='signal' ) , # dataset( "QCD80_HT300to500" , QCD_HT300to500 , MC , 10 , 10000 , splitting='FileBased' , priority=10 , label='signal' ) , # dataset( "QCD80_HT500to700" , QCD_HT500to700 , MC , 10 , 10000 , splitting='FileBased' , priority=10 , label='signal' ) , # dataset( "QCD80_HT700to1000" , QCD_HT700to1000 , MC , 10 , 10000 , splitting='FileBased' , priority=80 , label='signal' ) , # dataset( "QCD80_HT1000to1500" , QCD_HT1000to1500 , MC , 10 , 10000 , splitting='FileBased' , priority=90 , label='signal' ) , # dataset( "QCD80_HT1500to2000" , QCD_HT1500to2000 , MC , 10 , 10000 , splitting='FileBased' , priority=80 , label='signal' ) , # dataset( "QCD80_HT2000toInf" , QCD_HT2000toInf , MC , 5 , 10000 , splitting='FileBased' , priority=70 , label='signal' ) , dataset( "WJet80" , WJet , MC , 10 , 10000 , splitting='FileBased' , priority=70 , label='wjet' ) , ] import os crabTaskDir = 'crabTasks' if not os.path.exists(crabTaskDir): os.makedirs(crabTaskDir) if __name__ == '__main__': ############################################################ ## Common settings ############################################################ from WMCore.Configuration import Configuration import time config = Configuration()
def train(n_epochs, learning_rate, batch_size, data_root, verbose): ds, label_names, all_image_paths = dataset(data_root, batch_size, verbose=verbose) # print(f"{ds}, {label_names}, {all_image_paths}") # mobile_net.trainable=False keras_ds = ds.map(change_range) print(f" {keras_ds}") image_batch, label_batch = next(iter(keras_ds)) model = mobile_net(label_names, pic_size=96) # mobile_net = tf.keras.applications.MobileNetV2(input_shape=(224, 224, 3), include_top=False) # # if verbose: # # feature_map_batch = mobile_net(image_batch) # # print(feature_map_batch.shape) # model = tf.keras.Sequential([ # mobile_net, # tf.keras.layers.GlobalAveragePooling2D(), # tf.keras.layers.Dense(len(label_names))]) logit_batch = model(image_batch).numpy() if verbose: print(f"min logit: {logit_batch.min()} ") print(f"max logit: {logit_batch.max()} ") print() print(f"Shape: {logit_batch.shape}") model.compile(optimizer=tf.train.AdamOptimizer(), loss=tf.keras.losses.binary_crossentropy, metrics=["accuracy"]) if verbose: print(f"Trainable variables: {len(model.trainable_variables)}") model.summary() steps_per_epoch = tf.ceil(len(all_image_paths) / batch_size).numpy() model.fit(ds, epochs=n_epochs, steps_per_epoch=int(steps_per_epoch)) def timeit(ds, batches=2 * steps_per_epoch + 1): overall_start = time.time() # Fetch a single batch to prime the pipeline (fill the shuffle buffer), # before starting the timer it = iter(ds.take(batches + 1)) next(it) start = time.time() for i, (images, labels) in enumerate(it): if i % 10 == 0: print('.', end='') print() end = time.time() duration = end - start print("{} batches: {} s".format(batches, duration)) print("{:0.5f} Images/s".format(batch_size * batches / duration)) print("Total time: {}s".format(end - overall_start)) if verbose: timeit(ds)
"""MultiCRAB script template for EmergingJet analysis""" MC=0 DATA=1 jobname = 'DataSkim-20160301' # Jobname psetname = 'test_cfg.py' # Path to pset postfix = 'v0' # Postfix to job, increment for each major version dryrun = False from datasets import dataset from wrappers import submit, submit_newthread datasets = [ dataset( "Run2015D" , "/JetHT/Run2015D-PromptReco-v3/AOD" , DATA, 100000, 80000000, splitting='EventAwareLumiBased', priority=10, label='signal' ), ] if __name__ == '__main__': ############################################################ ## Common settings ############################################################ from WMCore.Configuration import Configuration import time config = Configuration() config.section_("General") config.General.workArea = 'crab_' + jobname + time.strftime("-%Y-%m%d") + '-' + postfix tasklistFileName = config.General.workArea + '.txt' if not dryrun: tasklistFile = open(tasklistFileName, 'a') config.section_("JobType") config.JobType.pluginName = 'Analysis'
"""MultiCRAB script template for EmergingJet analysis""" MC=0 DATA=1 jobname = 'Analysis-20161012' # Jobname psetname = 'Configuration/test/test_cfg.py' # Path to pset postfix = 'v0' # Postfix to job, increment for each major version dryrun = 0 from datasets import dataset from wrappers import submit, submit_newthread datasets = [ # dataset( "WJetsToLNuInclusive" , "/WJetsToLNu_TuneCUETP8M1_13TeV-amcatnloFXFX-pythia8/RunIISpring15DR74-Asympt25ns_MCRUN2_74_V9-v1/AODSIM" , MC, 1, 1000, splitting='FileBased', priority=30, label='wjet' ), # dataset( "Dummy" , "/WJetsToLNu_TuneCUETP8M1_13TeV-amcatnloFXFX-pythia8/RunIISpring15DR74-Asympt25ns_MCRUN2_74_V9-v1/AODSIM" , MC , 1 , 1 , splitting='FileBased' , priority=99 , label='wjet' ) , dataset( "ModelA" , "/EmergingJets_ModelA_TuneCUETP8M1_13TeV_pythia8Mod/yoshin-AODSIM-69070e02f00a6fbca8a74a9d93177037/USER" , MC , 1 , 10000000 , splitting='FileBased' , priority=99 , label='signal' , inputDBS='phys03' ) , dataset( "ModelB" , "/EmergingJets_ModelB_TuneCUETP8M1_13TeV_pythia8Mod/yoshin-AODSIM-69070e02f00a6fbca8a74a9d93177037/USER" , MC , 1 , 10000000 , splitting='FileBased' , priority=99 , label='signal' , inputDBS='phys03' ) , # dataset( "QCD_HT500to700" , "/QCD_HT500to700_TuneCUETP8M1_13TeV-madgraphMLM-pythia8/RunIISpring15DR74-Asympt25ns_MCRUN2_74_V9-v1/AODSIM" , MC , 1 , 100 , splitting='FileBased' , priority=10 , label='signal' ) , # dataset( "QCD_HT700to1000" , "/QCD_HT700to1000_TuneCUETP8M1_13TeV-madgraphMLM-pythia8/RunIISpring15DR74-Asympt25ns_MCRUN2_74_V9-v1/AODSIM" , MC , 1 , 1000 , splitting='FileBased' , priority=15 , label='signal' ) , # dataset( "QCD_HT1000to1500" , "/QCD_HT1000to1500_TuneCUETP8M1_13TeV-madgraphMLM-pythia8/RunIISpring15DR74-Asympt25ns_MCRUN2_74_V9-v2/AODSIM" , MC , 1 , 100 , splitting='FileBased' , priority=30 , label='signal' ) , # dataset( "QCD_HT1500to2000" , "/QCD_HT1500to2000_TuneCUETP8M1_13TeV-madgraphMLM-pythia8/RunIISpring15DR74-Asympt25ns_MCRUN2_74_V9-v1/AODSIM" , MC , 1 , 100 , splitting='FileBased' , priority=28 , label='signal' ) , # dataset( "QCD_HT2000toInf" , "/QCD_HT2000toInf_TuneCUETP8M1_13TeV-madgraphMLM-pythia8/RunIISpring15DR74-Asympt25ns_MCRUN2_74_V9-v1/AODSIM" , MC , 1 , 100 , splitting='FileBased' , priority=25 , label='signal' ) , # dataset( "QCD_HT500to700_76X" , "/QCD_HT500to700_TuneCUETP8M1_13TeV-madgraphMLM-pythia8/RunIIFall15DR76-PU25nsData2015v1_76X_mcRun2_asymptotic_v12-v1/AODSIM" , MC , 1 , 100 , splitting='FileBased' , priority=10 , label='signal' ) , # dataset( "QCD_HT700to1000_76X" , "/QCD_HT700to1000_TuneCUETP8M1_13TeV-madgraphMLM-pythia8/RunIIFall15DR76-PU25nsData2015v1_76X_mcRun2_asymptotic_v12-v1/AODSIM" , MC , 1 , 1000 , splitting='FileBased' , priority=15 , label='signal' ) , # dataset( "QCD_HT1000to1500_76X" , "/QCD_HT1000to1500_TuneCUETP8M1_13TeV-madgraphMLM-pythia8/RunIIFall15DR76-PU25nsData2015v1_76X_mcRun2_asymptotic_v12-v1/AODSIM" , MC , 1 , 100 , splitting='FileBased' , priority=30 , label='signal' ) , # dataset( "QCD_HT1500to2000_76X" , "/QCD_HT1500to2000_TuneCUETP8M1_13TeV-madgraphMLM-pythia8/RunIIFall15DR76-PU25nsData2015v1_76X_mcRun2_asymptotic_v12-v1/AODSIM" , MC , 1 , 100 , splitting='FileBased' , priority=28 , label='signal' ) , # dataset( "QCD_HT2000toInf_76X" , "/QCD_HT2000toInf_TuneCUETP8M1_13TeV-madgraphMLM-pythia8/RunIIFall15DR76-PU25nsData2015v1_76X_mcRun2_asymptotic_v12-v1/AODSIM" , MC , 1 , 100 , splitting='FileBased' , priority=25 , label='signal' ) , # dataset( "DataSkim_Run2015-PRv3" , "/JetHT/yoshin-DataSkim-20160302-80c51f15cd036b2256e94c207509265d/USER" , DATA , 1000 , 20000 , splitting='EventAwareLumiBased' , priority=35 , label='signal' , inputDBS='phys03' ) , ] if __name__ == '__main__':
# dataset( "mass_pi_d_10_tau_pi_d_25" , mass_pi_d_10_tau_pi_d_25 , MC , 1 , 10000 , splitting='FileBased' , priority=99 , inputDBS='phys03' , label='signal' , doHLT=0 ) , # dataset( "mass_pi_d_10_tau_pi_d_60" , mass_pi_d_10_tau_pi_d_60 , MC , 1 , 10000 , splitting='FileBased' , priority=99 , inputDBS='phys03' , label='signal' , doHLT=0 ) , # dataset( "mass_pi_d_10_tau_pi_d_100" , mass_pi_d_10_tau_pi_d_100 , MC , 1 , 10000 , splitting='FileBased' , priority=99 , inputDBS='phys03' , label='signal' , doHLT=0 ) , # dataset( "mass_pi_d_10_tau_pi_d_150" , mass_pi_d_10_tau_pi_d_150 , MC , 1 , 10000 , splitting='FileBased' , priority=99 , inputDBS='phys03' , label='signal' , doHLT=0 ) , # dataset( "mass_pi_d_10_tau_pi_d_300" , mass_pi_d_10_tau_pi_d_300 , MC , 1 , 10000 , splitting='FileBased' , priority=99 , inputDBS='phys03' , label='signal' , doHLT=0 ) , # dataset( "ModelA" , ModelA , MC , 1 , 10000 , splitting='FileBased' , priority=99 , inputDBS='phys03' , label='signal' , doHLT=0 ) , # dataset( "ModelB" , ModelB , MC , 1 , 10000 , splitting='FileBased' , priority=99 , inputDBS='phys03' , label='signal' , doHLT=0 ) , # dataset( "QCD_HT50to100" , QCD_HT50to100 , MC , 10 , 10000 , splitting='FileBased' , priority=10 , label='signal' ) , # dataset( "QCD_HT100to200" , QCD_HT100to200 , MC , 10 , 10000 , splitting='FileBased' , priority=10 , label='signal' ) , # dataset( "QCD_HT200to300" , QCD_HT200to300 , MC , 10 , 10000 , splitting='FileBased' , priority=10 , label='signal' ) , # dataset( "QCD_HT300to500" , QCD_HT300to500 , MC , 10 , 10000 , splitting='FileBased' , priority=10 , label='signal' ) , # dataset( "QCD_HT500to700" , QCD_HT500to700 , MC , 2 , 10000 , splitting='FileBased' , priority=10 , label='signal' ) , # dataset( "QCD_HT700to1000" , QCD_HT700to1000 , MC , 2 , 10000 , splitting='FileBased' , priority=80 , label='signal' ) , # dataset( "QCD_HT1000to1500" , QCD_HT1000to1500 , MC , 1 , 10000 , splitting='FileBased' , priority=90 , label='signal' ) , # dataset( "QCD_HT1500to2000" , QCD_HT1500to2000 , MC , 1 , 10000 , splitting='FileBased' , priority=80 , label='signal' ) , dataset( "QCD_HT2000toInf" , QCD_HT2000toInf , MC , 1 , 10000 , splitting='FileBased' , priority=99 , label='signal' ) , # dataset( "WJet" , WJet , MC , 1 , 10000 , splitting='FileBased' , priority=70 , label='wjet' ) , # dataset( "QCD_HT700to1000x" , QCD_HT700to1000x , MC , 2 , 10000 , splitting='FileBased' , priority=80 , label='signal' ) , # dataset( "QCD_HT1000to1500x" , QCD_HT1000to1500x , MC , 1 , 10000 , splitting='FileBased' , priority=90 , label='signal' ) , # dataset( "QCD_HT1500to2000x" , QCD_HT1500to2000x , MC , 1 , 10000 , splitting='FileBased' , priority=80 , label='signal' ) , # dataset( "QCD_HT2000toInfx" , QCD_HT2000toInfx , MC , 1 , 10000 , splitting='FileBased' , priority=70 , label='signal' ) , ] import os crabTaskDir = 'crabTasks' if not os.path.exists(crabTaskDir): os.makedirs(crabTaskDir) if __name__ == '__main__': ############################################################
postfix = 'v0' # Postfix to job, increment for each major version dryrun = 0 from datasets import dataset from wrappers import submit, submit_newthread datasets = [ # dataset( "WJetsToLNuInclusive" , "/WJetsToLNu_TuneCUETP8M1_13TeV-amcatnloFXFX-pythia8/RunIISpring15DR74-Asympt25ns_MCRUN2_74_V9-v1/AODSIM" , MC, 1, 1000, splitting='FileBased', priority=30, label='wjet' ), # dataset( "Dummy" , "/WJetsToLNu_TuneCUETP8M1_13TeV-amcatnloFXFX-pythia8/RunIISpring15DR74-Asympt25ns_MCRUN2_74_V9-v1/AODSIM" , MC , 1 , 1 , splitting='FileBased' , priority=99 , label='wjet' ) , # dataset( "ModelA" , "/EmergingJets_ModelA_TuneCUETP8M1_13TeV_pythia8Mod/yoshin-AODSIM-69070e02f00a6fbca8a74a9d93177037/USER" , MC , 1 , 10000000 , splitting='FileBased' , priority=99 , label='signal', inputDBS='phys03' ) , # dataset( "ModelB" , "/EmergingJets_ModelB_TuneCUETP8M1_13TeV_pythia8Mod/yoshin-AODSIM-69070e02f00a6fbca8a74a9d93177037/USER" , MC , 1 , 10000000 , splitting='FileBased' , priority=99 , label='signal', inputDBS='phys03' ) , # dataset( "QCD_HT500to700" , "/QCD_HT500to700_TuneCUETP8M1_13TeV-madgraphMLM-pythia8/RunIISpring15DR74-Asympt25ns_MCRUN2_74_V9-v1/AODSIM" , MC , 1 , 100 , splitting='FileBased' , priority=10 , label='signal' ) , # dataset( "QCD_HT700to1000" , "/QCD_HT700to1000_TuneCUETP8M1_13TeV-madgraphMLM-pythia8/RunIISpring15DR74-Asympt25ns_MCRUN2_74_V9-v1/AODSIM" , MC , 1 , 1000 , splitting='FileBased' , priority=15 , label='signal' ) , # dataset( "QCD_HT1000to1500" , "/QCD_HT1000to1500_TuneCUETP8M1_13TeV-madgraphMLM-pythia8/RunIISpring15DR74-Asympt25ns_MCRUN2_74_V9-v2/AODSIM" , MC , 1 , 100 , splitting='FileBased' , priority=30 , label='signal' ) , # dataset( "QCD_HT1500to2000" , "/QCD_HT1500to2000_TuneCUETP8M1_13TeV-madgraphMLM-pythia8/RunIISpring15DR74-Asympt25ns_MCRUN2_74_V9-v1/AODSIM" , MC , 1 , 100 , splitting='FileBased' , priority=20 , label='signal' ) , # dataset( "QCD_HT2000toInf" , "/QCD_HT2000toInf_TuneCUETP8M1_13TeV-madgraphMLM-pythia8/RunIISpring15DR74-Asympt25ns_MCRUN2_74_V9-v1/AODSIM" , MC , 1 , 100 , splitting='FileBased' , priority=20 , label='signal' ) , dataset( "DataSkim_Run2015-PRv3" , "/JetHT/yoshin-DataSkim-20160302-80c51f15cd036b2256e94c207509265d/USER" , DATA , 1000 , 20000 , splitting='EventAwareLumiBased' , priority=50 , label='signal', inputDBS='phys03' ) , ] if __name__ == '__main__': ############################################################ ## Common settings ############################################################ from WMCore.Configuration import Configuration import time config = Configuration() config.section_("General") config.General.workArea = 'crab_' + jobname + time.strftime("-%Y-%m%d") + '-' + postfix tasklistFileName = config.General.workArea + '.txt' if not dryrun: tasklistFile = open(tasklistFileName, 'a')
# dataset( "mass_pi_d_10_tau_pi_d_100" , mass_pi_d_10_tau_pi_d_100 , MC , 1 , 10000 , splitting='FileBased' , priority=99 , inputDBS='phys03' , label='signal' , doHLT=0 ) , # dataset( "mass_pi_d_10_tau_pi_d_150" , mass_pi_d_10_tau_pi_d_150 , MC , 1 , 10000 , splitting='FileBased' , priority=99 , inputDBS='phys03' , label='signal' , doHLT=0 ) , # dataset( "mass_pi_d_10_tau_pi_d_300" , mass_pi_d_10_tau_pi_d_300 , MC , 1 , 10000 , splitting='FileBased' , priority=99 , inputDBS='phys03' , label='signal' , doHLT=0 ) , # dataset( "ModelA" , ModelA , MC , 1 , 10000 , splitting='FileBased' , priority=99 , inputDBS='phys03' , label='signal' , doHLT=0 ) , # dataset( "ModelB" , ModelB , MC , 1 , 10000 , splitting='FileBased' , priority=99 , inputDBS='phys03' , label='signal' , doHLT=0 ) , # dataset( "QCD_HT50to100" , QCD_HT50to100 , MC , 10 , 10000 , splitting='FileBased' , priority=10 , label='signal' ) , # dataset( "QCD_HT100to200" , QCD_HT100to200 , MC , 10 , 10000 , splitting='FileBased' , priority=10 , label='signal' ) , # dataset( "QCD_HT200to300" , QCD_HT200to300 , MC , 10 , 10000 , splitting='FileBased' , priority=10 , label='signal' ) , # dataset( "QCD_HT300to500" , QCD_HT300to500 , MC , 10 , 10000 , splitting='FileBased' , priority=10 , label='signal' ) , # dataset( "QCD_HT500to700" , QCD_HT500to700 , MC , 2 , 10000 , splitting='FileBased' , priority=10 , label='signal' ) , # dataset( "QCD_HT700to1000" , QCD_HT700to1000 , MC , 2 , 10000 , splitting='FileBased' , priority=80 , label='signal' ) , # dataset( "QCD_HT1000to1500" , QCD_HT1000to1500 , MC , 1 , 10000 , splitting='FileBased' , priority=90 , label='signal' ) , # dataset( "QCD_HT1500to2000" , QCD_HT1500to2000 , MC , 1 , 10000 , splitting='FileBased' , priority=80 , label='signal' ) , # dataset( "QCD_HT2000toInf" , QCD_HT2000toInf , MC , 1 , 10000 , splitting='FileBased' , priority=70 , label='signal' ) , # dataset( "WJet" , WJet , MC , 1 , 10000 , splitting='FileBased' , priority=70 , label='wjet' ) , dataset( "QCD_HT700to1000x" , QCD_HT700to1000x , MC , 2 , 10000 , splitting='FileBased' , priority=80 , label='signal' ) , dataset( "QCD_HT1000to1500x" , QCD_HT1000to1500x , MC , 1 , 10000 , splitting='FileBased' , priority=90 , label='signal' ) , dataset( "QCD_HT1500to2000x" , QCD_HT1500to2000x , MC , 1 , 10000 , splitting='FileBased' , priority=80 , label='signal' ) , dataset( "QCD_HT2000toInfx" , QCD_HT2000toInfx , MC , 1 , 10000 , splitting='FileBased' , priority=70 , label='signal' ) , ] import os crabTaskDir = 'crabTasks' if not os.path.exists(crabTaskDir): os.makedirs(crabTaskDir) if __name__ == '__main__': ############################################################ ## Common settings ############################################################
jobname = 'Analysis-20170221' # Jobname psetname = 'Configuration/test/test_cfg.py' # Path to pset postfix = 'v1' # Postfix to job, increment for each major version dryrun = 0 from datasets import dataset from wrappers import submit, submit_newthread datasets = [ #dataset( "WJetsToLNuInclusive" , "/WJetsToLNu_TuneCUETP8M1_13TeV-amcatnloFXFX-pythia8/RunIISpring15DR74-Asympt25ns_MCRUN2_74_V9-v1/AODSIM" , MC, 1, 1000, splitting='FileBased', priority=30, label='wjet' ), # dataset( "WJetSkimMuon" , "/SingleMuon/yoshin-WJetSkim-ede3f21fae18a825b193df32c86b780e/USER" , DATA , 10000 , 10000000 , splitting='EventAwareLumiBased' , priority=30 , label='wjet' , inputDBS='phys03' ) , dataset( "GJets_HT-600ToInf_RunIIFall15DR76", "/GJets_HT-600ToInf_TuneCUETP8M1_13TeV-madgraphMLM-pythia8/RunIIFall15DR76-PU25nsData2015v1_76X_mcRun2_asymptotic_v12-v1/AODSIM", MC, 1, 1000, splitting='FileBased', priority=30, label='gjet'), dataset( "GJets_HT-400To600_RunIIFall15DR76", "/GJets_HT-400To600_TuneCUETP8M1_13TeV-madgraphMLM-pythia8/RunIIFall15DR76-PU25nsData2015v1_76X_mcRun2_asymptotic_v12-v1/AODSIM", MC, 1, 1000, splitting='FileBased', priority=30, label='gjet'), dataset( "GJets_HT-200To400_RunIIFall15DR76",
# 0.75 Marks. # To test your trainer and arePantsonFire class, Just create random tensor and see if everything is working or not. from torch.utils.data import DataLoader # Your code goes here. from trainer import trainer from utils import * from datasets import dataset from Encoder import Encoder from LiarLiar import arePantsonFire from Attention import MultiHeadAttention, PositionFeedforward liar_dataset_train = dataset(prep_Data_from='train') liar_dataset_val = dataset(prep_Data_from='val') sent_len, just_len = liar_dataset_train.get_max_lenghts() dataloader_train = DataLoader(dataset=liar_dataset_train, batch_size=50) dataloader_val = DataLoader(dataset=liar_dataset_val, batch_size=25) statement_encoder = Encoder(hidden_dim=512, conv_layers=5) justification_encoder = Encoder(hidden_dim=512, conv_layers=5) multiheadAttention = MultiHeadAttention(hid_dim=512, n_heads=32) positionFeedForward = PositionFeedforward(hid_dim=512, feedForward_dim=2048) model = arePantsonFire(statement_encoder, justification_encoder, multiheadAttention, positionFeedForward, 512, sent_len, just_len, liar_dataset_train.embedding_dim, 'cpu') trainer(model, dataloader_train, dataloader_val, num_epochs=1, train_batch=1, test_batch=1, device='cpu')
MC = 0 DATA = 1 jobname = 'Skim-20170303' # Jobname psetname = 'Configuration/test/test_cfg.py' # Path to pset postfix = 'v1' # Postfix to job, increment for each major version dryrun = 0 from datasets import dataset from wrappers import submit, submit_newthread datasets = [ # dataset( "Run2016B-v1" , "/JetHT/Run2016B-23Sep2016-v1/AOD" , DATA , 10 , 1000000 , splitting='LumiBased' , priority=10 , label='signal' ) , dataset("Run2016B-v3", "/JetHT/Run2016B-23Sep2016-v3/AOD", DATA, 10, 1000000, splitting='LumiBased', priority=10, label='signal'), # dataset( "Run2016C" , "/JetHT/Run2016C-23Sep2016-v1/AOD" , DATA , 10 , 1000000 , splitting='LumiBased' , priority=10 , label='signal' ) , # dataset( "Run2016D" , "/JetHT/Run2016D-23Sep2016-v1/AOD" , DATA , 10 , 1000000 , splitting='LumiBased' , priority=10 , label='signal' ) , # dataset( "Run2016E" , "/JetHT/Run2016E-23Sep2016-v1/AOD" , DATA , 10 , 1000000 , splitting='LumiBased' , priority=10 , label='signal' ) , # dataset( "Run2016F" , "/JetHT/Run2016F-23Sep2016-v1/AOD" , DATA , 10 , 1000000 , splitting='LumiBased' , priority=10 , label='signal' ) , # dataset( "Run2016G" , "/JetHT/Run2016G-23Sep2016-v1/AOD" , DATA , 10 , 1000000 , splitting='LumiBased' , priority=10 , label='signal' ) , ] import os crabTaskDir = 'crabTasks' if not os.path.exists(crabTaskDir): os.makedirs(crabTaskDir)
# dataset( "mass_pi_d_10_tau_pi_d_0p001" , mass_pi_d_10_tau_pi_d_0p001 , MC , 1 , 10000 , splitting='FileBased' , priority=99 , inputDBS='phys03' , label='signal' , doHLT=0 ) , # dataset( "mass_pi_d_10_tau_pi_d_0p1" , mass_pi_d_10_tau_pi_d_0p1 , MC , 1 , 10000 , splitting='FileBased' , priority=99 , inputDBS='phys03' , label='signal' , doHLT=0 ) , # dataset( "mass_pi_d_10_tau_pi_d_1" , mass_pi_d_10_tau_pi_d_1 , MC , 1 , 10000 , splitting='FileBased' , priority=99 , inputDBS='phys03' , label='signal' , doHLT=0 ) , # dataset( "mass_pi_d_10_tau_pi_d_5" , mass_pi_d_10_tau_pi_d_5 , MC , 1 , 10000 , splitting='FileBased' , priority=99 , inputDBS='phys03' , label='signal' , doHLT=0 ) , # dataset( "mass_pi_d_10_tau_pi_d_25" , mass_pi_d_10_tau_pi_d_25 , MC , 1 , 10000 , splitting='FileBased' , priority=99 , inputDBS='phys03' , label='signal' , doHLT=0 ) , # dataset( "mass_pi_d_10_tau_pi_d_60" , mass_pi_d_10_tau_pi_d_60 , MC , 1 , 10000 , splitting='FileBased' , priority=99 , inputDBS='phys03' , label='signal' , doHLT=0 ) , # dataset( "mass_pi_d_10_tau_pi_d_100" , mass_pi_d_10_tau_pi_d_100 , MC , 1 , 10000 , splitting='FileBased' , priority=99 , inputDBS='phys03' , label='signal' , doHLT=0 ) , # dataset( "mass_pi_d_10_tau_pi_d_150" , mass_pi_d_10_tau_pi_d_150 , MC , 1 , 10000 , splitting='FileBased' , priority=99 , inputDBS='phys03' , label='signal' , doHLT=0 ) , # dataset( "mass_pi_d_10_tau_pi_d_300" , mass_pi_d_10_tau_pi_d_300 , MC , 1 , 10000 , splitting='FileBased' , priority=99 , inputDBS='phys03' , label='signal' , doHLT=0 ) , # dataset( "ModelA" , ModelA , MC , 1 , 10000 , splitting='FileBased' , priority=99 , inputDBS='phys03' , label='signal' , doHLT=0 ) , # dataset( "ModelB" , ModelB , MC , 1 , 10000 , splitting='FileBased' , priority=99 , inputDBS='phys03' , label='signal' , doHLT=0 ) , # dataset( "QCD_HT50to100" , QCD_HT50to100 , MC , 10 , 10000 , splitting='FileBased' , priority=10 , label='signal' ) , # dataset( "QCD_HT100to200" , QCD_HT100to200 , MC , 10 , 10000 , splitting='FileBased' , priority=10 , label='signal' ) , # dataset( "QCD_HT200to300" , QCD_HT200to300 , MC , 10 , 10000 , splitting='FileBased' , priority=10 , label='signal' ) , # dataset( "QCD_HT300to500" , QCD_HT300to500 , MC , 10 , 10000 , splitting='FileBased' , priority=10 , label='signal' ) , dataset( "QCD_HT500to700" , QCD_HT500to700 , MC , 2 , 10000 , splitting='FileBased' , priority=10 , label='signal' ) , dataset( "QCD_HT700to1000" , QCD_HT700to1000 , MC , 2 , 10000 , splitting='FileBased' , priority=80 , label='signal' ) , dataset( "QCD_HT1000to1500" , QCD_HT1000to1500 , MC , 1 , 10000 , splitting='FileBased' , priority=90 , label='signal' ) , dataset( "QCD_HT1500to2000" , QCD_HT1500to2000 , MC , 1 , 10000 , splitting='FileBased' , priority=80 , label='signal' ) , dataset( "QCD_HT2000toInf" , QCD_HT2000toInf , MC , 1 , 10000 , splitting='FileBased' , priority=99 , label='signal' ) , # dataset( "WJet" , WJet , MC , 1 , 10000 , splitting='FileBased' , priority=70 , label='wjet' ) , # dataset( "QCD_HT700to1000x" , QCD_HT700to1000x , MC , 2 , 10000 , splitting='FileBased' , priority=80 , label='signal' ) , # dataset( "QCD_HT1000to1500x" , QCD_HT1000to1500x , MC , 1 , 10000 , splitting='FileBased' , priority=90 , label='signal' ) , # dataset( "QCD_HT1500to2000x" , QCD_HT1500to2000x , MC , 1 , 10000 , splitting='FileBased' , priority=80 , label='signal' ) , # dataset( "QCD_HT2000toInfx" , QCD_HT2000toInfx , MC , 1 , 10000 , splitting='FileBased' , priority=70 , label='signal' ) , ] import os crabTaskDir = 'crabTasks' if not os.path.exists(crabTaskDir): os.makedirs(crabTaskDir)
# dataset( "QCD_HT700to1000" , QCD_HT700to1000 , MC , 2 , 10000 , splitting='FileBased' , priority=80 , label='signal' ) , # dataset( "QCD_HT1000to1500" , QCD_HT1000to1500 , MC , 1 , 10000 , splitting='FileBased' , priority=90 , label='signal' ) , # dataset( "QCD_HT1500to2000" , QCD_HT1500to2000 , MC , 1 , 10000 , splitting='FileBased' , priority=80 , label='signal' ) , # dataset( "QCD_HT2000toInf" , QCD_HT2000toInf , MC , 1 , 10000 , splitting='FileBased' , priority=99 , label='signal' ) , # dataset( "WJet" , WJet , MC , 1 , 10000 , splitting='FileBased' , priority=70 , label='wjet' ) , # dataset( "QCD_HT700to1000x" , QCD_HT700to1000x , MC , 2 , 10000 , splitting='FileBased' , priority=80 , label='signal' ) , # dataset( "QCD_HT1000to1500x" , QCD_HT1000to1500x , MC , 1 , 10000 , splitting='FileBased' , priority=90 , label='signal' ) , # dataset( "QCD_HT1500to2000x" , QCD_HT1500to2000x , MC , 1 , 10000 , splitting='FileBased' , priority=80 , label='signal' ) , # dataset( "QCD_HT2000toInfx" , QCD_HT2000toInfx , MC , 1 , 10000 , splitting='FileBased' , priority=70 , label='signal' ) , # # For trigger testing # dataset( "test-HLT_QCD_HT50to100" , QCD_HT50to100 , MC , 1 , 1 , splitting='FileBased' , priority=199 , label='signal' , doHLT=1 ) , dataset("HLT_QCD_HT50to100", QCD_HT50to100, MC, 5, 10000, splitting='FileBased', priority=199, label='signal', doHLT=1), dataset("HLT_QCD_HT100to200", QCD_HT100to200, MC, 5, 10000, splitting='FileBased', priority=199, label='signal', doHLT=1), dataset("HLT_QCD_HT200to300", QCD_HT200to300,
"""MultiCRAB script template for EmergingJet analysis""" MC=0 DATA=1 jobname = 'DataSkim-20160302' # Jobname psetname = 'test_cfg.py' # Path to pset postfix = 'v0' # Postfix to job, increment for each major version dryrun = False from datasets import dataset from wrappers import submit, submit_newthread datasets = [ dataset( "Run2015D" , "/JetHT/Run2015D-PromptReco-v3/AOD" , DATA, 100000, 80000000, splitting='EventAwareLumiBased', priority=10, label='signal' ), ] if __name__ == '__main__': ############################################################ ## Common settings ############################################################ from WMCore.Configuration import Configuration import time config = Configuration() config.section_("General") config.General.workArea = 'crab_' + jobname + time.strftime("-%Y-%m%d") + '-' + postfix tasklistFileName = config.General.workArea + '.txt' if not dryrun: tasklistFile = open(tasklistFileName, 'a') config.section_("JobType") config.JobType.pluginName = 'Analysis'
from torch.utils.data import DataLoader from datasets import dataset from encoder import Encoder from Attention import MultiHeadAttention, PositionFeedforward from LiarLiar import arePantsonFire path_to_glove = None #liar_dataset_train and liar_dataset_val defined as datasets.dataset() with appropriate #value in prep_data_from argument to prepare data. sentence and justification length are both #defined as liar_dataset_train.get_max_length(). Instantiate dataloader_train and dataloader_val #on train and val dataset liar_dataset_train = dataset() liar_dataset_val = dataset(prep_Data_from='val', purpose='test_class') batch_size = 25 dataloader_train = DataLoader(liar_dataset_train, batch_size) dataloader_val = DataLoader(liar_dataset_val, batch_size) #statement_encoder and justification_encoder defined as instances of Encoder class statement_encoder = Encoder(5,512) justification_encoder = Encoder(5,512) #multiHeadAttention and positionFeedForward are instances of the respective classes multiHeadAttention = MultiHeadAttention(512, 32) positionFeedForward = PositionFeedforward(512, 2048) #model is an instance of arePantsOnFire class model = arePantsonFire( statement_encoder , justification_encoder
# "ESO137_3", -- problems with molecfit/NIR # "NGC7172_1", ## -- data OK? (has been re-observed but in same night as 7172_2 -- no FLUX observed) /// reduction fails / NIR molecfit # NGC7172_2 -- no FLUX observed # NGC7172_3 -- only telluric of the night is heavily saturated # NGC7582 -- not reduced ] # problematic OBs: "NGC1947_1": no FLUX -> use _2 instead # "NGC2775_1", --> no data / observed 2015-11 / check!! # ngc3351_1 (and _2 -- both taken in the same night): flux standard has some high counts # 3717_1: very badly centered # 4224_1: nearest telluric saturated, take telluric 3 hours after obs # 4254 / 4260: not yet observed # 7727: only telluric over-exposed for ob_name in ob_list: print(ob_name) d=dataset(ob_name) d.make_QC_page() flatten_ob(ob_name) run_molecfit(ob_name,"NIR") molecfit_QC(ob_name,"NIR") run_molecfit(ob_name,"VIS") molecfit_QC(ob_name,"VIS") ## flux_calibrate(ob_name,"NIR") flux_calibrate(ob_name,"VIS") flux_calibrate(ob_name,"UVB")
"""MultiCRAB script template for EmergingJet analysis""" MC=0 DATA=1 jobname = 'Skim-20170303' # Jobname psetname = 'Configuration/test/test_cfg.py' # Path to pset postfix = 'v1' # Postfix to job, increment for each major version dryrun = 0 from datasets import dataset from wrappers import submit, submit_newthread datasets = [ # dataset( "Run2016B-v1" , "/JetHT/Run2016B-23Sep2016-v1/AOD" , DATA , 10 , 1000000 , splitting='LumiBased' , priority=10 , label='signal' ) , dataset( "Run2016B-v3" , "/JetHT/Run2016B-23Sep2016-v3/AOD" , DATA , 10 , 1000000 , splitting='LumiBased' , priority=10 , label='signal' ) , # dataset( "Run2016C" , "/JetHT/Run2016C-23Sep2016-v1/AOD" , DATA , 10 , 1000000 , splitting='LumiBased' , priority=10 , label='signal' ) , # dataset( "Run2016D" , "/JetHT/Run2016D-23Sep2016-v1/AOD" , DATA , 10 , 1000000 , splitting='LumiBased' , priority=10 , label='signal' ) , # dataset( "Run2016E" , "/JetHT/Run2016E-23Sep2016-v1/AOD" , DATA , 10 , 1000000 , splitting='LumiBased' , priority=10 , label='signal' ) , # dataset( "Run2016F" , "/JetHT/Run2016F-23Sep2016-v1/AOD" , DATA , 10 , 1000000 , splitting='LumiBased' , priority=10 , label='signal' ) , # dataset( "Run2016G" , "/JetHT/Run2016G-23Sep2016-v1/AOD" , DATA , 10 , 1000000 , splitting='LumiBased' , priority=10 , label='signal' ) , ] import os crabTaskDir = 'crabTasks' if not os.path.exists(crabTaskDir): os.makedirs(crabTaskDir) if __name__ == '__main__': ############################################################ ## Common settings ############################################################
from wrappers import submit, submit_newthread datasets = [ # dataset( "WJetsToLNuInclusive" , "/WJetsToLNu_TuneCUETP8M1_13TeV-amcatnloFXFX-pythia8/RunIISpring15DR74-Asympt25ns_MCRUN2_74_V9-v1/AODSIM" , MC, 1, 1000, splitting='FileBased', priority=30, label='wjet' ), # dataset( "Dummy" , "/WJetsToLNu_TuneCUETP8M1_13TeV-amcatnloFXFX-pythia8/RunIISpring15DR74-Asympt25ns_MCRUN2_74_V9-v1/AODSIM" , MC , 1 , 1 , splitting='FileBased' , priority=99 , label='wjet' ) , # dataset( "ModelA" , "/EmergingJets_ModelA_TuneCUETP8M1_13TeV_pythia8Mod/yoshin-AODSIM-69070e02f00a6fbca8a74a9d93177037/USER" , MC , 1 , 10000000 , splitting='FileBased' , priority=99 , label='signal', inputDBS='phys03' ) , # dataset( "ModelB" , "/EmergingJets_ModelB_TuneCUETP8M1_13TeV_pythia8Mod/yoshin-AODSIM-69070e02f00a6fbca8a74a9d93177037/USER" , MC , 1 , 10000000 , splitting='FileBased' , priority=99 , label='signal', inputDBS='phys03' ) , # dataset( "QCD_HT500to700" , "/QCD_HT500to700_TuneCUETP8M1_13TeV-madgraphMLM-pythia8/RunIISpring15DR74-Asympt25ns_MCRUN2_74_V9-v1/AODSIM" , MC , 1 , 100 , splitting='FileBased' , priority=10 , label='signal' ) , # dataset( "QCD_HT700to1000" , "/QCD_HT700to1000_TuneCUETP8M1_13TeV-madgraphMLM-pythia8/RunIISpring15DR74-Asympt25ns_MCRUN2_74_V9-v1/AODSIM" , MC , 1 , 1000 , splitting='FileBased' , priority=15 , label='signal' ) , # dataset( "QCD_HT1000to1500" , "/QCD_HT1000to1500_TuneCUETP8M1_13TeV-madgraphMLM-pythia8/RunIISpring15DR74-Asympt25ns_MCRUN2_74_V9-v2/AODSIM" , MC , 1 , 100 , splitting='FileBased' , priority=30 , label='signal' ) , # dataset( "QCD_HT1500to2000" , "/QCD_HT1500to2000_TuneCUETP8M1_13TeV-madgraphMLM-pythia8/RunIISpring15DR74-Asympt25ns_MCRUN2_74_V9-v1/AODSIM" , MC , 1 , 100 , splitting='FileBased' , priority=20 , label='signal' ) , # dataset( "QCD_HT2000toInf" , "/QCD_HT2000toInf_TuneCUETP8M1_13TeV-madgraphMLM-pythia8/RunIISpring15DR74-Asympt25ns_MCRUN2_74_V9-v1/AODSIM" , MC , 1 , 100 , splitting='FileBased' , priority=20 , label='signal' ) , dataset( "DataSkim_Run2015-PRv3", "/JetHT/yoshin-DataSkim-20160302-80c51f15cd036b2256e94c207509265d/USER", DATA, 1000, 20000, splitting='EventAwareLumiBased', priority=50, label='signal', inputDBS='phys03'), ] if __name__ == '__main__': ############################################################ ## Common settings ############################################################ from WMCore.Configuration import Configuration import time config = Configuration()
"""MultiCRAB script template for EmergingJet analysis""" MC=0 DATA=1 jobname = 'Analysis-20170430' # Jobname psetname = 'Configuration/test/testscan_cfg.py' # Path to pset postfix = 'v1' # Postfix to job, increment for each major version dryrun = 0 from datasets import dataset from wrappers import submit, submit_newthread datasets = [ #dataset( "WJetsToLNuInclusive_RunIISummer16DR80Premix" , "/WJetsToLNu_TuneCUETP8M1_13TeV-amcatnloFXFX-pythia8/RunIISummer16DR80Premix-PUMoriond17_80X_mcRun2_asymptotic_2016_TrancheIV_v6-v1/AODSIM" , MC, 1, 2500, splitting='FileBased', priority=30, label='wjet' ), # dataset( "WJetSkimMuon" , "/SingleMuon/yoshin-WJetSkim-ede3f21fae18a825b193df32c86b780e/USER" , DATA , 10000 , 10000000 , splitting='EventAwareLumiBased' , priority=30 , label='wjet' , inputDBS='phys03' ) , #dataset( "GJets_HT-40To100_RunIISummer16DR80Premix" , "/GJets_HT-40To100_TuneCUETP8M1_13TeV-madgraphMLM-pythia8/RunIISummer16DR80Premix-PUMoriond17_80X_mcRun2_asymptotic_2016_TrancheIV_v6-v1/AODSIM" , MC, 1, 1000, splitting='FileBased', priority=30, label='gjet' ), dataset( "GJets_HT-100To200_RunIISummer16DR80Premix" , "/GJets_HT-100To200_TuneCUETP8M1_13TeV-madgraphMLM-pythia8/RunIISummer16DR80Premix-PUMoriond17_80X_mcRun2_asymptotic_2016_TrancheIV_v6-v1/AODSIM" , MC, 1, 1000, splitting='FileBased', priority=30, label='gjet' ), #dataset( "GJets_HT-200To400_RunIISummer16DR80Premix" , "/GJets_HT-200To400_TuneCUETP8M1_13TeV-madgraphMLM-pythia8/RunIISummer16DR80Premix-PUMoriond17_80X_mcRun2_asymptotic_2016_TrancheIV_v6-v1/AODSIM" , MC, 1, 1000, splitting='FileBased', priority=30, label='gjet' ), #dataset( "GJets_HT-400To600_RunIISummer16DR80Premix" , "/GJets_HT-400To600_TuneCUETP8M1_13TeV-madgraphMLM-pythia8/RunIISummer16DR80Premix-PUMoriond17_80X_mcRun2_asymptotic_2016_TrancheIV_v6-v1/AODSIM" , MC, 1, 1000, splitting='FileBased', priority=30, label='gjet' ), #dataset( "GJets_HT-600ToInf_RunIISummer16DR80Premix" , "/GJets_HT-600ToInf_TuneCUETP8M1_13TeV-madgraphMLM-pythia8/RunIISummer16DR80Premix-PUMoriond17_80X_mcRun2_asymptotic_2016_TrancheIV_v6-v1/AODSIM" , MC, 1, 1000, splitting='FileBased', priority=30, label='gjet' ), ] if __name__ == '__main__': ############################################################ ## Common settings ############################################################ from WMCore.Configuration import Configuration import time config = Configuration() config.section_("General")
from wrappers import submit, submit_newthread datasets = [ #dataset( "WJetsToLNuInclusive" , "/WJetsToLNu_TuneCUETP8M1_13TeV-amcatnloFXFX-pythia8/RunIISpring15DR74-Asympt25ns_MCRUN2_74_V9-v1/AODSIM" , MC, 1, 1000, splitting='FileBased', priority=30, label='wjet' ), # dataset( "WJetSkimMuon" , "/SingleMuon/yoshin-WJetSkim-ede3f21fae18a825b193df32c86b780e/USER" , DATA , 10000 , 10000000 , splitting='EventAwareLumiBased' , priority=30 , label='wjet' , inputDBS='phys03' ) , #dataset( "GJets_HT-600ToInf_RunIIFall15DR76" , "/GJets_HT-600ToInf_TuneCUETP8M1_13TeV-madgraphMLM-pythia8/RunIIFall15DR76-PU25nsData2015v1_76X_mcRun2_asymptotic_v12-v1/AODSIM" , MC, 1, 1000, splitting='FileBased', priority=30, label='gjet' ), #dataset( "GJets_HT-400To600_RunIIFall15DR76" , "/GJets_HT-400To600_TuneCUETP8M1_13TeV-madgraphMLM-pythia8/RunIIFall15DR76-PU25nsData2015v1_76X_mcRun2_asymptotic_v12-v1/AODSIM" , MC, 1, 1000, splitting='FileBased', priority=30, label='gjet' ), #dataset( "GJets_HT-200To400_RunIIFall15DR76" , "/GJets_HT-200To400_TuneCUETP8M1_13TeV-madgraphMLM-pythia8/RunIIFall15DR76-PU25nsData2015v1_76X_mcRun2_asymptotic_v12-v1/AODSIM" , MC, 1, 1000, splitting='FileBased', priority=30, label='gjet' ), #dataset( "GJets_HT-100To200_RunIIFall15DR76" , "/GJets_HT-100To200_TuneCUETP8M1_13TeV-madgraphMLM-pythia8/RunIIFall15DR76-PU25nsData2015v1_76X_mcRun2_asymptotic_v12-v1/AODSIM" , MC, 1, 1000, splitting='FileBased', priority=30, label='gjet' ), #dataset( "GJets_HT-40To100_RunIIFall15DR76" , "/GJets_HT-40To100_TuneCUETP8M1_13TeV-madgraphMLM-pythia8/RunIIFall15DR76-PU25nsData2015v1_76X_mcRun2_asymptotic_v12-v1/AODSIM" , MC, 1, 1000, splitting='FileBased', priority=30, label='gjet' ), #dataset( "GJets_HT-600ToInf_RunIISpring15DR74" , "/GJets_HT-600ToInf_TuneCUETP8M1_13TeV-madgraphMLM-pythia8/RunIISpring15DR74-Asympt25ns_MCRUN2_74_V9-v1/AODSIM" , MC, 1, 1000, splitting='FileBased', priority=30, label='gjet' ), #dataset( "GJets_HT-400To600_RunIISpring15DR74" , "/GJets_HT-400To600_TuneCUETP8M1_13TeV-madgraphMLM-pythia8/RunIISpring15DR74-Asympt25ns_MCRUN2_74_V9-v1/AODSIM" , MC, 1, 1000, splitting='FileBased', priority=30, label='gjet' ), dataset( "GJets_HT-200To400_RunIISpring15DR74", "/GJets_HT-200To400_TuneCUETP8M1_13TeV-madgraphMLM-pythia8/RunIISpring15DR74-Asympt25ns_MCRUN2_74_V9-v2/AODSIM", MC, 1, 1000, splitting='FileBased', priority=30, label='gjet'), dataset( "GJets_HT-100To200_RunIISpring15DR74", "/GJets_HT-100To200_TuneCUETP8M1_13TeV-madgraphMLM-pythia8/RunIISpring15DR74-Asympt25ns_MCRUN2_74_V9-v2/AODSIM", MC, 1, 1000, splitting='FileBased', priority=30, label='gjet'), #dataset( "GJets_HT-40To100_RunIISpring15DR74" , "/GJets_HT-40To100_TuneCUETP8M1_13TeV-madgraphMLM-pythia8/RunIISpring15DR74-Asympt25ns_MCRUN2_74_V9-v2/AODSIM" , MC, 1, 1000, splitting='FileBased', priority=30, label='gjet' ), ]
# dataset( "test-HLT_QCD_HT50to100" , QCD_HT50to100 , MC , 1 , 1 , splitting='FileBased' , priority=199 , label='signal' , doHLT=1 ) , # dataset( "HLT_QCD_HT50to100" , QCD_HT50to100 , MC , 1 , 100 , splitting='FileBased' , priority=199 , label='signal' , doHLT=1 ) , # dataset( "HLT_QCD_HT100to200" , QCD_HT100to200 , MC , 1 , 100 , splitting='FileBased' , priority=199 , label='signal' , doHLT=1 ) , # dataset( "HLT_QCD_HT200to300" , QCD_HT200to300 , MC , 1 , 100 , splitting='FileBased' , priority=199 , label='signal' , doHLT=1 ) , # dataset( "HLT_QCD_HT300to500" , QCD_HT300to500 , MC , 1 , 100 , splitting='FileBased' , priority=199 , label='signal' , doHLT=1 ) , # dataset( "HLT_QCD_HT500to700" , QCD_HT500to700 , MC , 1 , 100 , splitting='FileBased' , priority=199 , label='signal' , doHLT=1 ) , # dataset( "HLT_QCD_HT700to1000" , QCD_HT700to1000 , MC , 1 , 100 , splitting='FileBased' , priority=199 , label='signal' , doHLT=1 ) , # dataset( "HLT_QCD_HT1000to1500" , QCD_HT1000to1500 , MC , 1 , 100 , splitting='FileBased' , priority=199 , label='signal' , doHLT=1 ) , # dataset( "HLT_QCD_HT1500to2000" , QCD_HT1500to2000 , MC , 1 , 100 , splitting='FileBased' , priority=199 , label='signal' , doHLT=1 ) , # dataset( "HLT_QCD_HT2000toInf" , QCD_HT2000toInf , MC , 1 , 100 , splitting='FileBased' , priority=199 , label='signal' , doHLT=1 ) , # Data skim for trigger testing # dataset( "HLT_JetHT_G1" , JetHT_G1 , DATA , 1 , 1000 , splitting='LumiBased' , priority=199 , label='signal' , doHLT=1 ) , # dataset( "HLT_JetHT_H1" , JetHT_H1 , DATA , 1 , 1000 , splitting='LumiBased' , priority=199 , label='signal' , doHLT=1 ) , # No jobs generated with json file # dataset( "HLT_JetHT_H2" , JetHT_H2 , DATA , 1 , 1000 , splitting='LumiBased' , priority=199 , label='signal' , doHLT=1 ) , # dataset( "HLT_JetHT_H3" , JetHT_H3 , DATA , 1 , 1000 , splitting='LumiBased' , priority=199 , label='signal' , doHLT=1 ) , dataset( "HLT_JetHT_G1_b" , JetHT_G1 , DATA , 5 , 10000 , splitting='LumiBased' , priority=199 , label='signal' , doHLT=1 ) , dataset( "HLT_JetHT_H1_b" , JetHT_H1 , DATA , 5 , 10000 , splitting='LumiBased' , priority=199 , label='signal' , doHLT=1 ) , # No jobs generated with json file dataset( "HLT_JetHT_H2_b" , JetHT_H2 , DATA , 5 , 10000 , splitting='LumiBased' , priority=199 , label='signal' , doHLT=1 ) , dataset( "HLT_JetHT_H3_b" , JetHT_H3 , DATA , 5 , 10000 , splitting='LumiBased' , priority=199 , label='signal' , doHLT=1 ) , ] import os crabTaskDir = 'crabTasks' if not os.path.exists(crabTaskDir): os.makedirs(crabTaskDir) if __name__ == '__main__': ############################################################ ## Common settings ############################################################
jobname = 'Analysis-20170316' # Jobname psetname = 'Configuration/test/test_cfg.py' # Path to pset postfix = 'v7' # Postfix to job, increment for each major version dryrun = 0 from datasets import dataset from wrappers import submit, submit_newthread datasets = [ #dataset( "WJetsToLNuInclusive" , "/WJetsToLNu_TuneCUETP8M1_13TeV-amcatnloFXFX-pythia8/RunIISpring15DR74-Asympt25ns_MCRUN2_74_V9-v1/AODSIM" , MC, 1, 1000, splitting='FileBased', priority=30, label='wjet' ), # dataset( "WJetSkimMuon" , "/SingleMuon/yoshin-WJetSkim-ede3f21fae18a825b193df32c86b780e/USER" , DATA , 10000 , 10000000 , splitting='EventAwareLumiBased' , priority=30 , label='wjet' , inputDBS='phys03' ) , dataset( "GJet_Pt-15ToInf", "/GJet_Pt-15ToInf_TuneCUETP8M1_13TeV-pythia8/RunIIFall15DR76-PU25nsData2015v1_76X_mcRun2_asymptotic_v12-v1/AODSIM", MC, 1, 1000, splitting='FileBased', priority=30, label='gjet'), #dataset( "GJetDataRun2015D-v3" , "/SinglePhoton/Run2015D-PromptReco-v3/AOD" , DATA, 1, 10000, splitting='FileBased', priority=30, label='gjet' ), #dataset( "GJetDataRun2015D-v4" , "/SinglePhoton/Run2015D-PromptReco-v4/AOD" , DATA, 1, 10000, splitting='FileBased', priority=30, label='gjet' ), #dataset( "GJets_HT-600ToInf_RunIISpring15DR74" , "/GJets_HT-600ToInf_TuneCUETP8M1_13TeV-madgraphMLM-pythia8/RunIISpring15DR74-Asympt25ns_MCRUN2_74_V9-v1/AODSIM" , MC, 1, 1000, splitting='FileBased', priority=30, label='gjet' ), #dataset( "GJets_HT-400To600_RunIISpring15DR74" , "/GJets_HT-400To600_TuneCUETP8M1_13TeV-madgraphMLM-pythia8/RunIISpring15DR74-Asympt25ns_MCRUN2_74_V9-v1/AODSIM" , MC, 1, 1000, splitting='FileBased', priority=30, label='gjet' ), #dataset( "GJets_HT-200To400_RunIISpring15DR74" , "/GJets_HT-200To400_TuneCUETP8M1_13TeV-madgraphMLM-pythia8/RunIISpring15DR74-Asympt25ns_MCRUN2_74_V9-v2/AODSIM" , MC, 1, 1000, splitting='FileBased', priority=30, label='gjet' ), #dataset( "GJets_HT-100To200_RunIISpring15DR74" , "/GJets_HT-100To200_TuneCUETP8M1_13TeV-madgraphMLM-pythia8/RunIISpring15DR74-Asympt25ns_MCRUN2_74_V9-v2/AODSIM" , MC, 1, 1000, splitting='FileBased', priority=30, label='gjet' ), #dataset( "GJets_HT-40To100_RunIISpring15DR74" , "/GJets_HT-40To100_TuneCUETP8M1_13TeV-madgraphMLM-pythia8/RunIISpring15DR74-Asympt25ns_MCRUN2_74_V9-v2/AODSIM" , MC, 1, 1000, splitting='FileBased', priority=30, label='gjet' ), ] if __name__ == '__main__':
# dataset( "QCD_HT1000to1500x" , QCD_HT1000to1500x , MC , 1 , 10000 , splitting='FileBased' , priority=90 , label='signal' ) , # dataset( "QCD_HT1500to2000x" , QCD_HT1500to2000x , MC , 1 , 10000 , splitting='FileBased' , priority=80 , label='signal' ) , # dataset( "QCD_HT2000toInfx" , QCD_HT2000toInfx , MC , 1 , 10000 , splitting='FileBased' , priority=70 , label='signal' ) , # # For trigger testing # dataset( "HLT_QCD_HT300to500" , QCD_HT300to500 , MC , 1 , 100 , splitting='FileBased' , priority=199 , label='signal' , doHLT=0 ) , # dataset( "HLT_QCD_HT500to700" , QCD_HT500to700 , MC , 1 , 100 , splitting='FileBased' , priority=199 , label='signal' , doHLT=0 ) , # dataset( "HLT_QCD_HT700to1000" , QCD_HT700to1000 , MC , 1 , 100 , splitting='FileBased' , priority=199 , label='signal' , doHLT=0 ) , # dataset( "HLT_QCD_HT1000to1500" , QCD_HT1000to1500 , MC , 1 , 100 , splitting='FileBased' , priority=199 , label='signal' , doHLT=0 ) , # dataset( "HLT_QCD_HT1500to2000" , QCD_HT1500to2000 , MC , 1 , 100 , splitting='FileBased' , priority=199 , label='signal' , doHLT=0 ) , # dataset( "HLT_QCD_HT2000toInf" , QCD_HT2000toInf , MC , 1 , 100 , splitting='FileBased' , priority=199 , label='signal' , doHLT=0 ) , # Data skim for trigger testing dataset("HLT_JetHT_G1", JetHT_G1, DATA, 1, 1000, splitting='LumiBased', priority=199, label='signal', doHLT=1), ] import os crabTaskDir = 'crabTasks' if not os.path.exists(crabTaskDir): os.makedirs(crabTaskDir) if __name__ == '__main__': ############################################################ ## Common settings
jobname = 'Analysis-20170308' # Jobname psetname = 'Configuration/test/test_cfg.py' # Path to pset postfix = 'v4' # Postfix to job, increment for each major version dryrun = 0 from datasets import dataset from wrappers import submit, submit_newthread datasets = [ #dataset( "WJetsToLNuInclusive" , "/WJetsToLNu_TuneCUETP8M1_13TeV-amcatnloFXFX-pythia8/RunIISpring15DR74-Asympt25ns_MCRUN2_74_V9-v1/AODSIM" , MC, 1, 1000, splitting='FileBased', priority=30, label='wjet' ), # dataset( "WJetSkimMuon" , "/SingleMuon/yoshin-WJetSkim-ede3f21fae18a825b193df32c86b780e/USER" , DATA , 10000 , 10000000 , splitting='EventAwareLumiBased' , priority=30 , label='wjet' , inputDBS='phys03' ) , #dataset( "GJet_Pt-15ToInf_PhotonPtcut50" , "/GJet_Pt-15ToInf_TuneCUETP8M1_13TeV-pythia8/RunIIFall15DR76-PU25nsData2015v1_76X_mcRun2_asymptotic_v12-v1/AODSIM" , MC, 1, 1000, splitting='FileBased', priority=30, label='gjet' ), dataset( "GJet_Pt-15To6000-Flat_PhotonPtcut50", "/GJet_Pt-15To6000_TuneCUETP8M1-Flat_13TeV_pythia8/RunIIFall15DR76-PU25nsData2015v1_76X_mcRun2_asymptotic_v12-v1/AODSIM", MC, 1, 1000, splitting='FileBased', priority=30, label='gjet'), #dataset( "GJetDataRun2015D-v3" , "/SinglePhoton/Run2015D-PromptReco-v3/AOD" , DATA, 1, 10000, splitting='FileBased', priority=30, label='gjet' ), #dataset( "GJetDataRun2015D-v4" , "/SinglePhoton/Run2015D-PromptReco-v4/AOD" , DATA, 1, 10000, splitting='FileBased', priority=30, label='gjet' ), #dataset( "GJets_HT-600ToInf_RunIISpring15DR74" , "/GJets_HT-600ToInf_TuneCUETP8M1_13TeV-madgraphMLM-pythia8/RunIISpring15DR74-Asympt25ns_MCRUN2_74_V9-v1/AODSIM" , MC, 1, 1000, splitting='FileBased', priority=30, label='gjet' ), #dataset( "GJets_HT-400To600_RunIISpring15DR74" , "/GJets_HT-400To600_TuneCUETP8M1_13TeV-madgraphMLM-pythia8/RunIISpring15DR74-Asympt25ns_MCRUN2_74_V9-v1/AODSIM" , MC, 1, 1000, splitting='FileBased', priority=30, label='gjet' ), #dataset( "GJets_HT-200To400_RunIISpring15DR74" , "/GJets_HT-200To400_TuneCUETP8M1_13TeV-madgraphMLM-pythia8/RunIISpring15DR74-Asympt25ns_MCRUN2_74_V9-v2/AODSIM" , MC, 1, 1000, splitting='FileBased', priority=30, label='gjet' ), #dataset( "GJets_HT-100To200_RunIISpring15DR74" , "/GJets_HT-100To200_TuneCUETP8M1_13TeV-madgraphMLM-pythia8/RunIISpring15DR74-Asympt25ns_MCRUN2_74_V9-v2/AODSIM" , MC, 1, 1000, splitting='FileBased', priority=30, label='gjet' ), #dataset( "GJets_HT-40To100_RunIISpring15DR74" , "/GJets_HT-40To100_TuneCUETP8M1_13TeV-madgraphMLM-pythia8/RunIISpring15DR74-Asympt25ns_MCRUN2_74_V9-v2/AODSIM" , MC, 1, 1000, splitting='FileBased', priority=30, label='gjet' ), ] if __name__ == '__main__':
# dataset( "QCD_HT100to200" , QCD_HT100to200 , MC , 10 , 10000 , splitting='FileBased' , priority=10 , label='signal' ) , # dataset( "QCD_HT200to300" , QCD_HT200to300 , MC , 10 , 10000 , splitting='FileBased' , priority=10 , label='signal' ) , # dataset( "QCD_HT300to500" , QCD_HT300to500 , MC , 10 , 10000 , splitting='FileBased' , priority=10 , label='signal' ) , # dataset( "QCD_HT500to700" , QCD_HT500to700 , MC , 2 , 10000 , splitting='FileBased' , priority=10 , label='signal' ) , # dataset( "QCD_HT700to1000" , QCD_HT700to1000 , MC , 2 , 10000 , splitting='FileBased' , priority=80 , label='signal' ) , # dataset( "QCD_HT1000to1500" , QCD_HT1000to1500 , MC , 1 , 10000 , splitting='FileBased' , priority=90 , label='signal' ) , # dataset( "QCD_HT1500to2000" , QCD_HT1500to2000 , MC , 1 , 10000 , splitting='FileBased' , priority=80 , label='signal' ) , # dataset( "QCD_HT2000toInf" , QCD_HT2000toInf , MC , 1 , 10000 , splitting='FileBased' , priority=99 , label='signal' ) , # dataset( "WJet" , WJet , MC , 1 , 10000 , splitting='FileBased' , priority=70 , label='wjet' ) , # dataset( "QCD_HT700to1000x" , QCD_HT700to1000x , MC , 2 , 10000 , splitting='FileBased' , priority=80 , label='signal' ) , # dataset( "QCD_HT1000to1500x" , QCD_HT1000to1500x , MC , 1 , 10000 , splitting='FileBased' , priority=90 , label='signal' ) , # dataset( "QCD_HT1500to2000x" , QCD_HT1500to2000x , MC , 1 , 10000 , splitting='FileBased' , priority=80 , label='signal' ) , # dataset( "QCD_HT2000toInfx" , QCD_HT2000toInfx , MC , 1 , 10000 , splitting='FileBased' , priority=70 , label='signal' ) , # # For trigger testing # dataset( "test-HLT_QCD_HT50to100" , QCD_HT50to100 , MC , 1 , 1 , splitting='FileBased' , priority=199 , label='signal' , doHLT=1 ) , dataset( "HLT_QCD_HT50to100" , QCD_HT50to100 , MC , 5 , 10000 , splitting='FileBased' , priority=199 , label='signal' , doHLT=1 ) , dataset( "HLT_QCD_HT100to200" , QCD_HT100to200 , MC , 5 , 10000 , splitting='FileBased' , priority=199 , label='signal' , doHLT=1 ) , dataset( "HLT_QCD_HT200to300" , QCD_HT200to300 , MC , 5 , 10000 , splitting='FileBased' , priority=199 , label='signal' , doHLT=1 ) , dataset( "HLT_QCD_HT300to500" , QCD_HT300to500 , MC , 5 , 10000 , splitting='FileBased' , priority=199 , label='signal' , doHLT=1 ) , # dataset( "HLT_QCD_HT500to700" , QCD_HT500to700 , MC , 5 , 10000 , splitting='FileBased' , priority=199 , label='signal' , doHLT=1 ) , # dataset( "HLT_QCD_HT700to1000" , QCD_HT700to1000 , MC , 5 , 10000 , splitting='FileBased' , priority=199 , label='signal' , doHLT=1 ) , # dataset( "HLT_QCD_HT1000to1500" , QCD_HT1000to1500 , MC , 5 , 10000 , splitting='FileBased' , priority=199 , label='signal' , doHLT=1 ) , # dataset( "HLT_QCD_HT1500to2000" , QCD_HT1500to2000 , MC , 5 , 10000 , splitting='FileBased' , priority=199 , label='signal' , doHLT=1 ) , # dataset( "HLT_QCD_HT1500to2000x" , QCD_HT1500to2000x , MC , 5 , 10000 , splitting='FileBased' , priority=199 , label='signal' , doHLT=1 ) , # dataset( "HLT_QCD_HT2000toInf" , QCD_HT2000toInf , MC , 5 , 10000 , splitting='FileBased' , priority=199 , label='signal' , doHLT=1 ) , # Data skim for trigger testing # dataset( "HLT_JetHT_G1" , JetHT_G1 , DATA , 1 , 1000 , splitting='LumiBased' , priority=199 , label='signal' , doHLT=1 ) , # dataset( "HLT_JetHT_H1" , JetHT_H1 , DATA , 1 , 1000 , splitting='LumiBased' , priority=199 , label='signal' , doHLT=1 ) , # No jobs generated with json file # dataset( "HLT_JetHT_H2" , JetHT_H2 , DATA , 1 , 1000 , splitting='LumiBased' , priority=199 , label='signal' , doHLT=1 ) , # dataset( "HLT_JetHT_H3" , JetHT_H3 , DATA , 1 , 1000 , splitting='LumiBased' , priority=199 , label='signal' , doHLT=1 ) , # dataset( "HLT_SingleMuon_G1" , SingleMuon_G1 , DATA , 5 , 300000 , splitting='LumiBased' , priority=199 , label='signal' , doHLT=1 ) ,
"""MultiCRAB script template for EmergingJet analysis""" MC=0 DATA=1 jobname = 'Analysis-20160301' # Jobname psetname = 'test_cfg.py' # Path to pset postfix = 'v0' # Postfix to job, increment for each major version dryrun = False from datasets import dataset from wrappers import submit, submit_newthread datasets = [ dataset( "WJetsToLNuInclusive" , "/WJetsToLNu_TuneCUETP8M1_13TeV-amcatnloFXFX-pythia8/RunIISpring15DR74-Asympt25ns_MCRUN2_74_V9-v1/AODSIM" , MC, 1, 1000, splitting='FileBased', priority=30, label='wjet' ), ] if __name__ == '__main__': ############################################################ ## Common settings ############################################################ from WMCore.Configuration import Configuration import time config = Configuration() config.section_("General") config.General.workArea = 'crabTasks/' + 'crab_' + jobname + time.strftime("-%Y-%m%d") + '-' + postfix tasklistFileName = config.General.workArea + '.txt' if not dryrun: tasklistFile = open(tasklistFileName, 'a') config.section_("JobType") config.JobType.pluginName = 'Analysis'
jobname = 'Analysis-20170327' # Jobname psetname = 'Configuration/test/test_cfg.py' # Path to pset postfix = 'v9' # Postfix to job, increment for each major version dryrun = 0 from datasets import dataset from wrappers import submit, submit_newthread datasets = [ #dataset( "WJetsToLNuInclusive" , "/WJetsToLNu_TuneCUETP8M1_13TeV-amcatnloFXFX-pythia8/RunIISpring15DR74-Asympt25ns_MCRUN2_74_V9-v1/AODSIM" , MC, 1, 1000, splitting='FileBased', priority=30, label='wjet' ), # dataset( "WJetSkimMuon" , "/SingleMuon/yoshin-WJetSkim-ede3f21fae18a825b193df32c86b780e/USER" , DATA , 10000 , 10000000 , splitting='EventAwareLumiBased' , priority=30 , label='wjet' , inputDBS='phys03' ) , #dataset( "GJet_Pt-15ToInf" , "/GJet_Pt-15ToInf_TuneCUETP8M1_13TeV-pythia8/RunIIFall15DR76-PU25nsData2015v1_76X_mcRun2_asymptotic_v12-v1/AODSIM" , MC, 1, 1000, splitting='FileBased', priority=30, label='gjet' ), dataset("GJetDataRun2015D-v3", "/SinglePhoton/Run2015D-PromptReco-v3/AOD", DATA, 1, 10000, splitting='FileBased', priority=30, label='gjet'), dataset("GJetDataRun2015D-v4", "/SinglePhoton/Run2015D-PromptReco-v4/AOD", DATA, 1, 10000, splitting='FileBased', priority=30, label='gjet'), #dataset( "GJets_HT-600ToInf_RunIIFall15DR76" , "/GJets_HT-600ToInf_TuneCUETP8M1_13TeV-madgraphMLM-pythia8/RunIIFall15DR76-PU25nsData2015v1_76X_mcRun2_asymptotic_v12-v1/AODSIM" , MC, 1, 1000, splitting='FileBased', priority=30, label='gjet' ), #dataset( "GJets_HT-400To600_RunIIFall15DR76" , "/GJets_HT-400To600_TuneCUETP8M1_13TeV-madgraphMLM-pythia8/RunIIFall15DR76-PU25nsData2015v1_76X_mcRun2_asymptotic_v12-v1/AODSIM" , MC, 1, 1000, splitting='FileBased', priority=30, label='gjet' ), #dataset( "GJets_HT-200To400_RunIIFall15DR76" , "/GJets_HT-200To400_TuneCUETP8M1_13TeV-madgraphMLM-pythia8/RunIIFall15DR76-PU25nsData2015v1_76X_mcRun2_asymptotic_v12-v1/AODSIM" , MC, 1, 1000, splitting='FileBased', priority=30, label='gjet' ), #dataset( "GJets_HT-100To200_RunIIFall15DR76" , "/GJets_HT-100To200_TuneCUETP8M1_13TeV-madgraphMLM-pythia8/RunIIFall15DR76-PU25nsData2015v1_76X_mcRun2_asymptotic_v12-v1/AODSIM" , MC, 1, 1000, splitting='FileBased', priority=30, label='gjet' ),
# this is for W +Jet MC samples. Apply the W Pt cut (35<pT<90 GeV) # for fake rate check jobname = 'Analysis-20170316' # Jobname psetname = 'Configuration/test/test_cfg.py' # Path to pset postfix = 'v0' # Postfix to job, increment for each major version dryrun = 0 from datasets import dataset from wrappers import submit, submit_newthread datasets = [ dataset( "WJetsToLNuInclusive", "/WJetsToLNu_TuneCUETP8M1_13TeV-amcatnloFXFX-pythia8/RunIISpring15DR74-Asympt25ns_MCRUN2_74_V9-v1/AODSIM", MC, 1, 1000, splitting='FileBased', priority=30, label='wjet'), # dataset( "WJetSkimMuon" , "/SingleMuon/yoshin-WJetSkim-ede3f21fae18a825b193df32c86b780e/USER" , DATA , 10000 , 10000000 , splitting='EventAwareLumiBased' , priority=30 , label='wjet' , inputDBS='phys03' ) , #dataset( "GJets_HT-600ToInf_RunIIFall15DR76" , "/GJets_HT-600ToInf_TuneCUETP8M1_13TeV-madgraphMLM-pythia8/RunIIFall15DR76-PU25nsData2015v1_76X_mcRun2_asymptotic_v12-v1/AODSIM" , MC, 1, 1000, splitting='FileBased', priority=30, label='gjet' ), #dataset( "GJets_HT-400To600_RunIIFall15DR76" , "/GJets_HT-400To600_TuneCUETP8M1_13TeV-madgraphMLM-pythia8/RunIIFall15DR76-PU25nsData2015v1_76X_mcRun2_asymptotic_v12-v1/AODSIM" , MC, 1, 1000, splitting='FileBased', priority=30, label='gjet' ), #dataset( "GJets_HT-200To400_RunIIFall15DR76" , "/GJets_HT-200To400_TuneCUETP8M1_13TeV-madgraphMLM-pythia8/RunIIFall15DR76-PU25nsData2015v1_76X_mcRun2_asymptotic_v12-v1/AODSIM" , MC, 1, 1000, splitting='FileBased', priority=30, label='gjet' ), #dataset( "GJets_HT-100To200_RunIIFall15DR76" , "/GJets_HT-100To200_TuneCUETP8M1_13TeV-madgraphMLM-pythia8/RunIIFall15DR76-PU25nsData2015v1_76X_mcRun2_asymptotic_v12-v1/AODSIM" , MC, 1, 1000, splitting='FileBased', priority=30, label='gjet' ), #dataset( "GJets_HT-40To100_RunIIFall15DR76" , "/GJets_HT-40To100_TuneCUETP8M1_13TeV-madgraphMLM-pythia8/RunIIFall15DR76-PU25nsData2015v1_76X_mcRun2_asymptotic_v12-v1/AODSIM" , MC, 1, 1000, splitting='FileBased', priority=30, label='gjet' ), #dataset( "GJetDataRun2015D-v3" , "/SinglePhoton/Run2015D-PromptReco-v3/AOD" , DATA, 1, 10000, splitting='FileBased', priority=30, label='gjet' ), #dataset( "GJetDataRun2015D-v4" , "/SinglePhoton/Run2015D-PromptReco-v4/AOD" , DATA, 1, 10000, splitting='FileBased', priority=30, label='gjet' ), #dataset( "GJets_HT-600ToInf_RunIISpring15DR74" , "/GJets_HT-600ToInf_TuneCUETP8M1_13TeV-madgraphMLM-pythia8/RunIISpring15DR74-Asympt25ns_MCRUN2_74_V9-v1/AODSIM" , MC, 1, 1000, splitting='FileBased', priority=30, label='gjet' ), #dataset( "GJets_HT-400To600_RunIISpring15DR74" , "/GJets_HT-400To600_TuneCUETP8M1_13TeV-madgraphMLM-pythia8/RunIISpring15DR74-Asympt25ns_MCRUN2_74_V9-v1/AODSIM" , MC, 1, 1000, splitting='FileBased', priority=30, label='gjet' ), #dataset( "GJets_HT-200To400_RunIISpring15DR74" , "/GJets_HT-200To400_TuneCUETP8M1_13TeV-madgraphMLM-pythia8/RunIISpring15DR74-Asympt25ns_MCRUN2_74_V9-v2/AODSIM" , MC, 1, 1000, splitting='FileBased', priority=30, label='gjet' ),
# dataset( "QCD_HT2000toInf" , QCD_HT2000toInf , MC , 1 , 10000 , splitting='FileBased' , priority=99 , label='signal' ) , # dataset( "WJet" , WJet , MC , 1 , 10000 , splitting='FileBased' , priority=70 , label='wjet' ) , # dataset( "QCD_HT700to1000x" , QCD_HT700to1000x , MC , 2 , 10000 , splitting='FileBased' , priority=80 , label='signal' ) , # dataset( "QCD_HT1000to1500x" , QCD_HT1000to1500x , MC , 1 , 10000 , splitting='FileBased' , priority=90 , label='signal' ) , # dataset( "QCD_HT1500to2000x" , QCD_HT1500to2000x , MC , 1 , 10000 , splitting='FileBased' , priority=80 , label='signal' ) , # dataset( "QCD_HT2000toInfx" , QCD_HT2000toInfx , MC , 1 , 10000 , splitting='FileBased' , priority=70 , label='signal' ) , # JetHT data # dataset( "JetHT_G1" , JetHT_G1 , DATA , 20 , 100000000 , splitting='LumiBased' , priority=199 , label='signal' , doHLT=1 ) , # dataset( "JetHT_H1" , JetHT_H1 , DATA , 20 , 100000000 , splitting='LumiBased' , priority=199 , label='signal' , doHLT=1 ) , # No jobs generated with json file # dataset( "JetHT_H2" , JetHT_H2 , DATA , 10 , 100000000 , splitting='LumiBased' , priority=199 , label='signal' , doHLT=1 ) , # dataset( "JetHT_H3" , JetHT_H3 , DATA , 10 , 100000000 , splitting='LumiBased' , priority=199 , label='signal' , doHLT=1 ) , dataset("JetHT_H3-testing", JetHT_H3, DATA, 10, 10, splitting='LumiBased', priority=199, label='signal', doHLT=1), # For trigger testing # dataset( "HLT_QCD_HT300to500" , QCD_HT300to500 , MC , 1 , 100 , splitting='FileBased' , priority=199 , label='signal' , doHLT=0 ) , # dataset( "HLT_QCD_HT500to700" , QCD_HT500to700 , MC , 1 , 100 , splitting='FileBased' , priority=199 , label='signal' , doHLT=0 ) , # dataset( "HLT_QCD_HT700to1000" , QCD_HT700to1000 , MC , 1 , 100 , splitting='FileBased' , priority=199 , label='signal' , doHLT=0 ) , # dataset( "HLT_QCD_HT1000to1500" , QCD_HT1000to1500 , MC , 1 , 100 , splitting='FileBased' , priority=199 , label='signal' , doHLT=0 ) , # dataset( "HLT_QCD_HT1500to2000" , QCD_HT1500to2000 , MC , 1 , 100 , splitting='FileBased' , priority=199 , label='signal' , doHLT=0 ) , # dataset( "HLT_QCD_HT2000toInf" , QCD_HT2000toInf , MC , 1 , 100 , splitting='FileBased' , priority=199 , label='signal' , doHLT=0 ) , ] import os crabTaskDir = 'crabTasks'