Python dataset 예제들, datasets.dataset Python 예제들

예제 #1

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 # 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,

예제 #2

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파일: multicrab_Analysis-20170321.py 프로젝트: yongbinfeng/EmergingJetAnalyzer

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",

예제 #3

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    #     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)

예제 #4

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    # 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)

예제 #5

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파일: multicrab_Analysis-20170823.py 프로젝트: yongbinfeng/EmergingJetAnalysis

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 ) ,

예제 #6

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파일: multicrab_Analysis-20160615.py 프로젝트: yhshin11/EmergingJetAnalysis

"""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__':

예제 #7

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파일: multicrab_Analysis-20160601.py 프로젝트: yongbinfeng/EmergingJetAnalysis

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(

예제 #8

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파일: multicrab_Analysis-20170520.py 프로젝트: yongbinfeng/EmergingJetAnalysis

 #     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",

예제 #9

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파일: multicrab_Analysis-20170426.py 프로젝트: lwang046/EmergingJetAnalysis

    #     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

예제 #10

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파일: multicrab_Analysis-20170520.py 프로젝트: yhshin11/EmergingJetAnalysis

#     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'

예제 #11

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파일: multicrab_HLT-Analysis-20171208.py 프로젝트: yongbinfeng/EmergingJetAnalysis

 # 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,

예제 #12

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    # 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__':

    ############################################################

예제 #13

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파일 보기

파일: multicrab_Analysis-20161012.py 프로젝트: yongbinfeng/EmergingJetAnalysis

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' ) ,

예제 #14

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파일 보기

파일: multicrab_HLT-Analysis-20180123.py 프로젝트: yhshin11/EmergingJetAnalysis

    # 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
    ############################################################

예제 #15

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파일 보기

파일: multicrab_Analysis-20170426.py 프로젝트: yhshin11/EmergingJetAnalysis

#     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()

예제 #16

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파일: overfit_single_batch.py 프로젝트: kosty/smoking-detector

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)

예제 #17

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"""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'

예제 #18

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파일: multicrab_Analysis-20161012.py 프로젝트: yhshin11/EmergingJetAnalysis

"""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__':

예제 #19

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파일 보기

파일: multicrab_Analysis-20170609.py 프로젝트: yhshin11/EmergingJetAnalysis

#     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__':

    ############################################################

예제 #20

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파일 보기

파일: multicrab_Analysis-20160314.py 프로젝트: yhshin11/EmergingJetAnalysis

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')

예제 #21

0

파일 보기

파일: multicrab_Analysis-20170523.py 프로젝트: yongbinfeng/EmergingJetAnalysis

#     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
    ############################################################

예제 #22

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파일: multicrab_Analysis-20170221.py 프로젝트: yongbinfeng/EmergingJetAnalyzer

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",

예제 #23

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파일: main.py 프로젝트: shreyas-bk/BITSF312_A2-NNFL-Assignment2

# 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')

예제 #24

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파일: multicrab_Skim-20170303.py 프로젝트: yongbinfeng/EmergingJetAnalysis

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)

예제 #25

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#     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)

예제 #26

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파일: multicrab_HLT-Analysis-20180130.py 프로젝트: yongbinfeng/EmergingJetAnalysis

 # 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,

예제 #27

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파일: multicrab_DataSkim-20160302.py 프로젝트: yhshin11/EmergingJetAnalysis

"""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'

예제 #28

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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

예제 #29

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파일: XSHOO_pipeline.py 프로젝트: astroleo/xshtools

#	"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")

예제 #30

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파일: multicrab_Skim-20170303.py 프로젝트: yhshin11/EmergingJetAnalysis

"""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
    ############################################################

예제 #31

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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()

예제 #32

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파일 보기

파일: multicrab_Analysis-20170430.py 프로젝트: yongbinfeng/EmergingJetAnalysis

"""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")

예제 #33

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파일 보기

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' ),
]

예제 #34

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파일 보기

파일: multicrab_HLT-Analysis-20171208.py 프로젝트: yhshin11/EmergingJetAnalysis

    # 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
    ############################################################

예제 #35

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파일 보기

파일: multicrab_Analysis-20170316_2.py 프로젝트: yongbinfeng/EmergingJetAnalyzer

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__':

예제 #36

0

파일 보기

파일: multicrab_HLT-Analysis-20170823.py 프로젝트: yongbinfeng/EmergingJetAnalysis

    # 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

예제 #37

0

파일 보기

파일: multicrab_Analysis-20170308.py 프로젝트: yongbinfeng/EmergingJetAnalyzer

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__':

예제 #38

0

파일 보기

파일: multicrab_HLT-Analysis-20180130.py 프로젝트: yhshin11/EmergingJetAnalysis

 # 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 )  ,

예제 #39

0

파일 보기

파일: multicrab_template-emjet.py 프로젝트: yhshin11/EmergingJetAnalysis

"""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'

예제 #40

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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' ),

예제 #41

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파일: multicrab_Analysis-20170316.py 프로젝트: yongbinfeng/EmergingJetAnalyzer

# 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' ),

예제 #42

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    # 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'