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datasetsSig_2015.py
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import json
isMC_ = 'True'
isSignalMC_ = 'True'
applyFilter_ = 'False'
doSS_ = 'False'
data = {}
data['people'] = []
data['people'].append({
'name': 'Taustar_m250',
'das': '/Taustar_TauG_L10000_m250_13TeV-pythia8/RunIIFall15MiniAODv2-PU25nsData2015v1_76X_mcRun2_asymptotic_v12-v1/MINIAODSIM',
'nevents': '20000',
'nfiles': '9',
'xs': '0.0177 * 1.285',
'isMC' : isMC_,
'isSignalMC': isSignalMC_,
'applyFilter': applyFilter_,
'doSS': doSS_
})
data['people'].append({
'name': 'Taustar_m500',
'das': '/Taustar_TauG_L10000_m500_13TeV-pythia8/RunIIFall15MiniAODv2-PU25nsData2015v1_76X_mcRun2_asymptotic_v12-v1/MINIAODSIM',
'nevents': '20000',
'nfiles': '9',
'xs': '0.0108 * 1.284',
'isMC' : isMC_,
'isSignalMC': isSignalMC_,
'applyFilter': applyFilter_,
'doSS': doSS_
})
data['people'].append({
'name': 'Taustar_m750',
'das': '/Taustar_TauG_L10000_m750_13TeV-pythia8/RunIIFall15MiniAODv2-PU25nsData2015v1_76X_mcRun2_asymptotic_v12-v2/MINIAODSIM',
'nevents': '20000',
'nfiles': '1',
'xs': '6.639e-3 * 1.277',
'isMC' : isMC_,
'isSignalMC': isSignalMC_,
'applyFilter': applyFilter_,
'doSS': doSS_
})
data['people'].append({
'name':'Taustar_m1000',
'das': '/Taustar_TauG_L10000_m1000_13TeV-pythia8/RunIIFall15MiniAODv2-PU25nsData2015v1_76X_mcRun2_asymptotic_v12-v1/MINIAODSIM',
'nevents': '20000',
'nfiles': '14',
'xs': '4.069e-3 * 1.270',
'isMC' : isMC_,
'isSignalMC': isSignalMC_,
'applyFilter': applyFilter_,
'doSS': doSS_
})
data['people'].append({
'name': 'Taustar_m1250',
'das': '/Taustar_TauG_L10000_m1250_13TeV-pythia8/RunIIFall15MiniAODv2-PU25nsData2015v1_76X_mcRun2_asymptotic_v12-v1/MINIAODSIM',
'nevents': '15000',
'nfiles': '3',
'xs': '2.494e-3 * 1.264',
'isMC' : isMC_,
'isSignalMC': isSignalMC_,
'applyFilter': applyFilter_,
'doSS': doSS_
})
data['people'].append({
'name': 'Taustar_m1500',
'das': '/Taustar_TauG_L10000_m1500_13TeV-pythia8/RunIIFall15MiniAODv2-PU25nsData2015v1_76X_mcRun2_asymptotic_v12-v1/MINIAODSIM',
'nevents': '14718',
'nfiles': '16',
'xs': '1.529e-3 * 1.259',
'isMC' : isMC_,
'isSignalMC': isSignalMC_,
'applyFilter': applyFilter_,
'doSS': doSS_
})
data['people'].append({
'name': 'Taustar_m1750',
'das': '/Taustar_TauG_L10000_m1750_13TeV-pythia8/RunIIFall15MiniAODv2-PU25nsData2015v1_76X_mcRun2_asymptotic_v12-v1/MINIAODSIM',
'nevents': '14188',
'nfiles': '2',
'xs': '9.371e-4 * 1.256',
'isMC' : isMC_,
'isSignalMC': isSignalMC_,
'applyFilter': applyFilter_,
'doSS': doSS_
})
data['people'].append({
'name': 'Taustar_m2000',
'das': '/Taustar_TauG_L10000_m2000_13TeV-pythia8/RunIIFall15MiniAODv2-PU25nsData2015v1_76X_mcRun2_asymptotic_v12-v1/MINIAODSIM',
'nevents': '14766',
'nfiles': '2',
'xs': '5.744e-4 * 1.255',
'isMC' : isMC_,
'isSignalMC': isSignalMC_,
'applyFilter': applyFilter_,
'doSS': doSS_
})
data['people'].append({
'name': 'Taustar_m2250',
'das': '/Taustar_TauG_L10000_m2250_13TeV-pythia8/RunIIFall15MiniAODv2-PU25nsData2015v1_76X_mcRun2_asymptotic_v12-v1/MINIAODSIM',
'nevents': '10000',
'nfiles': '8',
'xs': '3.521e-4 * 1.256',
'isMC' : isMC_,
'isSignalMC': isSignalMC_,
'applyFilter': applyFilter_,
'doSS': doSS_
})
data['people'].append({
'name': 'Taustar_m2500',
'das': '/Taustar_TauG_L10000_m2500_13TeV-pythia8/RunIIFall15MiniAODv2-PU25nsData2015v1_76X_mcRun2_asymptotic_v12-v1/MINIAODSIM',
'nevents': '10000',
'nfiles': '15',
'xs': '2.159e-4 * 1.260',
'isMC' : isMC_,
'isSignalMC': isSignalMC_,
'applyFilter': applyFilter_,
'doSS': doSS_
})
data['people'].append({
'name': 'Taustar_m2750',
'das': '/Taustar_TauG_L10000_m2750_13TeV-pythia8/RunIIFall15MiniAODv2-PU25nsData2015v1_76X_mcRun2_asymptotic_v12-v1/MINIAODSIM',
'nevents': '10000',
'nfiles': '8',
'xs': '1.323e-4 * 1.266',
'isMC' : isMC_,
'isSignalMC': isSignalMC_,
'applyFilter': applyFilter_,
'doSS': doSS_
})
data['people'].append({
'name': 'Taustar_m3000',
'das': '/Taustar_TauG_L10000_m3000_13TeV-pythia8/RunIIFall15MiniAODv2-PU25nsData2015v1_76X_mcRun2_asymptotic_v12-v1/MINIAODSIM',
'nevents': '10000',
'nfiles': '',
'xs': '8.12e-5 * 1.275',
'isMC' : isMC_,
'isSignalMC': isSignalMC_,
'applyFilter': applyFilter_,
'doSS': doSS_
})
data['people'].append({
'name': 'Taustar_m3250',
'das': '/Taustar_TauG_L10000_m3250_13TeV-pythia8/RunIIFall15MiniAODv2-PU25nsData2015v1_76X_mcRun2_asymptotic_v12-v1/MINIAODSIM',
'nevents': '10000',
'nfiles': '3',
'xs': '4.97e-5 * 1.285',
'isMC' : isMC_,
'isSignalMC': isSignalMC_,
'applyFilter': applyFilter_,
'doSS': doSS_
})
data['people'].append({
'name': 'Taustar_m3500',
'das': '/Taustar_TauG_L10000_m3500_13TeV-pythia8/RunIIFall15MiniAODv2-PU25nsData2015v1_76X_mcRun2_asymptotic_v12-v2/MINIAODSIM',
'nevents': '10000',
'nfiles': '1',
'xs': '3.05e-5 * 1.297',
'isMC' : isMC_,
'isSignalMC': isSignalMC_,
'applyFilter': applyFilter_,
'doSS': doSS_
})
data['people'].append({
'name': 'Taustar_m3750',
'das': '/Taustar_TauG_L10000_m3750_13TeV-pythia8/RunIIFall15MiniAODv2-PU25nsData2015v1_76X_mcRun2_asymptotic_v12-v1/MINIAODSIM',
'nevents': '10000',
'nfiles': '',
'xs': '1.87e-5 * 1.310',
'isMC' : isMC_,
'isSignalMC': isSignalMC_,
'applyFilter': applyFilter_,
'doSS': doSS_
})
data['people'].append({
'name': 'Taustar_m4000',
'das': '/Taustar_TauG_L10000_m4000_13TeV-pythia8/RunIIFall15MiniAODv2-PU25nsData2015v1_76X_mcRun2_asymptotic_v12-v1/MINIAODSIM',
'nevents': '10000',
'nfiles': '',
'xs': '1.14e-5 * 1.324',
'isMC' : isMC_,
'isSignalMC': isSignalMC_,
'applyFilter': applyFilter_,
'doSS': doSS_
})
#data['people'].append({
# 'name': 'Taustar_m4250',
# 'das': '',
# 'nevents': '',
# 'nfiles': '',
# 'xs': '7.02e-6 * 1.340',
# 'isSignalMC': isSignalMC_
#})
data['people'].append({
'name': 'Taustar_m4500',
'das': '/Taustar_TauG_L10000_m4500_13TeV-pythia8/RunIIFall15MiniAODv2-PU25nsData2015v1_76X_mcRun2_asymptotic_v12-v1/MINIAODSIM',
'nevents': '9408',
'nfiles': '2',
'xs': '4.30e-6 * 1.356',
'isMC' : isMC_,
'isSignalMC': isSignalMC_,
'applyFilter': applyFilter_,
'doSS': doSS_
})
#data['people'].append({
# 'name': 'Taustar_m4750',
# 'das': '',
# 'nevents': '',
# 'nfiles': '',
# 'xs': '2.64e-6 * 1.372',
# 'isSignalMC': isSignalMC_
#})
data['people'].append({
'name': 'Taustar_m5000',
'das': '/Taustar_TauG_L10000_m5000_13TeV-pythia8/RunIIFall15MiniAODv2-PU25nsData2015v1_76X_mcRun2_asymptotic_v12-v1/MINIAODSIM',
'nevents': '10000',
'nfiles': '2',
'xs': '1.62e-6 * 1.389',
'isMC' : isMC_,
'isSignalMC': isSignalMC_,
'applyFilter': applyFilter_,
'doSS': doSS_
})
with open('datasetsSig.json', 'w') as outfile:
json.dump(data, outfile)