'monoelHfake': selectors.monoelectronHadProxy,
'elmu': selectors.oppflavor,
'eefake': selectors.zee,
'wenu': selectors.wenuall,
'zeeJets': selectors.zeeJets,
'zmmJets': selectors.zmmJets
}
sphLumi = sum(allsamples[s].lumi for s in ['sph-16b-r', 'sph-16c-r', 'sph-16d-r', 'sph-16e-r', 'sph-16f-r', 'sph-16g-r', 'sph-16h'])
haloNorms = [ 8.7 * allsamples[sph].lumi / sphLumi for sph in ['sph-16b-r', 'sph-16c-r', 'sph-16d-r', 'sph-16e-r', 'sph-16f-r', 'sph-16g-r', 'sph-16h'] ]
spikeNorms = [ 8.5 * allsamples[sph].lumi / sphLumi for sph in ['sph-16b-r', 'sph-16c-r', 'sph-16d-r', 'sph-16e-r', 'sph-16f-r', 'sph-16g-r', 'sph-16h'] ]
noncollision = [
('halo', selectors.haloMIP(haloNorms[0])),
('haloUp', selectors.haloCSC(haloNorms[0])),
('spikeSieie', selectors.spikeSieie(spikeNorms[0]))
]
data_15 = []
data_sph = ['monoph', 'efake', 'hfake', 'hfakeUp', 'hfakeDown', 'purity', 'purityUp', 'purityDown', 'lowmt', 'lowmtEfake', 'lowmtHfake', 'gjets', 'dimu', 'diel', 'monomu', 'monoel'] + noncollision
data_smu = ['dimu', 'monomu', 'monomuHfake', 'elmu', 'zmmJets'] # are SinglePhoton triggers in this PD? (do the samples know about them, obviously they are not used to define it)
data_sel = ['diel', 'monoel', 'monoelHfake', 'eefake', 'zeeJets'] # are SinglePhoton triggers in this PD? (do the samples know about them, obviously they are not used to define it)
mc_cand = ['monoph', 'purity']
mc_qcd = ['hfake', 'hfakeUp', 'hfakeDown', 'purity', 'purityUp', 'purityDown', 'gjets']
mc_sig = ['monoph', 'purity', 'signalRaw']
mc_lep = ['monomu', 'monoel']
mc_dilep = ['dimu', 'diel', 'elmu', 'zmmJets', 'zeeJets']
mc_vgcand = [(region, selectors.kfactor(defaults[region])) for region in mc_cand]
mc_vglep = [(region, selectors.kfactor(defaults[region])) for region in mc_lep]
mc_vgdilep = [(region, selectors.kfactor(defaults[region])) for region in mc_dilep]
#mc_gj = [('raw', selectors.kfactor(defaults['monoph'])), ('monoph', selectors.kfactor(selectors.gjSmeared)), ('purity', selectors.kfactor(selectors.purity))]
haloNorms = [ 8.7 * allsamples[sph].lumi / sphLumi for sph in ['sph-16b2-d', 'sph-16c2-d', 'sph-16d2-d'] ]
neroSphLumi = allsamples['sph-16b2-d'].lumi + allsamples['sph-16c2-d'].lumi + allsamples['sph-16d2-d'].lumi
print neroSphLumi
neroHaloNorms = [ 5.5 * allsamples[sph].lumi / neroSphLumi for sph in ['sph-16b2-d', 'sph-16c2-d', 'sph-16d2-d'] ]
print neroHaloNorms
neroSpikeNorms = [ 8.5 * allsamples[sph].lumi / neroSphLumi for sph in ['sph-16b2-d', 'sph-16c2-d', 'sph-16d2-d'] ]
selectors = {
# Data 2016
# dima
'sph-16b2-d': data_sph + [('halo', selectors.haloMIP(neroHaloNorms[0]))
,('haloUp', selectors.haloCSC(neroHaloNorms[0]))
,('haloDown', selectors.haloSieie(neroHaloNorms[0]))
,('spikeE2E9', selectors.spikeE2E9(neroSpikeNorms[0]))
,('spikeSieie', selectors.spikeSieie(neroSpikeNorms[0]))
,('spikeSipip', selectors.spikeSipip(neroSpikeNorms[0]))
],
'sph-16c2-d': data_sph + [('halo', selectors.haloMIP(neroHaloNorms[1]))
,('haloUp', selectors.haloCSC(neroHaloNorms[1]))
,('haloDown', selectors.haloSieie(neroHaloNorms[1]))
,('spikeE2E9', selectors.spikeE2E9(neroSpikeNorms[1]))
,('spikeSieie', selectors.spikeSieie(neroSpikeNorms[1]))
,('spikeSipip', selectors.spikeSipip(neroSpikeNorms[1]))
],
'sph-16d2-d': data_sph + [('halo', selectors.haloMIP(neroHaloNorms[2]))
,('haloUp', selectors.haloCSC(neroHaloNorms[2]))
,('haloDown', selectors.haloSieie(neroHaloNorms[2]))
,('spikeE2E9', selectors.spikeE2E9(neroSpikeNorms[2]))
,('spikeSieie', selectors.spikeSieie(neroSpikeNorms[2]))
,('spikeSipip', selectors.spikeSipip(neroSpikeNorms[2]))