### Es importante indicar (cuando proceda) que isdata = 0 para que se aplique la normalizacion
treeMC = Sample.Tree(fileName=helper.selectSamples(
WORKPATH + 'dat/Samples_cern.dat', Backgrounds, 'MC'),
name='MC',
isdata=0)
treeSI = Sample.Tree(fileName=helper.selectSamples(
WORKPATH + 'dat/Samples_cern.dat', Signals, 'SI'),
name='SI',
isdata=0)
############# DEFINICION DE CORTES
### Como ejemplo pongo algunos de los cortes basicos de los displaced global muon pais (DMDM)
### Hay algunos definidos en include/CutManager, pero desde aqui podeis definir los que querais
### La sintaxis es la que se utilizaria con el metodo .Draw de un TTree normal
cuts = CutManager.CutManager() # Clase CutManager
haveDMDM = cuts.brackets('nDMDMBase > 0') # Corte 1
lowPhi = cuts.brackets(
'fabs(DMDMBase_dPhi[DMDMBase_maxIxy])< 3.14/2.0') # Corte 2
allcuts = cuts.AddListB([haveDMDM,
lowPhi]) # Combinamos ambos en un unico string
############# EJEMPLOS:
### --> Ejemplo de coger un TH1F con getTH1F():
### Nombre del histograma: 'hBCK' (fondo con treeMC) y 'hSig' (senyal con treeSI)
### Normalizado a la lumi
### Variable que ploteamos: Distancia transversa del vertice del primer DMDM candidate
### En 20 bins, de 0 a 10 (nos pintara overflow tambien)
### options: Nunca lo uso
### xlabel: El label del eje x
hist_E_relPFIso = r.TH1F("hist_E_relPFIso", "", 50, 0, 1)
hist_E_relPFIso_log = r.TH1F("hist_E_relPFIso_log", "", len(bin_iso_log) -1, bin_iso_log)
hist_M_relPFIso = r.TH1F("hist_M_relPFIso", "", 50, 0, 1)
hist_M_relPFIso_log = r.TH1F("hist_M_relPFIso_log", "", len(bin_iso_log) -1, bin_iso_log)
#########################
#### Load sample ####
#########################
treeBKG = Sample.Tree( fileName = helper.selectSamples(GALAPAGOPATH + 'dat/Samples_cern_UltraLegacy.dat', ['WW_postVFP', 'WZ_postVFP'], 'MC'), name = '2016', isdata = 0 )
###################################
#### Loop over tree events ####
###################################
cm = CutManager.CutManager()
for b in treeBKG.blocks:
for s in b.samples:
for t in s.ttrees:
print('New tree with:', t.GetEntries())
for e,ev in enumerate(t):
if e > 500000: break
#if not eval(cm.epath2016): continue
# Count number of hard process leptons:
hasLepton = False
for j in range(0, ev.nHardProcessParticle):
def __init__(self, outdir, treename, blockname, samplename, samplenumber, lumiweight, isdata, year = '2016'):
### outdir: Path where the root file will be stored
### treename: Name of the (Galapago) Tree (MC; DATA; SI)
### blockname: Name of the (Galapago) Block
### samplename: Name of the sample
### samplenumber: Number of the sample file/ttree
self.outdir = outdir
if self.outdir[-1] != '/': self.outdir = self.outdir + '/'
self.filename = self.outdir + '{0}__{1}__{2}__{3}.root'.format(treename, blockname, samplename, str(samplenumber))
self.treename = treename
self.blockname = blockname
self.samplename = samplename
self.samplenumber = samplenumber
self.lumiweight = lumiweight
self.isdata = isdata
self.year = year
self.cm = CutManager.CutManager()
self.sufix = '__{0}__{1}__{2}__{3}'.format(treename, blockname, samplename, str(samplenumber))
## Init histogram efficiencies
self.declareEfficiencies()
#### ------------------------------
#### ---- Set year configuration
#### ------------------------------
self.mumu_path = 'False'
self.mumu_selection = 'False'
self.ee_path = 'False'
self.ee_selection = 'False'
if year=='2016':
self.mumu_path = self.cm.mupath2016
self.ee_path = self.cm.epath2016
self.mumu_selection = self.cm.MM_BS2016
self.ee_selection = self.cm.EE_BS2016
elif year=='2017':
self.ee_path = self.cm.epath2017
self.ee_selection = self.cm.EE_BS2017
elif year=='2018':
self.mumu_path = self.cm.mupath2018
self.ee_path = self.cm.epath2018
self.mumu_selection = self.cm.MM_BS2018
self.ee_selection = self.cm.EE_BS2018
#### ------------------------------
#### ---- Regions initialization
#### ------------------------------
self.dielectronRegions = [] # region name : region cut
self.declareDielectronRegions()
self.dimuonRegions = [] # region name : region cut
self.declareDimuonRegions()
#### -------------------------------
#### ---- Histogram initialization
#### -------------------------------
self.hEE_yield = r.TH1F('hEE_yield' + self.sufix, ';Passed photon trigger;', 1, 0, 1)
self.hEE_nBSEE = {}
self.hEE_nPU = {}
self.hEE_dPhi = {}
self.hEE_dPhi_inv = {}
self.hEE_mass = {}
self.hEE_cosAlpha = {}
self.hEE_trackIxy = {}
self.hEE_trackIxy_log = {}
self.hEE_trackDxy = {}
self.hEE_sigmaD = {}
self.hEE_Lxy = {}
self.hEE_Ixy = {}
self.hEE_leadingEt = {}
self.hEE_subleadingEt = {}
self.hEE_normalizedChi2 = {}
self.hEE_vx_vy = {}
for region in self.dielectronRegions:
region_name = region[0]
self.declareDielectronHistograms(region_name)
self.hMM_yield = r.TH1F('hMM_yield' + self.sufix, ';Passed muon trigger;', 1, 0, 1)
self.hMM_nBSMM = {}
self.hMM_nPU = {}
self.hMM_dPhi = {}
self.hMM_dPhi_inv = {}
self.hMM_mass = {}
self.hMM_cosAlpha = {}
self.hMM_trackIxy = {}
self.hMM_trackIxy_log = {}
self.hMM_trackDxy = {}
self.hMM_sigmaD = {}
self.hMM_Lxy = {}
self.hMM_Ixy = {}
self.hMM_leadingPt = {}
self.hMM_subleadingPt = {}
self.hMM_normalizedChi2 = {}
self.hMM_vx_vy = {}
for region in self.dimuonRegions:
region_name = region[0]
self.declareDimuonHistograms(region_name)
#### --------------------------------
#### ---- Apply sumw2 to histograms
#### --------------------------------
for attr, value in self.__dict__.items():
if attr[0] == 'h':
if type(value) == dict:
for key in value.keys():
value[key].Sumw2()
else:
value.Sumw2()
treeEGDATA = Sample.Tree(fileName=helper.selectSamples(
WORKPATH + filename, DoubleEG, 'DATA'),
name='DATA',
isdata=1)
treeMuonDATA = Sample.Tree(fileName=helper.selectSamples(
WORKPATH + filename, DoubleMuon, 'DATA'),
name='DATA',
isdata=1)
treeMC = Sample.Tree(fileName=helper.selectSamples(WORKPATH + filename,
Backgrounds, 'MC'),
name='MC',
isdata=0)
############# Cut definition
cuts = CutManager.CutManager()
EESR = cuts.AddListB(
[cuts.nTrack, cuts.EEChannel, cuts.haveEEBase, cuts.EESR_dPhi])
EECR = cuts.AddListB(
[cuts.nTrack, cuts.EEChannel, cuts.haveEEBase, cuts.EECR_dPhi])
MMSR = cuts.AddListB([
cuts.nTrack, cuts.MMChannel, cuts.haveMM, cuts.MMSR_dPhi,
cuts.cosmicRejection
])
MMCR = cuts.AddListB([
cuts.nTrack, cuts.MMChannel, cuts.haveMM, cuts.MMCR_dPhi,
cuts.cosmicRejection
])
############# Plotting
start_time = time.time()