def run(self):
for igen, gj in enumerate(self.outer.genjets_):
match=False
if abs(gj.Eta()) > 3.0 or abs(gj.Eta()) < 1.5 : continue
pt_gen=gj.Pt()
if pt_gen < 40 : continue
isReco=False
for itr, jet in enumerate(self.outer.jets_):
if jet.Pt()<20 : continue
#if jet.Pt()<200 : continue ##FIXME
if abs(jet.Eta()) > 3.0 or abs(jet.Eta()) < 1.5 : continue
if gj.DeltaR(jet) < 0.4: isReco=True
if not isReco: continue
for icl, di in enumerate(self.outer.cl_raw_):
ieta = self.outer.cl_eta_[icl]
iphi = self.outer.cl_phi_[icl]
ilayer = self.outer.cl_layer_[icl]
if f.deltaR(gj.Eta(),ieta, gj.Phi(),iphi ) >= self.dR: continue
for jcl, dj in enumerate(self.outer.cl_raw_):
jeta = self.outer.cl_eta_[jcl]
jphi = self.outer.cl_phi_[jcl]
jlayer = self.outer.cl_layer_[jcl]
if f.deltaR(gj.Eta(),jeta, gj.Phi(),jphi ) >= self.dR: continue
match = True
self.histos["M"].Fill(ilayer,jlayer,di*dj)
self.histos["v"].Fill(ilayer,di*pt_gen)
if match:
self.histos["N"].Fill(1)
return self
def run(self):
for igen, gj in enumerate(self.outer.genjets_):
match=False
if abs(gj.Eta()) > 3.0 or abs(gj.Eta()) < 1.5 : continue
pt_gen=gj.Pt()
pt0 =-1
pt1 =-1
for ipt in range( 0,len(self.ptcuts) -1 ):
if pt_gen >= self.ptcuts[ipt] and pt_gen<self.ptcuts[ipt+1]:
pt0 = self.ptcuts[ipt]
pt1 = self.ptcuts[ipt+1]
if pt0 < 0: continue ## not in the pt list
isReco=False
for itr, jet in enumerate(self.outer.jets_):
if jet.Pt()<20 : continue
if abs(jet.Eta()) > 3.0 or abs(jet.Eta()) < 1.5 : continue
if gj.DeltaR(jet) < 0.4: isReco=True
if not isReco: continue
for icl, di in enumerate(self.outer.cl_raw_):
ieta = self.outer.cl_eta_[icl]
iphi = self.outer.cl_phi_[icl]
if f.deltaR(gj.Eta(),ieta, gj.Phi(),iphi ) >= self.dR: continue
ilayer = self.outer.cl_layer_[icl]
ipt = self.outer.cl_pt_[icl]
iraw = self.outer.cl_raw_[icl]
self.histos["raw_layer%d_pt%.0f_%.0f"%(ilayer,pt0,pt1)] . Fill (iraw)
self.histos["cl_layer%d_pt%.0f_%.0f"%(ilayer,pt0,pt1)] . Fill (ipt)
return self
def loop(self):
nentries = self.chain.GetEntries()
for ientry, entry in enumerate(self.chain):
self.print_progress(ientry, nentries)
#self.clear()
#c3d_pt_ = np.array(entry.cl3d_pt)
#c3d_eta_ = np.array(entry.cl3d_eta)
#c3d_phi_ = np.array(entry.cl3d_phi)
#c3d_energy_ = np.array(entry.cl3d_energy)
gen_pt_ = np.array(entry.gen_pt)
gen_eta_ = np.array(entry.gen_eta)
gen_phi_ = np.array(entry.gen_phi)
gen_energy_ = np.array(entry.gen_energy)
gen_status_ = np.array(entry.gen_status)
gen_id_ = np.array(entry.gen_id)
cl_pt_ = np.array(entry.cl_pt)
cl_eta_ = np.array(entry.cl_eta)
cl_phi_ = np.array(entry.cl_phi)
cl_energy_ = np.array(entry.cl_energy)
cl_layer_ = np.array(entry.cl_layer)
cl_ncells_ = np.array(entry.cl_ncells)
##FIXME ??? check
cl_cells_ = np.array(entry.cl_cells) ### ?
tc_data_ = np.array(entry.tc_data)
for igen in range(0, len(gen_pt_)):
if gen_status_[igen] != 1: continue
if abs(gen_id_[igen]) != 11: continue ## electron
for icl in range(0, len(cl_pt_)):
if f.deltaR(cl_eta_[icl], gen_eta_[igen], cl_phi_[icl],
gen_phi_[igen]) > self.dR:
continue
## MATCHED
# 1. compute raw energy in the c2d
raw = 0.0
for icell in range(0, cl_ncells_[icl]):
raw += tc_data_[cl_cells_[icl][icell]]
# 2. save a histogram with the calibrated energy and the raw energy
# nominal and pt
name = "raw_layer_%d_truept_%.0f" % (cl_layer_[icl],
gen_pt_[igen])
if name not in self.histos:
self.histos[name] = ROOT.TH1D(name, name, self.nbins,
self.xmin, self.xmax)
self.histos[name].Fill(raw)
name = "rawt_layer_%d_truept_%.0f" % (cl_layer_[icl],
gen_pt_[igen])
t = math.exp(-cl_eta_[icl]) ## tan theta/2
sint = 2 * t / (1 + t * t) ## sin theta
if name not in self.histos:
self.histos[name] = ROOT.TH1D(name, name, self.nbins,
self.xmin, self.xmax)
self.histos[name].Fill(raw * sint)
name = "pt_layer_%d_truept_%.0f" % (cl_layer_[icl],
gen_pt_[igen])
if name not in self.histos:
self.histos[name] = ROOT.TH1D(name, name, self.nbins,
self.xmin, self.xmax)
self.histos[name].Fill(cl_pt_[icl])
## produce trigger jets and gen jets
self.output.cd()
for hStr in self.histos:
self.histos[hStr].Write()
return self
def plotResponse(self):
# definition of the output file and histogram to store in it
output = ROOT.TFile(self.outputFile + ".root", "RECREATE")
h_resoPt = ROOT.TH1D("resoPt", "Pt response", 100, 0, 2)
h_resoEta = ROOT.TH1D("resoEta", "Eta response", 100, -0.02, 0.02)
h_resoPhi = ROOT.TH1D("resoPhi", "Phi response", 100, -0.05, 0.05)
h_L1PtvsTrue2D = ROOT.TH2D("h_L1PtvsTrue2D", "h_L1PtvsTrue2D", 200, 0,
200, 201, -1, 200)
self.chain.Print()
# loop over the ttree ntries
for ientry, entry in enumerate(self.chain):
gen_pt_ = np.array(entry.gen_pt) # for vectors
gen_eta_ = np.array(entry.gen_eta)
gen_phi_ = np.array(entry.gen_phi)
gen_energy_ = np.array(entry.gen_energy)
gen_status_ = np.array(entry.gen_status)
gen_id_ = np.array(entry.gen_id)
c3d_pt_ = np.array(entry.cl3d_pt)
c3d_eta_ = np.array(entry.cl3d_eta)
c3d_phi_ = np.array(entry.cl3d_phi)
c3d_energy_ = np.array(entry.cl3d_energy)
# select the good C3d
goodC3d_idx = []
for i_c3d in range(len(c3d_pt_)):
if (abs(c3d_eta_[i_c3d]) > self.cfg.minEta_C3d
and abs(c3d_eta_[i_c3d]) < self.cfg.maxEta_C3d
and c3d_pt_[i_c3d] > self.cfg.minPt_C3d):
goodC3d_idx.append(i_c3d)
# loop over the gen particle and apply basic selection at MC-truth level
for i_gen in range(len(gen_pt_)):
if (abs(gen_eta_[i_gen]) > self.cfg.minEta_gen
and abs(gen_eta_[i_gen]) < self.cfg.maxEta_gen
and gen_pt_[i_gen] > self.cfg.minPt_gen
and abs(gen_id_[i_gen]) == self.cfg.particle_type
and gen_status_[i_gen] == self.cfg.particle_status):
hasMatched = False
pt_cand = -1.
eta_cand = -100.
phi_cand = -100.
# loop over the good 3D-cluster
for i in range(len(goodC3d_idx)):
i_c3d = goodC3d_idx[i]
dR = f.deltaR(gen_eta_[i_gen], c3d_eta_[i_c3d],
gen_phi_[i_gen], c3d_phi_[i_c3d])
if dR < 0.5:
hasMatched = True
if c3d_pt_[i_c3d] > pt_cand:
pt_cand = c3d_pt_[i_c3d]
eta_cand = c3d_eta_[i_c3d]
phi_cand = c3d_phi_[i_c3d]
# fill the response histograms
if hasMatched:
print gen_pt_[i_gen], pt_cand
h_L1PtvsTrue2D.Fill(gen_pt_[i_gen], pt_cand)
elif not hasMatched:
print gen_pt_[i_gen], -1
h_L1PtvsTrue2D.Fill(gen_pt_[i_gen], -1)
h_resoPt.Fill(pt_cand / gen_pt_[i_gen])
h_resoEta.Fill(eta_cand - gen_eta_[i_gen])
h_resoPhi.Fill(phi_cand - gen_phi_[i_gen])
# write histograms into output file
output.cd()
h_resoPt.Write()
h_resoEta.Write()
h_resoPhi.Write()
h_L1PtvsTrue2D.Write()