def remove_jets(parts, jets):
psjv = fj.vectorPJ()
reject_indexes = [
p.user_index() for j in jets for p in j.constituents()
if p.user_index() >= 0
]
# print ('indexes leading jets:', len(reject_indexes), sorted(reject_indexes))
_tmp = [
psjv.push_back(p) for p in parts
if p.user_index() not in reject_indexes
]
return psjv
def __init__(self, **kwargs):
self.configure_from_args(mean_pt=0.7, multiplicity=1, max_eta=1, max_pt=100, min_pt=0.15)
super(BoltzmannEvent, self).__init__(**kwargs)
if self.min_pt < 0:
self.min_pt = 0
self.particles = fj.vectorPJ()
self.funbg = ROOT.TF1("funbg", "2. / [0] * x * TMath::Exp(-(2. / [0]) * x)", self.min_pt, self.max_pt, 1);
self.funbg.SetParameter(0, self.mean_pt)
self.funbg.SetNpx(1000)
self.ROOT_random = ROOT.TRandom()
self.histogram_pt = ROOT.TH1F("BoltzmannEvent_pt", "BoltzmannEvent_pt;p_{T} (GeV/c)", 100, logbins(1e-1, self.max_pt, 100))
self.histogram_pt.SetDirectory(0)
self.histogram_eta = ROOT.TH1F("BoltzmannEvent_eta", "BoltzmannEvent_eta;#eta", 100, -self.max_eta, self.max_eta)
self.histogram_eta.SetDirectory(0)
self.histogram_phi = ROOT.TH1F("BoltzmannEvent_phi", "BoltzmannEvent_phi;#varphi (rad)", 100, -ROOT.TMath.Pi(), ROOT.TMath.Pi())
self.histogram_phi.SetDirectory(0)
self.nEvent = 0
def load_event(self, offset=0):
self.particles = None
if self.file_io is None:
self.open_file()
if self.file_io is None:
print('[e] unable to load the data file')
return None
if self.current_event_in_file >= self.current_file_number_of_events():
self.current_event_in_file = 0
self.file_io = None
return self.load_event(offset=offset)
self.event = self.file_io.df_events[self.current_event_in_file]
# print ('reset indexes')
# _tmp = [p.set_user_index(0) for ip,p in enumerate(event.particles)]
# print('loaded event:', self.current_event_in_file)
self.current_event_in_file = self.current_event_in_file + 1
self.particles = fj.vectorPJ()
for ip, p in enumerate(self.event.particles):
p.set_user_index(offset + ip)
self.particles.push_back(p)
return self.particles
def example():
tw = RTreeWriter()
print(tw)
tw.fill_branch('b', 10)
tw.fill_branch('b', 12.)
tw.fill_branch('bl', [1, 2, 3], do_enumerate=True)
tw.fill_branch('bt', (10, 20, 30.))
psj = fj.PseudoJet()
tw.fill_branch('jet', psj)
tw.fill_branch('jet', psj)
v = fj.vectorPJ()
_v = fj.PseudoJet(1, 2, 3, 4)
v.push_back(_v)
v.push_back(_v)
v.push_back(_v)
tw.fill_branch('jets', v)
tw.fill_branch('bd', {'x': 10, 'y': 20, 'z': 30.})
tw.fill_tree()
tw.write_and_close()
def load_event_with_loc(self, run_number=-1, ev_id=-1, offset=0):
self.particles = None
if self.file_io is None:
print('[e] unable to load the data because no file io is set')
return None
_events_match = [
e for e in self.file_io.df_events
if e.ev_id == ev_id and e.run_number == run_number
]
if len(_events_match) == 1:
self.event = _events_match[0]
else:
print('[w] requested ev_id:', ev_id, "run_number:", run_number,
'number of matches', len(_events_match))
return None
# print ('reset indexes')
# _tmp = [p.set_user_index(0) for ip,p in enumerate(event.particles)]
# print('loaded event:', self.current_event_in_file)
# self.current_event_in_file = self.current_event_in_file + 1
self.particles = fj.vectorPJ()
for ip, p in enumerate(self.event.particles):
p.set_user_index(offset + ip)
self.particles.push_back(p)
return self.particles
def jets_as_psj_vector(self):
self.psj_jet_vector = fj.vectorPJ()
# _tmp = [self.psj_jet_vector.push_back(j) for j in self.jets if not j.is_pure_ghost()]
_tmp = [self.psj_jet_vector.push_back(j) for j in self.jets]
return self.psj_jet_vector
def main():
parser = argparse.ArgumentParser(description='pythia8 fastjet on the fly',
prog=os.path.basename(__file__))
pyconf.add_standard_pythia_args(parser)
parser.add_argument('--ignore-mycfg',
help="ignore some settings hardcoded here",
default=False,
action='store_true')
parser.add_argument('--output', default="output.root", type=str)
parser.add_argument('--alpha', default=0, type=float)
parser.add_argument('--dRmax', default=0.0, type=float)
parser.add_argument('--zcut', default=0.1, type=float)
parser.add_argument('--overwrite',
help="overwrite output",
default=False,
action='store_true')
parser.add_argument('--embed',
help='run embedding from a file list',
default='',
type=str)
parser.add_argument('--SDsignal',
help='embed only SD signal prongs',
default=False,
action='store_true')
parser.add_argument('--SDsignal-single',
help='embed only SD signal - only leading prong!',
default=False,
action='store_true')
parser.add_argument('--efficiency',
help='apply charged particle efficiency',
default=False,
action='store_true')
parser.add_argument('--benchmark',
help='benchmark pthat setting - 80 GeV',
default=False,
action='store_true')
parser.add_argument('--csjet',
help='constituent subtration jet-by-jet',
default=False,
action='store_true')
args = parser.parse_args()
if args.output == 'output.root':
args.output = 'output_alpha_{}_dRmax_{}_SDzcut_{}.root'.format(
args.alpha, args.dRmax, args.zcut)
if args.py_seed >= 0:
args.output = 'output_alpha_{}_dRmax_{}_SDzcut_{}_seed_{}.root'.format(
args.alpha, args.dRmax, args.zcut, args.py_seed)
if args.embed:
args.output = args.output.replace('.root', '_emb.root')
if args.efficiency:
args.output = args.output.replace('.root', '_effi.root')
if args.SDsignal:
args.output = args.output.replace('.root', '_SDsignal.root')
if args.SDsignal_single:
args.output = args.output.replace('.root', '_SDsignal_single.root')
if args.csjet:
args.output = args.output.replace('.root', '_csjet.root')
if os.path.isfile(args.output):
if not args.overwrite:
print('[i] output', args.output,
'exists - use --overwrite to do just that...')
return
print(args)
# alice specific
max_eta = 0.9
# print the banner first
fj.ClusterSequence.print_banner()
print()
# set up our jet definition and a jet selector
jet_R0 = 0.4
jet_def = fj.JetDefinition(fj.antikt_algorithm, jet_R0)
print(jet_def)
mycfg = []
if args.benchmark:
mycfg = ['PhaseSpace:pThatMin = 80', 'PhaseSpace:pThatMax = -1']
jet_selector = fj.SelectorPtMin(80.0) & fj.SelectorPtMax(
100.0) & fj.SelectorAbsEtaMax(max_eta - 1.05 * jet_R0)
# jet_selector_cs = fj.SelectorPtMin(50.0) & fj.SelectorAbsEtaMax(max_eta - 1.05 * jet_R0)
else:
args.py_biaspow = 4
args.py_biasref = 10
jet_selector = fj.SelectorPtMin(20) & fj.SelectorAbsEtaMax(
max_eta - 1.05 * jet_R0)
# jet_selector_cs = fj.SelectorPtMin(50.0) & fj.SelectorAbsEtaMax(max_eta - 1.05 * jet_R0)
if args.ignore_mycfg:
mycfg = []
pythia = pyconf.create_and_init_pythia_from_args(args, mycfg)
if not pythia:
print("[e] pythia initialization failed.")
return
sd_zcut = args.zcut
sd = fjcontrib.SoftDrop(0, sd_zcut, jet_R0)
jarho = JetAnalysisWithRho(jet_R=jet_R0,
jet_algorithm=fj.antikt_algorithm,
particle_eta_max=max_eta)
ja = JetAnalysis(jet_R=jet_R0,
jet_algorithm=fj.antikt_algorithm,
particle_eta_max=max_eta)
be = None
embd = None
if len(args.embed) > 0:
embd = DataBackgroundIO(file_list=args.embed)
print(embd)
else:
be = BoltzmannEvent(mean_pt=0.6,
multiplicity=2000 * max_eta * 2,
max_eta=max_eta,
max_pt=100)
print(be)
cs = None
if args.dRmax > 0:
cs = CEventSubtractor(alpha=args.alpha,
max_distance=args.dRmax,
max_eta=max_eta,
bge_rho_grid_size=0.25,
max_pt_correct=100)
print(cs)
csjet = None
if args.csjet:
csjet = CSubtractorJetByJet(max_eta=max_eta, bge_rho_grid_size=0.25)
print(csjet)
parts_selector = fj.SelectorAbsEtaMax(max_eta)
if args.nev < 1:
args.nev = 1
outf = ROOT.TFile(args.output, 'recreate')
outf.cd()
t = ROOT.TTree('t', 't')
tw = RTreeWriter(tree=t)
te = ROOT.TTree('te', 'te')
twe = RTreeWriter(tree=te)
# effi_pp = AliceChargedParticleEfficiency(csystem='pp')
effi_PbPb = None
if args.efficiency:
effi_PbPb = AliceChargedParticleEfficiency(csystem='PbPb')
print(effi_PbPb)
### EVENT LOOP STARTS HERE
for iev in tqdm.tqdm(range(args.nev)):
if not pythia.next():
continue
parts_pythia = pythiafjext.vectorize_select(
pythia, [pythiafjext.kFinal, pythiafjext.kCharged])
parts_gen = parts_selector(parts_pythia)
if effi_PbPb:
parts = effi_PbPb.apply_efficiency(parts_gen)
else:
parts = parts_gen
signal_jets = fj.sorted_by_pt(jet_selector(jet_def(parts)))
if len(signal_jets) < 1:
continue
for sjet in signal_jets:
if args.SDsignal or args.SDsignal_single:
sd_sjet = sd.result(sjet)
pe1 = fj.PseudoJet()
pe2 = fj.PseudoJet()
has_parents = sd_sjet.has_parents(pe1, pe2)
if has_parents:
jparts = fj.vectorPJ()
pe1.set_user_index(0)
pe2.set_user_index(1)
if args.SDsignal_single:
if pe1.pt() > pe2.pt():
jparts.push_back(pe1)
else:
jparts.push_back(pe2)
else:
jparts.push_back(pe1)
jparts.push_back(pe2)
sjets = fj.sorted_by_pt(jet_selector(jet_def(jparts)))
if len(sjets) == 1:
sjet = sjets[0]
else:
continue
else:
continue
if embd:
bg_parts = embd.load_event(offset=10000)
# for p in bg_parts:
# print(p.user_index())
else:
bg_parts = be.generate(offset=10000)
# for p in bg_parts:
# print(p.user_index())
full_event = bg_parts
tmp = [full_event.push_back(psj) for psj in sjet.constituents()]
if cs:
cs_parts = cs.process_event(full_event)
rho = cs.bge_rho.rho()
jarho.analyze_event(cs_parts)
tmp = [
fill_tree_data(ej, twe, sd, rho, iev, pythia.info.weight(),
pythia.info.sigmaGen()) for ej in jarho.jets
]
tmp = [
fill_tree_matched(sjet, ej, tw, sd, rho, iev,
pythia.info.weight(),
pythia.info.sigmaGen())
for ej in jarho.jets
]
else:
jarho.analyze_event(full_event)
rho = jarho.rho
if csjet:
#_csjet = fjcontrib.ConstituentSubtractor(jarho.bg_estimator)
# subtr_jets = [_csjet.result(ej) for ej in jarho.jets]
csjet.set_event_particles(full_event)
#subtr_jets = [csjet.process_jet(ej) for ej in jarho.jets]
#print ('jbyj cs', len(subtr_jets), 'from', len(jarho.jets))
#subtr_jets_wconstits = [_j for _j in subtr_jets if _j.has_constituents()]
#for _j in subtr_jets_wconstits:
# print(len(_j.constituents()))
subtr_jets_wconstits = csjet.process_jets(jarho.jets)
japerjet = JetAnalysisPerJet(
jet_R=jet_R0,
jet_algorithm=fj.antikt_algorithm,
particle_eta_max=max_eta,
input_jets=subtr_jets_wconstits)
# for _j in japerjet.jets:
# for _c in _j.constituents():
# if _c.user_index() >= 0:
# print('user index kept?', _c.user_index())
# # else:
# # print('user index kept?', _c.user_index(), _c.pt())
# _sd_j = sd.result(_j)
# https://phab.hepforge.org/source/fastjetsvn/browse/contrib/contribs/RecursiveTools/trunk/Recluster.cc L 270
# tmp = [fill_tree_matched(sjet, ej, tw, sd, rho, iev, pythia.info.sigmaGen()) for ej in subtr_jets_wcs]
tmp = [
fill_tree_data(ej, twe, sd, rho, iev,
pythia.info.weight(),
pythia.info.sigmaGen())
for ej in japerjet.jets
]
tmp = [
fill_tree_matched(sjet, ej, tw, sd, rho, iev,
pythia.info.weight(),
pythia.info.sigmaGen())
for ej in japerjet.jets
]
else:
tmp = [
fill_tree_data(ej, twe, sd, rho, iev,
pythia.info.weight(),
pythia.info.sigmaGen())
for ej in jarho.jets
]
tmp = [
fill_tree_matched(sjet, ej, tw, sd, rho, iev,
pythia.info.weight(),
pythia.info.sigmaGen())
for ej in jarho.jets
]
pythia.stat()
outf.Write()
outf.Close()
print('[i] written', outf.GetName())
class RTreeWriter(MPBase):
_fj_psj_type = type(fj.PseudoJet())
_fj_psj_vector_type = type(fj.vectorPJ())
_fj_LundDeclustering_type = get_LundDeclusteringType()
# _fj_sdinfo = type(fjcontrib.SDinfo())
def __init__(self, **kwargs):
self.configure_from_args(tree=None,
tree_name=None,
name="RTreeWriter",
file_name="RTreeWriter.root",
fout=None)
super(RTreeWriter, self).__init__(**kwargs)
self._warnings = []
if self.tree is None:
if self.fout is None:
print('[i] new file {}'.format(self.file_name))
self.fout = ROOT.TFile(self.file_name, 'recreate')
self.fout.cd()
else:
self.name = self.fout.GetName()
self.file_name = self.name
self.fout.cd()
if self.tree_name is None:
self.tree_name = 't' + self.name
self.tree = ROOT.TTree(self.tree_name, self.tree_name)
self.branch_containers = {}
def add_warning(self, s):
if s not in self._warnings:
self._warnings.append(s)
def _fill_branch(self, bname, value):
b = self.tree.GetBranch(bname)
if not b:
print('[i] RTreeWriter {} tree {}: creating branch [{}]'.format(
self.name, self.tree.GetName(), bname))
self.branch_containers[bname] = ROOT.std.vector('float')()
b = self.tree.Branch(bname, self.branch_containers[bname])
if b:
# print('filling branch:', bname, 'at', b)
self.branch_containers[bname].push_back(value)
def fill_branches_attribs(self, o, attr_list=[], prefix=''):
if len(attr_list) == 0:
attr_list = o.__dict__
for a in attr_list:
self.fill_branch(prefix + a, getattr(o, a))
def fill_branches(self, **kwargs):
for a in kwargs:
self.fill_branch(bname=a, value=kwargs[a])
def fill_branch(self, bname, value, do_enumerate=False):
# print("FILL:", self.tree_name, bname, value)
if float == type(value) or int == type(value):
self._fill_branch(bname, value)
return
if type(value) in [tuple, list, self._fj_psj_vector_type]:
if do_enumerate:
r = [
self.fill_branch('{}_{}'.format(bname, i), x)
for i, x in enumerate(value)
]
else:
r = [self.fill_branch(bname, x) for x in value]
return
if dict == type(value):
r = [
self.fill_branch('{}_{}'.format(bname, i), x)
for i, x in value.items()
]
return
if self._fj_psj_type == type(value):
if value.has_area():
self.fill_branch(
bname, {
'pt': value.pt(),
'phi': value.phi(),
'eta': value.eta(),
'a': value.area()
})
else:
self.fill_branch(bname, {
'pt': value.pt(),
'phi': value.phi(),
'eta': value.eta()
})
return
if self._fj_LundDeclustering_type == type(value):
self.fill_branch(
bname, {
'm': value.m(),
'z': value.z(),
'Delta': value.Delta(),
'kt': value.kt(),
'kappa': value.kappa(),
'psi': value.psi(),
'p': value.pair(),
's1': value.harder(),
's2': value.softer(),
'tf': value.z() * value.Delta() * value.Delta()
})
return
if bool == type(value):
self._fill_branch(bname, value)
return
try:
_val = float(value)
self._fill_branch(bname, _val)
self.add_warning('converted {} to float for branch {}'.format(
type(value), bname))
return
except:
pass
self.add_warning(
'do not know how to fill tree {} branch {} for type {} - ignored'.
format(self.tree_name, bname, type(value)))
def clear(self):
for k in self.branch_containers:
self.branch_containers[k].clear()
def fill_tree(self):
self.tree.Fill()
self.clear()
def write_and_close(self):
print('[i] writing {}'.format(self.fout.GetName()))
self.fout.Write()
self.fout.Purge()
self.fout.Close()
def __del__(self):
for w in self._warnings:
pwarning(self.tree_name, ':', w)
def main():
parser = argparse.ArgumentParser(description='pythia8 fastjet on the fly',
prog=os.path.basename(__file__))
pyconf.add_standard_pythia_args(parser)
parser.add_argument('--embed',
help='run embedding from a file list',
default='',
type=str)
args = parser.parse_args()
if args.nev < 1:
args.nev = 1
mycfg = []
pythia = pyconf.create_and_init_pythia_from_args(args, mycfg)
part_selection = [pythiafjext.kFinal, pythiafjext.kCharged]
max_eta = 1.
be = None
embd = None
if len(args.embed) > 0:
embd = DataBackgroundIO(file_list=args.embed)
print(embd)
else:
be = BoltzmannEvent(mean_pt=0.6,
multiplicity=2000 * max_eta * 2,
max_eta=max_eta,
max_pt=100)
print(be)
# print the banner first
fj.ClusterSequence.print_banner()
print()
# set up our jet definition and a jet selector
jet_R0 = 0.6
jet_def = fj.JetDefinition(fj.antikt_algorithm, jet_R0)
jet_def_emb = fj.JetDefinition(fj.antikt_algorithm, jet_R0)
jet_selector = fj.SelectorPtMin(10.0) & fj.SelectorAbsEtaMax(1)
fout = ROOT.TFile('pythia_8jet.root', 'recreate')
fout.cd()
hfraction = ROOT.TProfile('hfraction', 'hfraction', 10, 0, 100)
hdpt = ROOT.TProfile('hdpt', 'hdpt', 10, 0, 100)
hfraction2D = ROOT.TH2F('hfraction2D', 'hfraction', 10, 0, 100, 20, 0, 1)
hdpt2D = ROOT.TH2F('hdpt2D', 'hdpt', 10, 0, 100, 20, -1, 0)
hfraction_emb = ROOT.TProfile('hfraction_emb', 'hfraction', 10, 0, 100)
hdpt_emb = ROOT.TProfile('hdpt_emb', 'hdpt', 10, 0, 100)
hfraction2D_emb = ROOT.TH2F('hfraction2D_emb', 'hfraction', 10, 0, 100, 20,
0, 1)
hdpt2D_emb = ROOT.TH2F('hdpt2D_emb', 'hdpt', 10, 0, 100, 20, -1, 0)
for iev in tqdm.tqdm(range(args.nev)):
if not pythia.next():
continue
parts = []
parts = pythiafjext.vectorize_select(pythia, part_selection, 0, False)
jets = fj.sorted_by_pt(jet_selector(jet_def(parts)))
if embd:
bg_parts = embd.load_event(offset=10000)
else:
bg_parts = be.generate(offset=10000)
for j in jets:
_sum_all, _sum_top_n, _fraction_pt = calc_n_lead(j, 8)
hfraction.Fill(j.pt(), _fraction_pt)
hdpt.Fill(j.pt(), (_sum_top_n - _sum_all) / _sum_all)
hfraction2D.Fill(j.pt(), _fraction_pt)
hdpt2D.Fill(j.pt(), (_sum_top_n - _sum_all) / _sum_all)
full_event = fj.vectorPJ()
tmp = [full_event.push_back(psj) for psj in bg_parts]
tmp = [full_event.push_back(psj) for psj in j.constituents()]
embd_jets = fj.sorted_by_pt(jet_selector(jet_def_emb(full_event)))
for jemb in embd_jets:
mpt = fjtools.matched_pt(jemb, j)
if mpt < 0.5:
continue
_sum_all_emb, _sum_top_n_emb, _fraction_pt_emb = calc_n_lead(
jemb, 8)
_fraction_pt_emb = _sum_top_n_emb / _sum_all
hfraction_emb.Fill(jemb.pt(), _fraction_pt)
hdpt_emb.Fill(jemb.pt(),
(_sum_top_n_emb - _sum_all) / _sum_all)
hfraction2D_emb.Fill(jemb.pt(), _fraction_pt)
hdpt2D_emb.Fill(jemb.pt(),
(_sum_top_n_emb - _sum_all) / _sum_all)
fg = ROOT.TF1('fg', 'gaus', 0, 1)
fg.SetParameter(0, 1)
fg.SetParameter(1, 0.8)
fg.SetParameter(2, 0.1)
hfraction2D.FitSlicesY(fg)
hfraction2D_emb.FitSlicesY(fg)
fgdpt = ROOT.TF1('fgdpt', 'gaus', -1, 0)
fgdpt.SetParameter(0, 1)
fgdpt.SetParameter(1, -0.2)
fgdpt.SetParameter(2, 0.1)
hdpt2D.FitSlicesY(fgdpt)
hdpt2D_emb.FitSlicesY(fgdpt)
fout.Write()
fout.Close()
def main():
parser = argparse.ArgumentParser(description='test groomers',
prog=os.path.basename(__file__))
parser.add_argument('-o',
'--output-filename',
default="output.root",
type=str)
parser.add_argument('datalistpp',
help='run through a file list',
default='',
type=str)
parser.add_argument('--datalistAA',
help='run through a file list - embedding mode',
default='',
type=str)
parser.add_argument('--jetR', default=0.4, type=float)
parser.add_argument('--alpha', default=0, type=float)
parser.add_argument('--dRmax', default=0.25, type=float)
parser.add_argument('--overwrite',
help="overwrite output",
default=False,
action='store_true')
parser.add_argument('--jetptcut',
help='remove jets below the cut',
default=50.,
type=float)
parser.add_argument('--nev',
help='number of events to run',
default=0,
type=int)
parser.add_argument('--max-eta',
help='max eta for particles',
default=0.9,
type=float)
parser.add_argument('--npart-cut',
help='npart cut on centrality low,high hint:' +
npart_cents,
default='325,450',
type=str)
args = parser.parse_args()
try:
npart_min = int(args.npart_cut.split(',')[0])
npart_max = int(args.npart_cut.split(',')[1])
except:
perror(
'unable to parse npart centrality selection - two integer numbers with a coma in-between needed - specified:',
args.npart_cut)
return 1
# initialize constituent subtractor
cs = None
if args.dRmax > 0:
cs = CEventSubtractor(alpha=args.alpha,
max_distance=args.dRmax,
max_eta=args.max_eta,
bge_rho_grid_size=0.25,
max_pt_correct=100)
pp_data = DataIO(name='Sim Pythia Detector level',
file_list=args.datalistpp,
random_file_order=False,
tree_name='tree_Particle_gen')
ja_pp = JetAnalysis(jet_R=args.jetR,
jet_algorithm=fj.antikt_algorithm,
jet_pt_min=50.,
particle_eta_max=args.max_eta)
if args.datalistAA:
aa_data = DataBackgroundIO(name='PbPb',
file_list=args.datalistAA,
tree_name='tree_Particle_gen')
ja_emb = JetAnalysis(jet_R=args.jetR,
jet_algorithm=fj.antikt_algorithm,
jet_pt_min=50.,
particle_eta_max=args.max_eta)
ja_aa = JetAnalysis(jet_R=args.jetR,
jet_algorithm=fj.antikt_algorithm,
jet_pt_min=50.,
particle_eta_max=args.max_eta)
dndeta_selector = fj.SelectorAbsEtaMax(1.)
# tg = thg.ThermalGenerator()
print(cs)
# print the banner first
fj.ClusterSequence.print_banner()
print()
gout = GroomerOutput(args.output_filename,
enable_aa_trees=bool(args.datalistAA))
delta_t = 0
start_t = time.time()
iev = 1
while pp_data.load_event(offset=0):
iev = iev + 1
if args.nev > 0:
if iev > args.nev:
iev = iev - 1
break
if iev % 1000 == 0:
delta_t = time.time() - start_t
pinfo('processing event', iev, ' - ev/sec =', iev / delta_t,
'elapsed =', delta_t)
# find jets on detector level
if len(pp_data.particles) < 1:
pwarning(iev, 'pp event skipped N parts', len(pp_data.particles))
continue
ja_pp.analyze_event(pp_data.particles)
if len(ja_pp.jets) < 1:
continue
# pinfo('n particles', len(pp_data.particles))
dndeta0 = dndeta_selector(pp_data.particles)
[
gout.fill_branches(j, syst=0, dndeta=len(dndeta0) / 2.)
for j in ja_pp.jets
]
# pinfo('n jets', len(ja_pp.jets))
if args.datalistAA:
while True:
aa_loaded = aa_data.load_event(offset=10000)
if aa_data.event.npart < npart_min or aa_data.event.npart >= npart_max:
continue
else:
if len(aa_data.particles) < 1:
pwarning(iev, 'AA event skipped N parts',
len(aa_data.particles))
continue
else:
break
if aa_loaded:
ja_aa.analyze_event(aa_data.particles)
dndeta1 = dndeta_selector(aa_data.particles)
if len(ja_aa.jets) > 0:
[
gout.fill_branches(j, syst=1, dndeta=len(dndeta1) / 2.)
for j in ja_aa.jets
]
else:
# pwarning('no jets in AA event?', len(ja_aa.jets), 'while dndeta=', len(dndeta1)/2.)
pass
emb_event = fj.vectorPJ()
[emb_event.push_back(p) for p in pp_data.particles]
[emb_event.push_back(p) for p in aa_data.particles]
rho = 0
if cs:
cs_parts = cs.process_event(emb_event)
rho = cs.bge_rho.rho()
ja_emb.analyze_event(cs_parts)
else:
ja_emb.analyze_event(emb_event)
# matches = [[jpp, jemb] for jpp in ja_pp.jets for jemb in ja_emb.jets if fjtools.matched_pt(jemb, jpp) > 0.5]
# for mj in matches:
# gout.fill_branches(mj[0], syst=2, dndeta=len(dndeta1)/2., rho=rho)
# gout.fill_branches(mj[1], syst=3)
[
gout.fill_branches_prong_matching(j_pp,
j_emb,
dndeta=len(dndeta1) / 2.,
rho=rho)
for j_pp in ja_pp.jets for j_emb in ja_emb.jets
]
delta_t = time.time() - start_t
pinfo('processed events', iev, ' - ev/sec =', iev / delta_t, 'elapsed =',
delta_t)
gout.write()
