def __init__(self, **kwargs):
self.configure_from_args(jet_R=0.4,
jet_algorithm=fj.antikt_algorithm,
particle_eta_max=0.9,
jet_pt_min=0.0,
particles=None,
explicit_ghosts=False)
super(JetAnalysis, self).__init__(**kwargs)
self.particle_selector = fj.SelectorAbsEtaMax(self.particle_eta_max)
self.jet_eta_max = self.particle_eta_max - self.jet_R * 1.05
# self.jet_eta_max = self.particle_eta_max - 0.05
self.jet_def = fj.JetDefinition(self.jet_algorithm, self.jet_R)
self.jet_selector = fj.SelectorPtMin(
self.jet_pt_min) & fj.SelectorAbsEtaMax(self.jet_eta_max)
if self.explicit_ghosts:
self.jet_area_def = fj.AreaDefinition(
fj.active_area_explicit_ghosts,
fj.GhostedAreaSpec(self.particle_eta_max))
else:
self.jet_area_def = fj.AreaDefinition(
fj.active_area, fj.GhostedAreaSpec(self.particle_eta_max))
if self.particles:
self.analyze_event(self.particles)
def __init__(self, **kwargs):
self.configure_from_args(jet_R=0.4,
jet_algorithm=fj.antikt_algorithm,
particle_eta_max=0.9,
particles=None)
super(JetAnalysis, self).__init__(**kwargs)
self.bg_rho_range = fj.SelectorAbsEtaMax(self.particle_eta_max)
self.bg_jet_def = fj.JetDefinition(fj.kt_algorithm, self.jet_R)
self.bg_area_def = fj.AreaDefinition(
fj.active_area_explicit_ghosts,
fj.GhostedAreaSpec(self.particle_eta_max))
self.bg_estimator = fj.JetMedianBackgroundEstimator(
self.bg_rho_range, self.bg_jet_def, self.bg_area_def)
self.rho = 0
self.jet_eta_max = self.particle_eta_max - self.jet_R * 1.05
self.jet_def = fj.JetDefinition(self.jet_algorithm, self.jet_R)
self.jet_selector = fj.SelectorPtMin(0.0) & fj.SelectorAbsEtaMax(
self.jet_eta_max)
self.jet_area_def = fj.AreaDefinition(
fj.active_area_explicit_ghosts,
fj.GhostedAreaSpec(self.particle_eta_max))
if self.particles:
self.analyze_event(self.particles)
def __init__(self, **kwargs):
self.configure_from_args(tree_name='tree_Particle',
tree_name_gen='tree_Particle_gen',
args=None)
super(Embedding, self).__init__(**kwargs)
self.copy_attributes(self.args)
self.jet_def = fj.JetDefinition(fj.antikt_algorithm, self.jetR)
if self.benchmark:
self.jet_selector = fj.SelectorPtMin(80.0) & fj.SelectorPtMax(
100.0) & fj.SelectorAbsEtaMax(self.max_eta - 1.05 * self.jetR)
# jet_selector_cs = fj.SelectorPtMin(50.0) & fj.SelectorAbsEtaMax(max_eta - 1.05 * self.jetR)
else:
self.jet_selector = fj.SelectorAbsEtaMax(self.max_eta -
1.05 * self.jetR)
self.parts_selector = fj.SelectorAbsEtaMax(self.max_eta)
self.output = EmbeddingOutput(args=self.args)
# self.output.copy_attributes(self)
self.sd = fjcontrib.SoftDrop(0, self.sd_zcut, self.jetR)
self.ja_part = JetAnalysis(jet_R=self.jetR,
jet_algorithm=fj.antikt_algorithm,
jet_pt_min=5.,
particle_eta_max=self.max_eta)
self.ja_det = JetAnalysis(jet_R=self.jetR,
jet_algorithm=fj.antikt_algorithm,
jet_pt_min=self.jetptcut,
particle_eta_max=self.max_eta)
self.ja_hybrid = JetAnalysis(jet_R=self.jetR,
jet_algorithm=fj.antikt_algorithm,
jet_pt_min=5.,
particle_eta_max=self.max_eta)
self.dataPbPb = DataBackgroundIO(name='Data PbPb',
file_list=self.datalistAA)
self.det_sim = DataIO(name='Sim Pythia Detector level',
file_list=self.simulationpp,
random_file_order=False)
self.part_sim = DataIO(name='Sim Pythia Particle level',
file_list=self.simulationpp,
random_file_order=False,
tree_name='tree_Particle_gen')
self.cs = None
if self.dRmax > 0:
self.cs = CEventSubtractor(alpha=self.alpha,
max_distance=self.dRmax,
max_eta=self.max_eta,
bge_rho_grid_size=0.25,
max_pt_correct=100)
def main():
parser = argparse.ArgumentParser(description='pythia8 fastjet on the fly', prog=os.path.basename(__file__))
pyconf.add_standard_pythia_args(parser)
args = parser.parse_args()
# 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)
jet_selector = fj.SelectorPtMin(5.0) & fj.SelectorAbsEtaMax(2)
print(jet_def)
all_jets = []
# mycfg = ['PhaseSpace:pThatMin = 100']
mycfg = []
pythia = pyconf.create_and_init_pythia_from_args(args, mycfg)
if args.nev < 100:
args.nev = 100
for i in tqdm.tqdm(range(args.nev)):
if not pythia.next():
continue
parts = pythiafjext.vectorize(pythia, True, -1, 1, False)
jets = jet_selector(jet_def(parts))
all_jets.extend(jets)
pythia.stat()
jet_def_lund = fj.JetDefinition(fj.cambridge_algorithm, 1.0)
lund_gen = fjcontrib.LundGenerator(jet_def_lund)
print('making lund diagram for all jets...')
lunds = [lund_gen.result(j) for j in all_jets]
print('listing lund plane points... Delta, kt - for {} selected jets'.format(len(all_jets)))
for l in lunds:
print ('- jet pT={0:5.2f} eta={1:5.2f}'.format(l[0].pair().perp(), l[0].pair().eta()))
print (' Deltas={}'.format([s.Delta() for s in l]))
print (' kts={}'.format([s.Delta() for s in l]))
print ( )
print('[i] reclustering and using soft drop...')
jet_def_rc = fj.JetDefinition(fj.cambridge_algorithm, 1.0)
print('Reclustering:', jet_def_rc)
rc = fjcontrib.Recluster(jet_def_rc, True)
sd = fjcontrib.SoftDrop(0, 0.1, 1.0)
for i,j in enumerate(all_jets):
j_rc = rc.result(j)
print()
print('- [{0:3d}] orig pT={1:10.3f} reclustered pT={2:10.3f}'.format(i, j.perp(), j_rc.perp()))
j_sd = sd.result(j)
print(' |-> after soft drop pT={0:10.3f} delta={1:10.3f}'.format(j_sd.perp(), j_sd.perp() - j.perp()))
sd_info = fjcontrib.get_SD_jet_info(j_sd)
print(" |-> SD jet params z={0:10.3f} dR={1:10.3f} mu={2:10.3f}".format(sd_info.z, sd_info.dR, sd_info.mu))
def __init__(self, **kwargs):
self.fout = None
super(HFAnalysisInvMass, self).__init__(**kwargs)
self.fout = ROOT.TFile(self.name+'.root', 'recreate')
self.fout.cd()
# self.hinvmass = ROOT.TH1F('hinvmass', 'hinvmass', 400, 1.5, 2.5)
# self.hinvmass.Sumw2()
# self.hinvmasspt = ROOT.TH2F('hinvmasspt', 'hinvmasspt', 400, 1.5, 2.5, 50, 2, 12)
# self.hinvmasspt.Sumw2()
self.tw = treewriter.RTreeWriter(tree_name='d0', fout=self.fout)
# jet stuff
max_eta = 0.9
self.parts_selector = fj.SelectorPtMin(0.15) & fj.SelectorPtMax(100.0) & fj.SelectorAbsEtaMax(max_eta)
jet_R0 = 0.4
self.jet_selector = fj.SelectorPtMin(5.0) & fj.SelectorPtMax(100.0) & fj.SelectorAbsEtaMax(max_eta - 1.05 * jet_R0)
self.jarho = JetAnalysisWithRho(jet_R=jet_R0, jet_algorithm=fj.antikt_algorithm, particle_eta_max=max_eta)
def main(args):
nevents = args.nevents
sconfig_pythia = get_pythia_config(args)
if args.generate:
pythia = create_and_init_pythia(sconfig_pythia)
if not pythia:
return
all_jets = []
for iEvent in tqdm(range(nevents), 'event'):
if not pythia.next(): continue
print("[i] done generating")
if args.write:
pythia = create_and_init_pythia(sconfig_pythia)
if not pythia:
return
pyhepmcwriter = mp.Pythia8HepMCWrapper(args.write)
all_jets = []
for iEvent in tqdm(range(nevents), 'event'):
if not pythia.next(): continue
pyhepmcwriter.fillEvent(pythia)
print("[i] done writing to {}".format(args.write))
if args.read:
import pyhepmc_ng
input = pyhepmc_ng.ReaderAsciiHepMC2(args.read)
if input.failed():
print("[error] unable to read from {}".format(args.read))
return
# print the banner first
fj.ClusterSequence.print_banner()
print()
jet_R0 = 0.4
jet_def = fj.JetDefinition(fj.antikt_algorithm, jet_R0)
jet_selector = fj.SelectorPtMin(100.0) & fj.SelectorPtMax(
200.0) & fj.SelectorAbsEtaMax(1)
event = pyhepmc_ng.GenEvent()
pbar = tqdm(range(nevents))
while not input.failed():
e = input.read_event(event)
if input.failed():
break
fjparts = []
for i, p in enumerate(event.particles):
if p.status == 1:
psj = fj.PseudoJet(p.momentum.px, p.momentum.py,
p.momentum.pz, p.momentum.e)
psj.set_user_index(i)
fjparts.append(psj)
jets = jet_selector(jet_def(fjparts))
pbar.update()
def get_event(self):
if not self.pythia:
return None
parts_selector = fj.SelectorAbsEtaMax(self.eta_max)
jet_selector = fj.SelectorPtMin(
self.jet_pt_min) & fj.SelectorAbsEtaMax(self.eta_max -
1.05 * self.jet_R0)
jet_def = fj.JetDefinition(fj.antikt_algorithm, self.jet_R0)
while True:
if not self.pythia.next():
continue
self.parts_pythia = pythiafjext.vectorize_select(
self.pythia, [pythiafjext.kFinal])
parts_gen = parts_selector(self.parts_pythia)
signal_jets = fj.sorted_by_pt(
jet_selector(jet_def(self.parts_pythia)))
if len(signal_jets) < 1:
continue
else:
break
return self.parts_pythia
def main():
parser = argparse.ArgumentParser(description='pythia8 in python',
prog=os.path.basename(__file__))
pyconf.add_standard_pythia_args(parser)
args = parser.parse_args()
mycfg = []
pythia = pyconf.create_and_init_pythia_from_args(args, mycfg)
max_eta_hadron = 3
jet_R0 = 0.4
jet_selector = fj.SelectorPtMin(100.0) & fj.SelectorPtMax(
125.0) & fj.SelectorAbsEtaMax(max_eta_hadron - 1.05 * jet_R0)
parts_selector_h = fj.SelectorAbsEtaMax(max_eta_hadron)
fj.ClusterSequence.print_banner()
jet_def = fj.JetDefinition(fj.antikt_algorithm, jet_R0)
pbar = tqdm.tqdm(range(args.nev))
for i in pbar:
if not pythia.next():
pbar.update(-1)
continue
parts_pythia_h = pythiafjext.vectorize_select(pythia,
[pythiafjext.kFinal], 0,
False)
parts_pythia_h_selected = parts_selector_h(parts_pythia_h)
jets_h = fj.sorted_by_pt(jet_selector(
jet_def(parts_pythia_h_selected)))
if len(jets_h) < 1:
continue
# do your things with jets here...
pythia.stat()
pythia.settings.writeFile(args.py_cmnd_out)
def init_jet_tools(self):
for jetR in self.jetR_list:
jetR_str = str(jetR).replace('.', '')
if not self.no_tree:
# Initialize tree writer
name = 'particle_unscaled_R%s' % jetR_str
t = ROOT.TTree(name, name)
setattr(self, "t_R%s" % jetR_str, t)
tw = RTreeWriter(tree=t)
setattr(self, "tw_R%s" % jetR_str, tw)
# set up our jet definition and a jet selector
jet_def = fj.JetDefinition(fj.antikt_algorithm, jetR)
setattr(self, "jet_def_R%s" % jetR_str, jet_def)
print(jet_def)
pwarning('max eta for particles after hadronization set to',
self.max_eta_hadron)
parts_selector_h = fj.SelectorAbsEtaMax(self.max_eta_hadron)
for jetR in self.jetR_list:
jetR_str = str(jetR).replace('.', '')
jet_selector = fj.SelectorPtMin(5.0) & \
fj.SelectorAbsEtaMax(self.max_eta_hadron - jetR)
setattr(self, "jet_selector_R%s" % jetR_str, jet_selector)
#max_eta_parton = self.max_eta_hadron + 2. * jetR
#setattr(self, "max_eta_parton_R%s" % jetR_str, max_eta_parton)
#pwarning("Max eta for partons with jet R =", jetR, "set to", max_eta_parton)
#parts_selector_p = fj.SelectorAbsEtaMax(max_eta_parton)
#setattr(self, "parts_selector_p_R%s" % jetR_str, parts_selector_p)
count1 = 0 # Number of jets rejected from ch-h matching
setattr(self, "count1_R%s" % jetR_str, count1)
count2 = 0 # Number of jets rejected from h-p matching
setattr(self, "count2_R%s" % jetR_str, count2)
def init_jet_tools(self):
for jetR in self.jetR_list:
jetR_str = str(jetR).replace('.', '')
# set up our jet definition and a jet selector
jet_def = fj.JetDefinition(fj.antikt_algorithm, jetR)
setattr(self, "jet_def_R%s" % jetR_str, jet_def)
print(jet_def)
pwarning('max eta for particles after hadronization set to', self.max_eta_hadron)
parts_selector_h = fj.SelectorAbsEtaMax(self.max_eta_hadron)
for jetR in self.jetR_list:
jetR_str = str(jetR).replace('.', '')
jet_selector = fj.SelectorPtMin(5.0) & \
fj.SelectorAbsEtaMax(self.max_eta_hadron - jetR)
setattr(self, "jet_selector_R%s" % jetR_str, jet_selector)
count1 = 0 # Number of jets rejected from ch-h matching
setattr(self, "count1_R%s" % jetR_str, count1)
count2 = 0 # Number of jets rejected from h-p matching
setattr(self, "count2_R%s" % jetR_str, count2)
def init(self):
"""
must be called before next(). Initializes the generator, and creates
all reused fastjet objects (selectors, jet definition). Returns the
status of the pythia generator
"""
# first initialize Pythia
self.gen.readString("Beams:eCM = 200.0")
self.gen.readString("HardQCD:all = on")
self.gen.readString("Random:setSeed = on")
self.gen.readString('Random:seed = ' + str(self.seed))
self.gen.readString('PhaseSpace:pTHatMin = ' + str(self.pt_hat_min))
self.gen.readString('PhaseSpace:pTHatMax = ' + str(self.pt_hat_max))
for setting in self.gen_args:
try:
self.gen.readString(setting)
except:
print('pythia read string failed')
# create jet definition
self.jet_def = fastjet.JetDefinition(self.jet_alg, self.jet_radius)
# create fastjet selectors for tracks and jets
self.track_selector = (
fastjet.SelectorAbsEtaMax(self.track_eta_max) *
fastjet.SelectorPtRange(self.track_pt_min, self.track_pt_max))
self.jet_selector = (fastjet.SelectorAbsEtaMax(self.jet_eta_max) *
fastjet.SelectorPtMin(self.jet_pt_min))
self.initialized = self.gen.init()
if not self.star_sim and not self.gauss_smear and not self.tpc_sim:
print('Warning: no detector simulation method has been chosen',
'disabling detector simulation')
return self.initialized
def main_make(args):
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
outf = ROOT.TFile(args.output, 'recreate')
outf.cd()
bgestim = BackgroundEstimator(name='bg_estim', grid_size=0.1, particle_eta_max=max_eta)
print(bgestim)
be = None
data = None
if len(args.data) > 0:
data = DataIO(file_list=args.data)
print(data)
else:
be = BoltzmannEvent(mean_pt=0.6, multiplicity=2000 * max_eta * 2, max_eta=max_eta, max_pt=100)
print(be)
parts_selector = fj.SelectorAbsEtaMax(max_eta)
if args.nev < 1:
args.nev = 1
### EVENT LOOP STARTS HERE
for iev in tqdm.tqdm(range(args.nev)):
if data:
bg_parts = data.load_event(offset=10000)
else:
if be:
bg_parts = be.generate(offset=10000)
bgestim.fill_grid(bg_parts)
outf.cd()
if be:
be.write()
bgestim.write()
outf.Write()
outf.Close()
print('[i] written', outf.GetName())
def main():
input_file = "$HOME/data/jetscape/test_out.hepmc"
if len(sys.argv) > 1:
input_file = sys.argv[1]
input_file = os.path.expandvars(input_file)
print('[i] reading from:', input_file)
# input = pyhepmc_ng.ReaderAsciiHepMC2(input_file)
input = pyhepmc_ng.ReaderAscii(input_file)
if input.failed():
print("[error] unable to read from {}".format(input_file))
return
nevents = 1000
# print the banner first
fj.ClusterSequence.print_banner()
print()
jet_R0 = 0.4
jet_def = fj.JetDefinition(fj.antikt_algorithm, jet_R0)
jet_selector = fj.SelectorPtMin(0.0) & fj.SelectorPtMax(
200.0) & fj.SelectorAbsEtaMax(3)
all_jets = []
event = pyhepmc_ng.GenEvent()
pbar = tqdm.tqdm(range(nevents))
while not input.failed():
e = input.read_event(event)
if input.failed():
break
fjparts = []
for i, p in enumerate(event.particles):
if p.status == 1 and not p.end_vertex:
psj = fj.PseudoJet(p.momentum.px, p.momentum.py, p.momentum.pz,
p.momentum.e)
psj.set_user_index(i)
fjparts.append(psj)
jets = jet_selector(jet_def(fjparts))
all_jets.append([[j.pt(), j.eta()] for j in jets])
pbar.update()
for j in jets:
hjetpt.Fill(j.perp())
if pbar.n >= nevents:
break
pbar.close()
def main_jets(args):
outfname = '{}_output.root'.format(args.read).replace('.dat', '')
print("output file: {}".format(outfname))
foutput = r.TFile(outfname, "recreate")
foutput.cd()
lbins = logbins(1., 100, 10)
hjetpt = r.TH1F('hjetpt', 'hjetpt', 10, lbins)
input = pyhepmc_ng.ReaderAsciiHepMC2(args.read)
if input.failed():
print ("[error] unable to read from {}".format(args.read))
return
# print the banner first
fj.ClusterSequence.print_banner()
print()
jet_R0 = 0.4
jet_def = fj.JetDefinition(fj.antikt_algorithm, jet_R0)
jet_selector = fj.SelectorPtMin(0.0) & fj.SelectorPtMax(200.0) & fj.SelectorAbsEtaMax(3)
all_jets = []
event = pyhepmc_ng.GenEvent()
pbar = tqdm(range(args.nevents))
while not input.failed():
e = input.read_event(event)
if input.failed():
break
fjparts = []
for i,p in enumerate(event.particles):
if p.status == 1 and not p.end_vertex:
psj = fj.PseudoJet(p.momentum.px, p.momentum.py, p.momentum.pz, p.momentum.e)
psj.set_user_index(i)
fjparts.append(psj)
jets = jet_selector(jet_def(fjparts))
all_jets.append([ [j.pt(), j.eta()] for j in jets])
pbar.update()
for j in jets:
hjetpt.Fill(j.perp())
if pbar.n >= args.nevents:
break
foutput.Write()
foutput.Close()
joblib.dump(all_jets, outfname.replace(".root", ".joblib"))
def main():
fj.ClusterSequence.print_banner()
print()
sconfig_pythia = [
"Beams:eCM = 8000.", "HardQCD:all = on", "PhaseSpace:pTHatMin = 20."
]
pythia = create_and_init_pythia(sconfig_pythia)
jet_R0 = 0.4
jet_def = fj.JetDefinition(fj.antikt_algorithm, jet_R0)
jet_selector = fj.SelectorPtMin(20.0) & fj.SelectorPtMax(
40.0) & fj.SelectorAbsEtaMax(1)
# sd = rt.SoftDrop(0, 0.1, 1.0)
all_jets = []
for iEvent in tqdm(range(1000), 'event'):
if not pythia.next():
continue
parts = pyfj.vectorize(pythia, True, -1, 1, True)
jets = jet_selector(jet_def(parts))
all_jets.extend(jets)
print_jets(all_jets)
def __init__(self, **kwargs):
self.configure_from_args(jet_particle_eta_max = 0.9,
output='hjet.root',
trigger_ranges = [ [0, 1e3], [6, 7] , [12, 22], [20, 30] ],
jet_Rs = [0.2, 0.4, 0.6])
super(HJetAnalysis, self).__init__(**kwargs)
self.fout = r.TFile(self.output, 'RECREATE')
self.fout.cd()
self.event_output = RTreeWriter(tree_name='tev', fout=self.fout)
self.hmV0M = r.TH1F('hmV0M', 'hmV0M', 1000, 0, 1000)
self.hmV0A = r.TH1F('hmV0A', 'hmV0A', 1000, 0, 1000)
self.hmV0C = r.TH1F('hmV0C', 'hmV0C', 1000, 0, 1000)
self.jet_particle_selector = fj.SelectorAbsEtaMax(self.jet_particle_eta_max)
self.jet_ans = []
self.hjet_ts = []
for jR in self.jet_Rs:
j_ana = JetAnalysis(jet_R=jR, particle_eta_max=self.jet_particle_eta_max)
self.jet_ans.append(j_ana)
for tr in self.trigger_ranges:
hjet_tree = HJetTree(fout=self.fout, trigger_range=tr, jet_ana=j_ana)
self.hjet_ts.append(hjet_tree)
def main():
parser = argparse.ArgumentParser(description='pythia8 fastjet on the fly',
prog=os.path.basename(__file__))
pyconf.add_standard_pythia_args(parser)
_default_output_filename = os.path.basename(__file__).replace(
".py", "") + "_output.root"
parser.add_argument('--output', default=_default_output_filename, type=str)
parser.add_argument('--debug', default=0, type=int)
args = parser.parse_args()
# 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_selector = fj.SelectorPtMin(2.0) & fj.SelectorAbsEtaMax(2)
print(jet_def)
jet_def_lund = fj.JetDefinition(fj.cambridge_algorithm, jet_R0)
lund_gen = fjcontrib.LundGenerator(jet_def_lund)
print(jet_def_lund)
print(lund_gen)
outf = ROOT.TFile(args.output, 'recreate')
outf.cd()
t = ROOT.TTree('t', 't')
tw = RTreeWriter(tree=t)
# mycfg = ['PhaseSpace:pThatMin = 100']
mycfg = []
pythia = pyconf.create_and_init_pythia_from_args(args, mycfg)
if args.nev < 100:
args.nev = 100
for i in tqdm.tqdm(range(args.nev)):
if not pythia.next():
continue
if args.debug:
pwarning('-- event', i)
# parts = pythiafjext.vectorize(pythia, True, -1, 1, False)
parts = pythiafjext.vectorize_select(pythia, [pythiafjext.kFinal], 0,
True)
if args.debug > 5:
parts = pythiafjext.vectorize_select(pythia, [pythiafjext.kHadron],
0, True)
if args.debug > 10:
parts = pythiafjext.vectorize_select(pythia, [pythiafjext.kAny], 0,
True)
if args.debug > 0:
for p in parts:
pypart = pythiafjext.getPythia8Particle(p)
if pypart.name()[:2] == 'D0':
pinfo(pypart.name(), pypart.id(), pypart.status(),
'final =?', pypart.isFinal())
jets = jet_selector(jet_def(parts))
for j in jets:
isD0_lead = False
lead_part = fj.sorted_by_E(j.constituents())[0]
pypart = pythiafjext.getPythia8Particle(lead_part)
if args.debug:
pinfo('leading id is', pypart.id(), pypart.name(), 'jet', j)
if abs(pypart.id()) == 421:
# pinfo('leading D0')
isD0_lead = True
l = lund_gen.result(j)
if len(l) > 0:
tw.fill_branch('Epair', [s.pair().e() for s in l])
tw.fill_branch('z', [s.z() for s in l])
tw.fill_branch('kt', [s.kt() for s in l])
tw.fill_branch('delta', [s.Delta() for s in l])
tw.fill_branch('D0lead', isD0_lead)
tw.fill_branch('lead_id', pypart.id())
tw.fill_tree()
else:
if args.debug:
pwarning("len of a lund is less than 1?", len(l), l)
pythia.stat()
outf.Write()
outf.Close()
print('[i] written', outf.GetName())
def main():
parser = argparse.ArgumentParser(description='pythia8 fastjet on the fly',
prog=os.path.basename(__file__))
pyconf.add_standard_pythia_args(parser)
# Could use --py-seed
parser.add_argument('--user-seed', help='PYTHIA starting seed', default=1111, type=int)
parser.add_argument('--output', default="output.root", type=str)
parser.add_argument('--sd_beta', help='SoftDrop beta', default=None, type=float)
parser.add_argument('--jetR', help='Jet radius/resolution parameter', default=0.4, type=float)
parser.add_argument('--no-match-level', help="Save simulation for only one level with " + \
"no matching. Options: 'p', 'h', 'ch'", default=None, type=str)
parser.add_argument('--p-ch-MPI', help="Match between parton level (no MPI) and charged " + \
"hadron level (with MPI) for ALICE response characterization",
action='store_true', default=False)
args = parser.parse_args()
level = args.no_match_level
if args.p_ch_MPI:
if level:
print("ERROR: --no-match-level and --p-ch-MPI cannot be set simultaneously.")
exit(1)
if level not in [None, 'p', 'h', 'ch']:
print("ERROR: Unrecognized type %s. Please use 'p', 'h', or 'ch'" % args.type_only)
exit(1)
# Angularity beta values
betas = [1, 1.5, 2, 3]
if args.user_seed < 0:
args.user_seed = 1111
pinfo('user seed for pythia', args.user_seed)
# mycfg = ['PhaseSpace:pThatMin = 100']
mycfg = ['Random:setSeed=on', 'Random:seed={}'.format(args.user_seed)]
mycfg.append('HadronLevel:all=off')
# Have at least 1 event
if args.nev < 1:
args.nev = 1
if args.p_ch_MPI:
d = vars(args)
d['py_noMPI'] = True
pythia_noMPI = pyconf.create_and_init_pythia_from_args(args, mycfg)
args_MPI = copy.deepcopy(args)
d = vars(args_MPI)
d['py_noMPI'] = False
pythia = pyconf.create_and_init_pythia_from_args(args_MPI, mycfg)
else:
pythia = pyconf.create_and_init_pythia_from_args(args, mycfg)
# print the banner first
fj.ClusterSequence.print_banner()
print()
# set up our jet definition and a jet selector
jet_R0 = args.jetR
jet_def = fj.JetDefinition(fj.antikt_algorithm, jet_R0)
print(jet_def)
# hadron level - ALICE
max_eta_hadron = 0.9
pwarning('max eta for particles after hadronization set to', max_eta_hadron)
parts_selector_h = fj.SelectorAbsEtaMax(max_eta_hadron)
jet_selector = fj.SelectorPtMin(5.0) #& fj.SelectorAbsEtaMax(max_eta_hadron - jet_R0)
max_eta_parton = max_eta_hadron + 2. * jet_R0
pwarning('max eta for partons set to', max_eta_parton)
parts_selector_p = fj.SelectorAbsEtaMax(max_eta_parton)
if not args.sd_beta is None:
args.output = args.output.replace('.root', '_sdbeta{}.root'.format(args.sd_beta))
outf = ROOT.TFile(args.output, 'recreate')
outf.cd()
t = ROOT.TTree('t', 't')
tw = RTreeWriter(tree=t)
count1 = 0
count2 = 0
# event loop
for iev in range(args.nev): #tqdm.tqdm(range(args.nev)):
if not pythia.next():
if args.p_ch_MPI:
pythia_noMPI.next()
continue
if args.p_ch_MPI and not pythia_noMPI.next():
continue
parts_pythia_p = pythiafjext.vectorize_select(pythia, [pythiafjext.kFinal], 0, True)
parts_pythia_p_selected = parts_selector_p(parts_pythia_p)
if args.p_ch_MPI:
parts_pythia_p = pythiafjext.vectorize_select(pythia_noMPI, [pythiafjext.kFinal], 0, True)
parts_pythia_p_selected = parts_selector_p(parts_pythia_p)
hstatus = pythia.forceHadronLevel()
if not hstatus:
#pwarning('forceHadronLevel false event', iev)
continue
# parts_pythia_h = pythiafjext.vectorize_select(
# pythia, [pythiafjext.kHadron, pythiafjext.kCharged])
parts_pythia_h = pythiafjext.vectorize_select(pythia, [pythiafjext.kFinal], 0, True)
parts_pythia_h_selected = parts_selector_h(parts_pythia_h)
parts_pythia_hch = pythiafjext.vectorize_select(
pythia, [pythiafjext.kFinal, pythiafjext.kCharged], 0, True)
parts_pythia_hch_selected = parts_selector_h(parts_pythia_hch)
# pinfo('debug partons...')
# for p in parts_pythia_p_selected:
# pyp = pythiafjext.getPythia8Particle(p)
# print(pyp.name())
# pinfo('debug hadrons...')
# for p in parts_pythia_h_selected:
# pyp = pythiafjext.getPythia8Particle(p)
# print(pyp.name())
# pinfo('debug ch. hadrons...')
# for p in parts_pythia_hch_selected:
# pyp = pythiafjext.getPythia8Particle(p)
# print(pyp.name())
# parts = pythiafjext.vectorize(pythia, True, -1, 1, False)
jets_p = fj.sorted_by_pt(jet_selector(jet_def(parts_pythia_p)))
jets_h = fj.sorted_by_pt(jet_selector(jet_def(parts_pythia_h)))
jets_ch = fj.sorted_by_pt(jet_selector(jet_def(parts_pythia_hch)))
if level: # Only save info at one level w/o matching
jets = locals()["jets_%s" % level]
for jet in jets:
tw.fill_branch('iev', iev)
tw.fill_branch(level, jet)
kappa = 1
for beta in betas:
label = str(beta).replace('.', '')
tw.fill_branch('l_%s_%s' % (level, label),
lambda_beta_kappa(jet, jet_R0, beta, kappa))
continue
if not args.sd_beta is None:
sd = fjcontrib.SoftDrop(args.sd_beta, 0.1, jet_R0)
for i,jchh in enumerate(jets_ch):
# match hadron (full) jet
drhh_list = []
for j, jh in enumerate(jets_h):
drhh = jchh.delta_R(jh)
if drhh < jet_R0 / 2.:
drhh_list.append((j,jh))
if len(drhh_list) != 1:
count1 += 1
else: # Require unique match
j, jh = drhh_list[0]
# match parton level jet
dr_list = []
for k, jp in enumerate(jets_p):
dr = jh.delta_R(jp)
if dr < jet_R0 / 2.:
dr_list.append((k, jp))
if len(dr_list) != 1:
count2 += 1
else:
k, jp = dr_list[0]
# pwarning('event', iev)
# pinfo('matched jets: ch.h:', jchh.pt(), 'h:', jh.pt(),
# 'p:', jp.pt(), 'dr:', dr)
tw.fill_branch('iev', iev)
tw.fill_branch('ch', jchh)
tw.fill_branch('h', jh)
tw.fill_branch('p', jp)
kappa = 1
for beta in betas:
label = str(beta).replace('.', '')
tw.fill_branch("l_ch_%s" % label,
lambda_beta_kappa(jchh, jet_R0, beta, kappa))
tw.fill_branch("l_h_%s" % label,
lambda_beta_kappa(jh, jet_R0, beta, kappa))
tw.fill_branch("l_p_%s" % label,
lambda_beta_kappa(jp, jet_R0, beta, kappa))
if not args.sd_beta is None:
jchh_sd = sd.result(jchh)
jchh_sd_info = fjcontrib.get_SD_jet_info(jchh_sd)
jh_sd = sd.result(jh)
jh_sd_info = fjcontrib.get_SD_jet_info(jh_sd)
jp_sd = sd.result(jp)
jp_sd_info = fjcontrib.get_SD_jet_info(jp_sd)
tw.fill_branch('p_zg', jp_sd_info.z)
tw.fill_branch('p_Rg', jp_sd_info.dR)
tw.fill_branch('p_thg', jp_sd_info.dR/jet_R0)
tw.fill_branch('p_mug', jp_sd_info.mu)
tw.fill_branch('h_zg', jh_sd_info.z)
tw.fill_branch('h_Rg', jh_sd_info.dR)
tw.fill_branch('h_thg', jh_sd_info.dR/jet_R0)
tw.fill_branch('h_mug', jh_sd_info.mu)
tw.fill_branch('ch_zg', jchh_sd_info.z)
tw.fill_branch('ch_Rg', jchh_sd_info.dR)
tw.fill_branch('ch_thg', jchh_sd_info.dR/jet_R0)
tw.fill_branch('ch_mug', jchh_sd_info.mu)
#print(" |-> SD jet params z={0:10.3f} dR={1:10.3f} mu={2:10.3f}".format(
# sd_info.z, sd_info.dR, sd_info.mu))
tw.fill_tree()
if args.p_ch_MPI:
pythia_noMPI.stat()
pythia.stat()
print("%i jets cut at first match criteria; %i jets cut at second match criteria." %
(count1, count2))
outf.Write()
outf.Close()
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('--nw',
help="no warn",
default=True,
action='store_true')
parser.add_argument('--ignore-mycfg',
help="ignore some settings hardcoded here",
default=False,
action='store_true')
parser.add_argument('--enable-background',
help="enable background calc",
default=False,
action='store_true')
parser.add_argument('--output',
help="output file name",
default='leadsj_vs_zloss.root',
type=str)
parser.add_argument('--jetptmin',
help="jet pt minimum",
default=-1,
type=float)
parser.add_argument('--jetptmax',
help="jet pt maximum",
default=1e6,
type=float)
parser.add_argument('--eta', help="jet eta max", default=2.4, type=float)
parser.add_argument(
'--kt',
help="use kT algorithm instead of anti-kT for the subjets",
default=False,
action='store_true')
args = parser.parse_args()
# 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)
jet_selector = fj.SelectorPtMin(args.py_pthatmin) & fj.SelectorPtMax(
1000.0) & fj.SelectorAbsEtaMax(args.eta - jet_R0)
mycfg = []
if args.jetptmin > 0:
mycfg = ['PhaseSpace:pThatMin = {}'.format(args.jetptmin)]
jet_selector = fj.SelectorPtMin(args.jetptmin) & fj.SelectorPtMax(
args.jetptmax) & fj.SelectorAbsEtaMax(args.eta - jet_R0)
print(jet_def)
if args.ignore_mycfg:
mycfg = []
pythia = pyconf.create_and_init_pythia_from_args(args, mycfg)
if not pythia:
perror("pythia initialization failed.")
return
nbins = 20
# sjrs = [0.001 + x * 0.04 for x in range(0, nbins)]
sjrs = logbins(0.001, jet_R0, nbins)
print(sjrs)
print('log(1/r) :', [ROOT.TMath.Log(1 / r) for r in sjrs])
sjdefs = dict()
for sjr in sjrs:
if args.kt:
_jet_def = fj.JetDefinition(fj.kt_algorithm, sjr)
else:
_jet_def = fj.JetDefinition(fj.antikt_algorithm, sjr)
sjdefs[sjr] = _jet_def
# tw = treewriter.RTreeWriter(name = 'lsjvsx', file_name = 'leadsj_vs_x.root')
tw = treewriter.RTreeWriter(name='lsjvszloss', file_name=args.output)
tw.fout.cd()
h_zloss_r_q = dict()
h_zloss_r_g = dict()
for sjr in sjrs:
sname = 'h_zloss_glue_{}'.format(sjr)
_h_zloss_r_g = ROOT.TH1F(sname, sname, len(sjrs), 0., 1.)
h_zloss_r_g[sjr] = _h_zloss_r_g
sname = 'h_zloss_quark_{}'.format(sjr)
_h_zloss_r_q = ROOT.TH1F(sname, sname, len(sjrs), 0., 1.)
h_zloss_r_q[sjr] = _h_zloss_r_q
lbins = logbins(ROOT.TMath.Log(1. / jet_R0), ROOT.TMath.Log(1. / sjrs[0]),
nbins)
print('lbins:', lbins)
sname = 'prof_zloss_vs_r_any'
prof_a = ROOT.TProfile(sname, sname, nbins, 0, jet_R0)
prof_a_log = ROOT.TProfile(sname + '_log', sname + '_log', nbins, lbins)
sname = 'prof_zloss_vs_r_glue'
prof_g = ROOT.TProfile(sname, sname, nbins, 0, jet_R0)
prof_g_log = ROOT.TProfile(sname + '_log', sname + '_log', nbins, lbins)
sname = 'prof_zloss_vs_r_quark'
prof_q = ROOT.TProfile(sname, sname, nbins, 0, jet_R0)
prof_q_log = ROOT.TProfile(sname + '_log', sname + '_log', nbins, lbins)
# prof_q_log = ROOT.TProfile(sname+'_log', sname+'_log', nbins, ROOT.TMath.Log(1./jet_R0), ROOT.TMath.Log(1./sjrs[0]))
sname = 'h2_zloss_vs_r_glue'
h2_zloss_r_g = ROOT.TH2F(sname, sname, nbins, 0., jet_R0, len(sjrs), 0.,
1.)
sname = 'h2_zloss_vs_r_quark'
h2_zloss_r_q = ROOT.TH2F(sname, sname, nbins, 0., jet_R0, len(sjrs), 0.,
1.)
# loop
if args.nev < 100:
args.nev = 100
for i in tqdm.tqdm(range(args.nev)):
if not pythia.next():
continue
# parts = pythiafjext.vectorize(pythia, True, -1, 1, False)
partons = pythiafjext.vectorize_select(pythia, [pythiafjext.kParton],
0, True)
parts = pythiafjext.vectorize_select(
pythia, [pythiafjext.kFinal, pythiafjext.kCharged], 0, False)
# parts = pythiafjext.vectorize_select(pythia, [pythiafjext.kFinal], 0, False)
jets = jet_selector(jet_def(parts))
# for j in tqdm.tqdm(jets):
for j in jets:
j_type = match_dR(j, partons, jet_R0 / 2.)
if j_type[0] is None:
if args.nw:
continue
pwarning('Jet with no parton label')
continue
tw.fill_branch("j", j)
for sjr in sjrs:
rc_jets = fj.sorted_by_pt(sjdefs[sjr](j.constituents()))
tw.fill_branch("sjr{}".format(sjr), rc_jets[0])
zloss = 1. - rc_jets[0].perp() / j.perp()
tw.fill_branch("sjr{}_zloss".format(sjr), zloss)
tw.fill_branch("ppid", j_type[0])
tw.fill_branch("pquark", j_type[1])
tw.fill_branch("pglue", j_type[2])
prof_a.Fill(sjr, zloss)
prof_a_log.Fill(ROOT.TMath.Log(1. / sjr), zloss)
if j_type[1]:
h_zloss_r_q[sjr].Fill(zloss)
h2_zloss_r_q.Fill(sjr, zloss)
prof_q.Fill(sjr, zloss)
prof_q_log.Fill(ROOT.TMath.Log(1. / sjr), zloss)
if j_type[2]:
h_zloss_r_g[sjr].Fill(zloss)
h2_zloss_r_g.Fill(sjr, zloss)
prof_g.Fill(sjr, zloss)
prof_g_log.Fill(ROOT.TMath.Log(1. / sjr), zloss)
tw.fill_tree()
pythia.stat()
tw.write_and_close()
return None
sconfig_pythia = [
"Beams:eCM = 8000.", "HardQCD:all = on", "PhaseSpace:pTHatMin = 100."
]
pythia = create_and_init_pythia(sconfig_pythia)
# 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)
jet_selector = fj.SelectorPtMin(100.0) & fj.SelectorPtMax(
200.0) & fj.SelectorAbsEtaMax(1)
sd = fjcontrib.SoftDrop(0, 0.1, 1.0)
all_jets = []
for iEvent in tqdm(range(10), 'event'):
if not pythia.next(): continue
parts = pyfj.vectorize(pythia, True, -1, 1, False)
jets = jet_selector(jet_def(parts))
all_jets.extend(jets)
all_sd_jets = [sd.result(j) for j in all_jets]
pts = [j.pt() for j in all_jets]
sd_pts = [j.pt() for j in all_sd_jets]
sd_delta_pt = [delta for delta in deltas(all_jets, all_sd_jets)]
nangs0 = [pyfj.angularity(j, 0.) for j in all_jets]
def main():
mycfg = []
ssettings = "--py-ecm 5000 --py-minbias --user-seed=100000"
args = get_args_from_settings(ssettings)
pythia_mb = pyconf.create_and_init_pythia_from_args(args, mycfg)
mycfg = []
ssettings = "--py-ecm 5000 --user-seed=100000 --nev 100000"
args = get_args_from_settings(ssettings)
pythia_hard = pyconf.create_and_init_pythia_from_args(args, mycfg)
max_eta_hadron = 1
parts_selector_h = fj.SelectorAbsEtaMax(max_eta_hadron)
jet_R0 = 0.4
jet_selector = fj.SelectorPtMin(20.0) & fj.SelectorPtMax(
200.0) & fj.SelectorAbsEtaMax(max_eta_hadron - 1.05 * jet_R0)
n_pileup = 1 #5
# 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)
fout = ROOT.TFile(args.output, 'recreate')
fout.cd()
tj_delta = ROOT.TNtuple(
"tj_delta", "tj_delta",
"pt:eta:phi:L11:L21:L31:ptm:etam:phim:L11m:L21m:L31m:mpt")
tj_no_pup = ROOT.TNtuple("tj_no_pup", "tj_no_pup",
"pt:eta:phi:L11:L21:L31")
tj_pup = ROOT.TNtuple("tj_pup", "tj_pup", "pt:eta:phi:L11:L21:L31")
hmult_hard = ROOT.TH1F("hmult_hard", "hmult_hard", 300, 0, 300)
hmult_pup = ROOT.TH1F("hmult_pup", "hmult_pup", 300, 0, 300)
hpt_acc_hard = ROOT.TProfile2D("hpt_acc_hard", "hpt_acc_hard;#eta;#varphi",
50, -1, 1, 50, 0,
ROOT.TMath.Pi() * 2.)
hpt_acc_pup = ROOT.TProfile2D("hpt_acc_pup", "hpt_acc_pup;#eta;#varphi",
50, -1, 1, 50, 0,
ROOT.TMath.Pi() * 2.)
for n in tqdm(range(args.nev)):
if not pythia_hard.next():
continue
parts_pythia_h = pythiafjext.vectorize_select(
pythia_hard, [pythiafjext.kFinal, pythiafjext.kCharged], 0, False)
parts_pythia_h_selected = parts_selector_h(parts_pythia_h)
parts_pileup = None
for ipile in range(n_pileup):
while not pythia_mb.next():
continue
parts_pythia_h_ue = pythiafjext.vectorize_select(
pythia_mb, [pythiafjext.kFinal, pythiafjext.kCharged], 10000,
False)
parts_pythia_h_selected_ue = parts_selector_h(parts_pythia_h_ue)
if parts_pileup is None:
parts_pileup = parts_pythia_h_selected_ue
else:
parts_pileup += parts_pythia_h_selected_ue
mult_hard = len(parts_pythia_h_selected)
mult_ue = len(parts_pileup)
jets_h = fj.sorted_by_pt(jet_selector(
jet_def(parts_pythia_h_selected)))
jets_h_w_ue = fj.sorted_by_pt(
jet_selector(jet_def(parts_pileup + parts_pythia_h_selected)))
if len(jets_h) < 1:
continue
fill_matched(jets_h, jets_h_w_ue, tj_no_pup, tj_pup, tj_delta, jet_R0)
hmult_hard.Fill(mult_hard)
hmult_pup.Fill(mult_ue)
_tmp = [
hpt_acc_hard.Fill(p.eta(), p.phi(), p.perp())
for p in parts_pythia_h_selected
]
_tmp = [
hpt_acc_pup.Fill(p.eta(), p.phi(), p.perp()) for p in parts_pileup
]
pythia_hard.stat()
pythia_mb.stat()
fout.Write()
fout.Close()
print('[i] written ', fout.GetName())
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('--nw', help="no warn", default=False, action='store_true')
parser.add_argument('--ignore-mycfg', help="ignore some settings hardcoded here", default=False, action='store_true')
parser.add_argument('--enable-background', help="enable background calc", default=False, action='store_true')
parser.add_argument('--output', help="output file name", default='leadsj_vs_x_output.root', type=str)
# for background
parser.add_argument('--cent-bin', help="centraility bin 0 is the 0-5 percent most central bin", type=int, default=0)
parser.add_argument('--seed', help="pr gen seed", type=int, default=1111)
parser.add_argument('--harmonics', help="set harmonics flag (0 : v1 - v5) , (1 : v2 - v5) , (2: v3 - v5) , (3: v1 - v4) , (4: v1 - v3) , (5: uniform dN/dphi no harmonics) , (6 : v1 - v2 , v4 - v5) , (7 : v1 - v3 , v5) , (8 : v1 , v3 - v5) , (9 : v1 only) , (10 : v2 only) , (11 : v3 only) , (12 : v4 only) , (13 : v5 only)",
type=int, default=5)
parser.add_argument('--eta', help="set eta range must be uniform (e.g. abs(eta) < 0.9, which is ALICE TPC fiducial acceptance)",
type=float, default=0.9)
parser.add_argument('--qa', help="PrintOutQAHistos", default=False, action='store_true')
parser.add_argument('--dRmax', default=0.25, type=float)
parser.add_argument('--alpha', default=0, type=float)
args = parser.parse_args()
# 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)
jet_selector = fj.SelectorPtMin(args.py_pthatmin) & fj.SelectorPtMax(1000.0) & fj.SelectorAbsEtaMax(args.eta - jet_R0)
# jet_selector = fj.SelectorPtMin(40.0) & fj.SelectorPtMax(200.0) &fj.SelectorAbsEtaMax(1)
print(jet_def)
all_jets = []
# mycfg = ['PhaseSpace:pThatMin = 80']
# mycfg = ['PhaseSpace:pThatMin = 40']
mycfg = ['']
if args.ignore_mycfg:
mycfg = []
pythia = pyconf.create_and_init_pythia_from_args(args, mycfg)
if not pythia:
perror("pythia initialization failed.")
return
jet_def_lund = fj.JetDefinition(fj.cambridge_algorithm, 1.0)
lund_gen = fjcontrib.LundGenerator(jet_def_lund)
print (lund_gen.description())
dy_groomer = fjcontrib.DynamicalGroomer(jet_def_lund)
print (dy_groomer.description())
# sd = fjcontrib.SoftDrop(0, 0.1, 1.0)
sd01 = fjcontrib.SoftDrop(0, 0.1, 1.0)
print (sd01)
sd02 = fjcontrib.SoftDrop(0, 0.2, 1.0)
print (sd02)
# jet_def_rc01 = fj.JetDefinition(fj.cambridge_algorithm, 0.1)
# jet_def_rc02 = fj.JetDefinition(fj.cambridge_algorithm, 0.2)
# print (jet_def_rc01)
# print (jet_def_rc02)
# rc = fjcontrib.Recluster(jet_def_rc, True)
jet_def_rc01 = fj.JetDefinition(fj.antikt_algorithm, 0.1)
jet_def_rc02 = fj.JetDefinition(fj.antikt_algorithm, 0.2)
print (jet_def_rc01)
print (jet_def_rc02)
#rc = fjcontrib.Recluster(jet_def_rc, True)
# tw = treewriter.RTreeWriter(name = 'lsjvsx', file_name = 'leadsj_vs_x.root')
tw = treewriter.RTreeWriter(name = 'lsjvsx', file_name = args.output)
tgbkg = None
be = None
if args.enable_background:
# ROOT.gSystem.Load("libpyjetty_TennGen.dylib")
# tgbkg = ROOT.TennGen() # //constructor
# tgbkg.SetCentralityBin(args.cent_bin) # //centraility bin 0 is the 0-5 % most central bin
# tgbkg.SetRandomSeed(args.seed) # //setting the seed
# tgbkg.SetHarmonics(args.harmonics) # // set harmonics flag (0 : v1 - v5) , (1 : v2 - v5) , (2: v3 - v5) , (3: v1 - v4) , (4: v1 - v3) , (5: uniform dN/dphi no harmonics) , (6 : v1 - v2 , v4 - v5) , (7 : v1 - v3 , v5) , (8 : v1 , v3 - v5) , (9 : v1 only) , (10 : v2 only) , (11 : v3 only) , (12 : v4 only) , (13 : v5 only)
# tgbkg.SetEtaRange(args.eta) # //set eta range must be uniform (e.g. |eta| < 0.9, which is ALICE TPC fiducial acceptance)
# tgbkg.PrintOutQAHistos(args.qa) #
# tgbkg.InitializeBackground() #
from pyjetty.mputils import BoltzmannEvent
be = BoltzmannEvent(mean_pt=0.7, multiplicity=2000 * args.eta * 2, max_eta=max_eta, max_pt=100)
print(be)
from pyjetty.mputils import CEventSubtractor, CSubtractorJetByJet
cs = CEventSubtractor(alpha=args.alpha, max_distance=args.dRmax, max_eta=args.eta, bge_rho_grid_size=0.25, max_pt_correct=100)
print(cs)
if args.nev < 100:
args.nev = 100
for i in tqdm.tqdm(range(args.nev)):
if not pythia.next():
continue
# parts = pythiafjext.vectorize(pythia, True, -1, 1, False)
partons = pythiafjext.vectorize_select(pythia, [pythiafjext.kParton], 0, True)
parts = pythiafjext.vectorize_select(pythia, [pythiafjext.kFinal, pythiafjext.kCharged], 0, False)
# parts = pythiafjext.vectorize_select(pythia, [pythiafjext.kFinal], 0, False)
jets = jet_selector(jet_def(parts))
# for j in tqdm.tqdm(jets):
for j in jets:
j_type = match_dR(j, partons, jet_R0 / 2.)
if j_type[0] is None:
if args.nw:
continue
pwarning('Jet with no parton label')
continue
j_sd02 = sd02.result(j)
sd02_info = fjcontrib.get_SD_jet_info(j_sd02)
j_sd01 = sd01.result(j)
sd01_info = fjcontrib.get_SD_jet_info(j_sd01)
rc_sjets01 = fj.sorted_by_pt(jet_def_rc01(j.constituents()))
rc_sjets02 = fj.sorted_by_pt(jet_def_rc02(j.constituents()))
tw.fill_branches( j = j,
lund = [ls for ls in lund_gen.result(j)],
dyg1 = dy_groomer.result(j, 1),
sd01 = j_sd01,
sd01_z = sd01_info.z,
sd01_mu = sd01_info.mu,
sd01_Delta = sd01_info.dR,
sd02 = j_sd02,
sd02_z = sd02_info.z,
sd02_mu = sd02_info.mu,
sd02_Delta = sd02_info.dR,
# breaking compatibility
# sd = j_sd,
# sd_z = sd_info.z,
# sd_mu = sd_info.mu,
# sd_Delta = sd_info.dR,
lsjet01 = rc_sjets01[0],
nsjet01 = len(rc_sjets01),
sjet01 = rc_sjets01,
lsjet02 = rc_sjets02[0],
nsjet02 = len(rc_sjets02),
sjet02 = rc_sjets02,
ppid = j_type[0],
pquark = j_type[1],
pglue = j_type[2], # this is redundancy
pycode = pythia.info.code(),
pysigmagen = pythia.info.sigmaGen(),
pysigmaerr = pythia.info.sigmaErr(),
pyid1 = pythia.info.id1pdf(),
pyid2 = pythia.info.id1pdf(),
pyx1 = pythia.info.x1pdf(),
pyx2 = pythia.info.x2pdf(),
pypdf1 = pythia.info.pdf1(),
pyQfac = pythia.info.QFac(),
pyalphaS = pythia.info.alphaS(),
pypthat = pythia.info.pTHat(),
pymhat = pythia.info.mHat()
)
if be:
bg_parts = be.generate(offset=10000)
full_event = bg_parts
tmp = [full_event.push_back(psj) for psj in j.constituents()]
if cs:
cs_parts = cs.process_event(full_event)
rho = cs.bge_rho.rho()
bg_jets = fj.sorted_by_pt(jet_def(cs_parts))
for bj in bg_jets:
if fjtools.matched_pt(bj, j) > 0.5:
pass
tw.fill_tree()
pythia.stat()
tw.write_and_close()
def main():
parser = argparse.ArgumentParser(description='pythia8 in python', prog=os.path.basename(__file__))
parser.add_argument('-i', '--input', help='input file', default='low', type=str, required=True)
parser.add_argument('--nev', help='number of events', default=-1, type=int)
parser.add_argument('--jetptcut', help='jet pt cut', default=10., type=float)
args = parser.parse_args()
files = find_files(args.input, "*.txt")
print(files)
print('[i] number of files found {}'.format(len(files)))
# jet finder
# print the banner first
fj.ClusterSequence.print_banner()
print()
jet_R0 = 0.4
jet_def = fj.JetDefinition(fj.antikt_algorithm, jet_R0)
jet_selector = fj.SelectorPtMin(10.0) & fj.SelectorAbsEtaMax(3)
if args.nev < 0:
args.nev = len(files)
if args.nev > len(files):
args.nev = len(files)
print("[i] running on {}".format(files[:args.nev]))
all_jets = []
for fin in tqdm.tqdm(files[:args.nev]):
input_hepmc = hepmc3ext.YuukaRead(fin)
if input_hepmc.failed():
print ("[error] unable to read from {}".format(fin))
sys.exit(1)
if input_hepmc.nextEvent():
jets = find_jets_hepmc(jet_def, jet_selector, input_hepmc, accept_status=[62])
all_jets.extend(jets)
jet_def_lund = fj.JetDefinition(fj.cambridge_algorithm, 1.0)
lund_gen = fjcontrib.LundGenerator(jet_def_lund)
print('[i] making lund diagram for all jets...')
lunds = [lund_gen.result(j) for j in all_jets]
print('[i] reclustering and using soft drop...')
jet_def_rc = fj.JetDefinition(fj.cambridge_algorithm, 0.1)
print('[i] Reclustering:', jet_def_rc)
all_jets_sd = []
rc = fjcontrib.Recluster(jet_def_rc, True)
sd = fjcontrib.SoftDrop(0, 0.1, 1.0)
fout = ROOT.TFile('hepmc_jetreco.root', 'recreate')
lbins = logbins(1., 500, 50)
hJetPt04 = ROOT.TH1D("hJetPt04", "hJetPt04", 50, lbins)
hJetPt04sd = ROOT.TH1D("hJetPt04sd", "hJetPt04sd", 50, lbins)
[hJetPt04.Fill(j.perp()) for j in all_jets]
[hJetPt04sd.Fill(j.perp()) for j in all_jets_sd]
hLund = ROOT.TH2D("hLund", "hLund", 60, 0, 6, 100, -4, 5)
lunds = [lund_gen.result(j) for j in all_jets if j.perp() > args.jetptcut]
jsel = [j for j in all_jets if j.perp() > args.jetptcut]
print('[i] {} jets above {} GeV/c'.format(len(jsel), args.jetptcut))
for l in lunds:
for s in l:
hLund.Fill(math.log(1./s.Delta()), math.log(s.kt()))
if len(jsel) > 0:
hLund.Scale(1./len(jsel))
fout.Write()
def generate():
parser = argparse.ArgumentParser(description='pythia8 fastjet on the fly',
prog=os.path.basename(__file__))
parser.add_argument(
'-d',
'--output-dir',
help='output directory name - use with default file name',
default='.',
type=str)
parser.add_argument('-o',
'--output',
help='output file name',
default='',
type=str)
parser.add_argument('--overwrite', default=False, action='store_true')
parser.add_argument('--jet-R',
help='jet finder R',
default=0.4,
type=float)
parser.add_argument('--charged', default=False, action='store_true')
parser.add_argument('--runid', default=0, type=int)
parser.add_argument('--tranges',
default='6-7',
help='hadron trigger ranges min-max,min1-max1,...',
type=str)
group = parser.add_mutually_exclusive_group()
group.add_argument('--inel', default=False, action='store_true')
group.add_argument('--hard', default=False, action='store_true')
pyconf.add_standard_pythia_args(parser)
args = parser.parse_args()
# mycfg = ['PhaseSpace:pThatMin = 6']
mycfg = []
if '.root' not in args.output:
rs = '0{}'.format(int(args.jet_R * 10))
if args.jet_R >= 1:
rs = '{}'.format(int(args.jet_R))
args.output = '{}/h_jet_R{}'.format(args.output_dir, rs)
if args.charged:
args.output = '{}/h_jet_ch_R{}'.format(args.output_dir, rs)
if args.tranges:
args.output += '_tranges_{}'.format(args.tranges.replace(',', "_"))
if args.runid >= 0:
args.output += '_runid_{}'.format(args.runid)
args.py_seed = 1000 + args.runid
if args.py_noMPI:
args.output += '_noMPI'
if args.py_noISR:
args.output += '_noISR'
if args.py_noHadron:
args.output += '_noHadr'
if args.py_minbias > 0:
args.output += '_minbias'
if args.py_pthatmin > 0:
args.output += '_pthatmin_{}'.format(args.py_pthatmin)
if args.inel:
args.output += '_inel'
mycfg.append("SoftQCD:inelastic = on")
mycfg.append("HardQCD:all = off")
else:
if args.hard:
args.output += '_biasref_{}'.format(args.py_biasref)
args.output += '_hard'
mycfg.append("HardQCD:all = on")
else:
mycfg.append("HardQCD:all = on")
args.output += '_hard'
args.output += '.root'
print(args)
if os.path.exists(args.output):
if not args.overwrite:
print('[w] output file', args.output, 'exists - skipping.')
return
print('[i] output file', args.output)
# print the banner first
fj.ClusterSequence.print_banner()
print()
#and in the code i do not allow decay of the following particles:
mycfg.append("310:mayDecay = off") # //K0s
mycfg.append("3122:mayDecay = off") # //labda0
mycfg.append("3112:mayDecay = off") # //sigma-
mycfg.append("3212:mayDecay = off") # //sigma0
mycfg.append("3222:mayDecay = off") # //sigma+
mycfg.append("3312:mayDecay = off") # //xi-
mycfg.append("3322:mayDecay = off") # //xi+
mycfg.append("3334:mayDecay = off") # //omega-
print('[i] additional settings', mycfg)
pythia = pyconf.create_and_init_pythia_from_args(args, mycfg)
if not pythia:
return
if args.nev < 1:
args.nev = 1
tpairs = []
st = args.tranges.split(',')
try:
for _s in st:
t0 = float(_s.split('-')[0])
t1 = float(_s.split('-')[1])
tpairs.append([t0, t1])
except:
print(
'[e] something is not quite right with trigger ranges... stop here.'
)
jet_particle_eta_max = 0.9
jet_particle_selector = fj.SelectorAbsEtaMax(jet_particle_eta_max)
v0det = V0Detector()
j_ana = JetAnalysis(jet_R=args.jet_R,
particle_eta_max=jet_particle_eta_max)
fout = r.TFile(args.output, 'RECREATE')
fout.cd()
hmV0M = r.TH1F('hmV0M', 'hmV0M', 1000, 0, 1000)
hmV0A = r.TH1F('hmV0A', 'hmV0A', 1000, 0, 1000)
hmV0C = r.TH1F('hmV0C', 'hmV0C', 1000, 0, 1000)
event_output = RTreeWriter(tree_name='evT', fout=fout)
jet_output = RTreeWriter(tree_name='jetT', fout=fout)
hjet_sets = []
for t in tpairs:
hjet_output = RTreeWriter(tree_name='hjetT_{}_{}'.format(
int(t[0]), int(t[1])),
fout=fout)
hjet = HJet(trigger_range=[t[0], t[1]])
print(hjet)
hjset = HJetSet(hjet, hjet_output)
hjet_sets.append(hjset)
for ev_id in tqdm.tqdm(range(args.nev)):
if not pythia.next():
continue
if args.charged:
parts = pythiafjext.vectorize_select(
pythia, [pythiafjext.kFinal, pythiafjext.kCharged])
else:
parts = pythiafjext.vectorize_select(pythia, [pythiafjext.kFinal])
event_output.clear()
jet_output.clear()
_tmp = [s.hjet_output.clear() for s in hjet_sets]
jet_parts = jet_particle_selector(parts)
ev_s = pythia.info.sigmaGen()
ev_w = pythia.info.weight()
ev_code = pythia.info.code()
pthard = pythia.info.pTHat()
mTot = len(parts)
mCB = len(jet_parts)
v0det.analyze_event(parts)
event_output.fill_branch('ev_id', ev_id)
event_output.fill_branch('weight', ev_w)
event_output.fill_branch('sigma', ev_s)
event_output.fill_branch('code', ev_code)
event_output.fill_branch('pthard', pthard)
event_output.fill_branch('mTot', mTot)
event_output.fill_branch('mCB', mCB)
v0det.fill_branches(event_output)
event_output.fill_tree()
hmV0M.Fill(v0det.V0_mult)
hmV0A.Fill(v0det.V0A_mult)
hmV0C.Fill(v0det.V0C_mult)
if len(parts) < 1:
continue
if True in [s.analyze_event(jet_parts) for s in hjet_sets]:
j_ana.analyze_event(jet_parts)
jet_output.fill_branch('ev_id', ev_id)
jet_output.fill_branch('weight', ev_w)
jet_output.fill_branch('sigma', ev_s)
jet_output.fill_branch('code', ev_code)
jet_output.fill_branch('pthard', pthard)
jet_output.fill_branch('mTot', mTot)
jet_output.fill_branch('mCB', mCB)
j_ana.fill_branches(jet_output)
jet_output.fill_tree()
for s in hjet_sets:
if s.hjet.trigger_particle:
s.hjet_output.fill_branch('ev_id', ev_id)
s.hjet_output.fill_branch('weight', ev_w)
s.hjet_output.fill_branch('sigma', ev_s)
s.hjet_output.fill_branch('code', ev_code)
s.hjet_output.fill_branch('pthard', pthard)
s.hjet_output.fill_branch('mTot', mTot)
s.hjet_output.fill_branch('mCB', mCB)
s.hjet.fill_branches(s.hjet_output, j_ana.jets)
v0det.fill_branches(s.hjet_output)
j_ana.fill_branches(s.hjet_output)
s.hjet_output.fill_tree()
pythia.stat()
fout.Write()
fout.Close()
print('[i] written', fout.GetName())
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')
args = parser.parse_args()
# 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)
jet_selector = fj.SelectorPtMin(100.0) & fj.SelectorAbsEtaMax(1)
print(jet_def)
all_jets = []
mycfg = ['PhaseSpace:pThatMin = 100']
if args.ignore_mycfg:
mycfg = []
pythia = pyconf.create_and_init_pythia_from_args(args, mycfg)
if not pythia:
print("[e] pythia initialization failed.")
return
if args.nev < 10:
args.nev = 10
for i in tqdm.tqdm(range(args.nev)):
if not pythia.next():
continue
attach_pythia_particle_info = True
parts = pythiafjext.vectorize_select(pythia, [pythiafjext.kFinal],
attach_pythia_particle_info)
jets = jet_selector(jet_def(parts))
for j in jets:
gshop = fjcontrib.GroomerShop(j)
# note these LundDeclustering objects can be streamed to a tree using RTreeStreamer
dg01 = gshop.dynamical(0.1)
idg01 = gshop.index(dg01)
dg20 = gshop.dynamical(2.0)
idg20 = gshop.index(dg20)
max_kt = gshop.max_kt()
imax_kt = gshop.index(max_kt)
max_pt_softer = gshop.max_pt_softer()
# check if the same split selected:
# if dg01.pair() == dg20.pair():
# or use indices
if idg01 == idg20 and idg01 > 0:
print('- interesting jet?:')
print(' dg01 :', dg01.as_string(), 'index dg01:',
idg01)
print(' dg20 :', dg20.as_string(), 'index dg20:',
idg20)
print(' max_kt :', max_kt.as_string(), 'index max_kt:',
imax_kt)
print(' max_pt_softer:', max_pt_softer.as_string())
print(' max_kappa :', gshop.max_kappa().as_string())
print(' max_tf :', gshop.max_tf().as_string())
print(' min_tf :', gshop.min_tf().as_string())
print(' max_z :', gshop.max_z().as_string())
print('softdrop check for jet:', j)
sd = fjcontrib.SoftDrop(0, 0.1, 1.0)
j_sd = sd.result(j)
#print(' |-> after soft drop pT={0:10.3f} delta={1:10.3f}'.format(j_sd.perp(), j_sd.perp() - j.perp()))
sd_info = fjcontrib.get_SD_jet_info(j_sd)
print(" |-> SD jet params z={} dR={} mu={}".format(
sd_info.z, sd_info.dR, sd_info.mu))
print(' |-> GroomerShop::soft_drop',
gshop.soft_drop(0, 0.1, 1.0).as_string())
# or call with no radius param - will use max allowed
# print(' |-> GroomerShop::soft_drop', gshop.soft_drop(0, 0.1).as_string())
pythia.stat()
def main():
parser = argparse.ArgumentParser(
description='read jewel to lund jets object and pickle with joblib',
prog=os.path.basename(__file__))
parser.add_argument('-d',
'--dir',
help='input directory',
default='',
type=str,
required=True)
parser.add_argument('-n',
'--nfiles',
help='number of files',
default=-1,
type=int,
required=False)
parser.add_argument('-p',
'--pattern',
help='input directory',
default='',
type=str,
required=True)
parser.add_argument('--nev', help='number of events', default=-1, type=int)
parser.add_argument('--clean',
help='remove output before writing',
action='store_true',
default=False)
args = parser.parse_args()
files = find_files(args.dir, args.pattern)
# jet finder
# print the banner first
fj.ClusterSequence.print_banner()
print()
jet_R0 = 0.4
jet_def = fj.JetDefinition(fj.antikt_algorithm, jet_R0)
jet_selector = fj.SelectorPtMin(40.0) & fj.SelectorPtMax(
500.0) & fj.SelectorAbsEtaMax(2)
jet_def_lund = fj.JetDefinition(fj.cambridge_algorithm, 1.0)
lund_gen = fjcontrib.LundGenerator(jet_def_lund)
sd = fjcontrib.SoftDrop(0, 0.1, 1.0)
if args.nfiles > 0:
rfiles = files[:args.nfiles]
else:
rfiles = files
print("[i] found {} files - running for {} files".format(
len(files), len(rfiles)))
for ifile, fn in enumerate(tqdm.tqdm(rfiles)):
# now lets read the HEPMC file and do some jet finding
input_hepmc = hepmc2wrap.ReadHepMCFile(fn)
if input_hepmc.failed():
print("[error] unable to read from {}".format(fn))
sys.exit(1)
all_jets = []
for iev in tqdm.tqdm(range(args.nev)):
if input_hepmc.failed():
break
if input_hepmc.NextEvent():
jets_hepmc = find_jets_hepmc(jet_def,
jet_selector,
input_hepmc,
final=True)
all_jets.extend(jets_hepmc)
lunds = [lund_gen.result(j) for j in all_jets]
lunds_pickle = [
lundjet.LundJet(j, lund_gen.result(j)) for j in all_jets
]
all_jets_sd = [sd.result(j) for j in all_jets]
lunds_sd = [lund_gen.result(j) for j in all_jets_sd]
lunds_sd_pickle = [
lundjet.LundJet(j, lund_gen.result(j)) for j in all_jets_sd
]
joblib_file = 'lund_{}.joblib'.format(os.path.basename(fn))
it = 0
while os.path.exists(joblib_file):
if args.clean:
os.unlink(joblib_file)
break
joblib_file = 'lund_{}_{}.joblib'.format(os.path.basename(fn), it)
it += 1
joblib.dump(lunds_pickle, joblib_file)
joblib_file_sd = 'lund_sd_{}.joblib'.format(os.path.basename(fn))
it = 0
while os.path.exists(joblib_file_sd):
if args.clean:
os.unlink(joblib_file_sd)
break
joblib_file_sd = 'lund_sd_{}_{}.joblib'.format(
os.path.basename(fn), it)
it += 1
joblib.dump(lunds_sd_pickle, joblib_file_sd)
def main():
parser = argparse.ArgumentParser(description='pythia8 in python',
prog=os.path.basename(__file__))
parser.add_argument('-i',
'--input',
help='input file',
default='low',
type=str,
required=True)
parser.add_argument('--hepmc',
help='what format 2 or 3',
default=2,
type=int)
parser.add_argument('--nev', help='number of events', default=10, type=int)
args = parser.parse_args()
###
# now lets read the HEPMC file and do some jet finding
if args.hepmc == 3:
input_hepmc = pyhepmc_ng.ReaderAscii(args.input)
if args.hepmc == 2:
input_hepmc = pyhepmc_ng.ReaderAsciiHepMC2(args.input)
if input_hepmc.failed():
print("[error] unable to read from {}".format(args.input))
sys.exit(1)
# jet finder
# print the banner first
fj.ClusterSequence.print_banner()
print()
jet_R0 = 0.4
jet_def = fj.JetDefinition(fj.antikt_algorithm, jet_R0)
jet_selector = fj.SelectorPtMin(10.0) & fj.SelectorPtMax(
500.0) & fj.SelectorAbsEtaMax(3)
all_jets = []
event_hepmc = pyhepmc_ng.GenEvent()
pbar = tqdm.tqdm(range(args.nev))
while not input_hepmc.failed():
ev = input_hepmc.read_event(event_hepmc)
if input_hepmc.failed():
break
jets_hepmc = find_jets_hepmc(jet_def, jet_selector, event_hepmc)
all_jets.extend(jets_hepmc)
pbar.update()
if pbar.n >= args.nev:
break
jet_def_lund = fj.JetDefinition(fj.cambridge_algorithm, 1.0)
lund_gen = fjcontrib.LundGenerator(jet_def_lund)
print('[i] making lund diagram for all jets...')
lunds = [lund_gen.result(j) for j in all_jets]
print('[i] listing lund plane points... Delta, kt - for {} selected jets'.
format(len(all_jets)))
for l in lunds:
if len(l) < 1:
continue
print('- jet pT={0:5.2f} eta={1:5.2f}'.format(l[0].pair().perp(),
l[0].pair().eta()))
print(' Deltas={}'.format([s.Delta() for s in l]))
print(' kts={}'.format([s.kt() for s in l]))
print()
print('[i] reclustering and using soft drop...')
jet_def_rc = fj.JetDefinition(fj.cambridge_algorithm, 0.1)
print('[i] Reclustering:', jet_def_rc)
all_jets_sd = []
rc = fjcontrib.Recluster(jet_def_rc, True)
sd = fjcontrib.SoftDrop(0, 0.1, 1.0)
for i, j in enumerate(all_jets):
j_rc = rc.result(j)
print()
print('- [{0:3d}] orig pT={1:10.3f} reclustered pT={2:10.3f}'.format(
i, j.perp(), j_rc.perp()))
j_sd = sd.result(j)
print(' |-> after soft drop pT={0:10.3f} delta={1:10.3f}'.format(
j_sd.perp(),
j_sd.perp() - j.perp()))
all_jets_sd.append(j_sd)
sd_info = fjcontrib.get_SD_jet_info(j_sd)
print(
" |-> SD jet params z={0:10.3f} dR={1:10.3f} mu={2:10.3f}".format(
sd_info.z, sd_info.dR, sd_info.mu))
fout = ROOT.TFile('hepmc_jetreco.root', 'recreate')
lbins = logbins(1., 500, 50)
hJetPt04 = ROOT.TH1D("hJetPt04", "hJetPt04", 50, lbins)
hJetPt04sd = ROOT.TH1D("hJetPt04sd", "hJetPt04sd", 50, lbins)
[hJetPt04.Fill(j.perp()) for j in all_jets]
[hJetPt04sd.Fill(j.perp()) for j in all_jets_sd]
hLund = ROOT.TH2D("hLund", "hLund", 60, 0, 6, 100, -4, 5)
lunds = [lund_gen.result(j) for j in all_jets if j.perp() > 100]
j100 = [j for j in all_jets if j.perp() > 100]
print('{} jets above 100 GeV/c'.format(len(j100)))
for l in lunds:
for s in l:
hLund.Fill(math.log(1. / s.Delta()), math.log(s.kt()))
fout.Write()
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')
args = parser.parse_args()
# 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)
jet_selector = fj.SelectorPtMin(80.0) & fj.SelectorPtMax(
100.0) & fj.SelectorAbsEtaMax(1)
# jet_selector = fj.SelectorPtMin(40.0) & fj.SelectorPtMax(200.0) &fj.SelectorAbsEtaMax(1)
print(jet_def)
all_jets = []
mycfg = ['PhaseSpace:pThatMin = 80']
# mycfg = ['PhaseSpace:pThatMin = 40']
if args.ignore_mycfg:
mycfg = []
pythia = pyconf.create_and_init_pythia_from_args(args, mycfg)
if not pythia:
perror("pythia initialization failed.")
return
jet_def_lund = fj.JetDefinition(fj.cambridge_algorithm, 1.0)
lund_gen = fjcontrib.LundGenerator(jet_def_lund)
print(lund_gen.description())
dy_groomer = fjcontrib.DynamicalGroomer(jet_def_lund)
print(dy_groomer.description())
# sd = fjcontrib.SoftDrop(0, 0.1, 1.0)
sd = fjcontrib.SoftDrop(0, 0.2, 1.0)
print(sd)
# jet_def_rc01 = fj.JetDefinition(fj.cambridge_algorithm, 0.1)
# jet_def_rc02 = fj.JetDefinition(fj.cambridge_algorithm, 0.2)
# print (jet_def_rc01)
# print (jet_def_rc02)
# rc = fjcontrib.Recluster(jet_def_rc, True)
jet_def_rc01 = fj.JetDefinition(fj.antikt_algorithm, 0.1)
jet_def_rc02 = fj.JetDefinition(fj.antikt_algorithm, 0.2)
print(jet_def_rc01)
print(jet_def_rc02)
#rc = fjcontrib.Recluster(jet_def_rc, True)
# tw = treewriter.RTreeWriter(name = 'lsjvsx', file_name = 'leadsj_vs_x.root')
tw = treewriter.RTreeWriter(name='lsjvsx',
file_name='leadsj_vs_x_bias80.root')
if args.nev < 100:
args.nev = 100
for i in tqdm.tqdm(range(args.nev)):
if not pythia.next():
continue
# parts = pythiafjext.vectorize(pythia, True, -1, 1, False)
partons = pythiafjext.vectorize_select(pythia, [pythiafjext.kParton],
0, True)
parts = pythiafjext.vectorize_select(
pythia, [pythiafjext.kFinal, pythiafjext.kCharged], 0, False)
# parts = pythiafjext.vectorize_select(pythia, [pythiafjext.kFinal], 0, False)
jets = jet_selector(jet_def(parts))
# for j in tqdm.tqdm(jets):
for j in jets:
j_type = match_dR(j, partons, jet_R0 / 2.)
j_sd = sd.result(j)
sd_info = fjcontrib.get_SD_jet_info(j_sd)
rc_sjets01 = fj.sorted_by_pt(jet_def_rc01(j.constituents()))
rc_sjets02 = fj.sorted_by_pt(jet_def_rc02(j.constituents()))
tw.fill_branches(
j=j,
lund=[ls for ls in lund_gen.result(j)],
dyg1=dy_groomer.result(j, 1),
sd=j_sd,
sd_z=sd_info.z,
sd_mu=sd_info.mu,
sd_Delta=sd_info.dR,
lsjet01=rc_sjets01[0],
nsjet01=len(rc_sjets01),
sjet01=rc_sjets01,
lsjet02=rc_sjets02[0],
nsjet02=len(rc_sjets02),
sjet02=rc_sjets02,
ppid=j_type[0],
pquark=j_type[1],
pglue=j_type[2] # this is redundancy
)
tw.fill_tree()
pythia.stat()
tw.write_and_close()
def main():
parser = argparse.ArgumentParser(description='jetscape in python', \
prog=os.path.basename(__file__))
parser.add_argument('-i', '--input', help='input file', \
default='low', type=str, required=True)
parser.add_argument('--nev', help='number of events', \
default=1000, type=int)
args = parser.parse_args()
plot_hadrons = False
plot_final_state_partons = True
plot_nth_partons = False
include_thermal_background = False
# Initialize histogram dictionary
hDict = initializeHistograms()
# Use pyhepmc_ng to parse the HepMC file
input_hepmc = pyhepmc_ng.ReaderAscii(args.input)
if input_hepmc.failed():
print("[error] unable to read from {}".format(args.input))
sys.exit(1)
# jet finder
fj.ClusterSequence.print_banner()
print()
jetR = 0.4
jet_def = fj.JetDefinition(fj.antikt_algorithm, jetR)
jet_selector = fj.SelectorPtMin(50.0) & fj.SelectorAbsEtaMax(2)
# Jet re-clustering definition, for primary Lund plane
jet_def_lund = fj.JetDefinition(fj.cambridge_algorithm, jetR)
lund_gen = fjcontrib.LundGenerator(jet_def_lund)
# Load thermal background: array of dataframes, one per event
if include_thermal_background:
thermal_background_array = get_thermal_background()
# Loop through events
all_jets_hadron = []
all_jets_parton = []
kt_shower_list = []
event_hepmc = pyhepmc_ng.GenEvent()
pbar = tqdm.tqdm(range(args.nev))
while not input_hepmc.failed():
ev = input_hepmc.read_event(event_hepmc)
if input_hepmc.failed():
nstop = pbar.n
pbar.close()
print('End of HepMC file at event {} '.format(nstop))
break
if plot_hadrons:
hadrons = get_hadrons(event_hepmc)
jets_hadron = find_jets(jet_def, jet_selector, hadrons)
all_jets_hadron.extend(jets_hadron)
if plot_final_state_partons:
parton_list = get_final_partons(event_hepmc, hDict)
elif plot_nth_partons:
# Get the first parton in the shower (it is apparently the child of the initiating parton)
first_parton = []
first_parton.append(
get_first_parton(event_hepmc, hDict).children[0])
#print('-----------------------------')
#print('First parton E: {}'.format(first_parton[0].momentum.e))
n = 3
parton_list = get_nth_partons(first_parton, n)
#print('Total number of partons: {}'.format(len(parton_list)))
fj_particles = []
for parton in parton_list:
fj_particles.append(
fj.PseudoJet(parton.momentum.px, parton.momentum.py,
parton.momentum.pz, parton.momentum.e))
# Append thermal background
if include_thermal_background:
thermal_background_df = thermal_background_array[0]
thermal_background_fjparticles = get_fjparticles(
thermal_background_df)
fj_particles.extend(thermal_background_fjparticles)
jets_parton = find_jets(jet_def, jet_selector, fj_particles)
all_jets_parton.extend(jets_parton)
# Analyze shower history
max_kt = get_max_kt_shower(event_hepmc, hDict)
kt_shower_list.append(max_kt)
pbar.update()
if pbar.n >= args.nev:
pbar.close()
print('{} event limit reached'.format(args.nev))
break
print('Constructing histograms...')
if plot_hadrons:
n_jets_hadron = len(all_jets_hadron)
print('n_jets_hadron: {}'.format(n_jets_hadron))
n_jets_parton = len(all_jets_parton)
print('n_jets_parton: {}'.format(n_jets_parton))
# Fill histogram
if plot_hadrons:
[fill_jet_histogram(hDict, jet) for jet in all_jets_hadron]
# Fill Lund diagram
# Note: l in lunds, l is the list of splittings in a given jet (following hardest splitting)
lunds_hadron = [lund_gen.result(jet) for jet in all_jets_hadron]
[
fill_lund_histogram(hDict, "hLundHadron", splitting_list)
for splitting_list in lunds_hadron
]
hDict['hLundHadron'].Scale(1. / n_jets_hadron, "width")
lunds_parton = [lund_gen.result(jet) for jet in all_jets_parton]
[
fill_lund_histogram(hDict, "hLundParton", splitting_list)
for splitting_list in lunds_parton
]
hDict['hLundParton'].Scale(1. / n_jets_parton, "width")
for splitting_list in lunds_parton:
max_kt_recluster = 0
for split in splitting_list:
kt = split.kt()
if kt > max_kt_recluster:
max_kt_recluster = kt
hDict['hMaxKT_2D'].Fill(np.log(max_kt_recluster), np.log(kt))
plot_histograms(hDict)
def main():
parser = argparse.ArgumentParser(description='pythia8 fastjet on the fly',
prog=os.path.basename(__file__))
pyconf.add_standard_pythia_args(parser)
# could use --py-seed
parser.add_argument('--user-seed',
help='pythia seed',
default=1111,
type=int)
parser.add_argument('--output', default="output.root", type=str)
parser.add_argument('--beta', help='sd beta', default=0, type=float)
parser.add_argument('--jetR', help='jet radius', default=0.4, type=float)
args = parser.parse_args()
if args.user_seed < 0:
args.user_seed = 1111
pinfo('user seed for pythia', args.user_seed)
# mycfg = ['PhaseSpace:pThatMin = 100']
mycfg = ['Random:setSeed=on', 'Random:seed={}'.format(args.user_seed)]
mycfg.append('HadronLevel:all=off')
pythia = pyconf.create_and_init_pythia_from_args(args, mycfg)
if args.nev < 100:
args.nev = 100
# print the banner first
fj.ClusterSequence.print_banner()
print()
# set up our jet definition and a jet selector
jet_R0 = args.jetR
jet_def = fj.JetDefinition(fj.antikt_algorithm, jet_R0)
print(jet_def)
# hadron level - ALICE
max_eta_hadron = 0.9
pwarning('max eta for particles after hadronization set to',
max_eta_hadron)
parts_selector_h = fj.SelectorAbsEtaMax(max_eta_hadron)
jet_selector = fj.SelectorPtMin(20.0) & fj.SelectorPtMax(
100.0) & fj.SelectorAbsEtaMax(max_eta_hadron - 1.05 * jet_R0)
max_eta_parton = max_eta_hadron + 2. * jet_R0
pwarning('max eta for partons set to', max_eta_parton)
parts_selector_p = fj.SelectorAbsEtaMax(max_eta_parton)
outf = ROOT.TFile(
args.output.replace('.root', '_beta{}.root'.format(args.beta)),
'recreate')
outf.cd()
t = ROOT.TTree('t', 't')
tw = RTreeWriter(tree=t)
# event loop
for iev in tqdm.tqdm(range(args.nev)):
if not pythia.next():
continue
parts_pythia_p = pythiafjext.vectorize_select(pythia,
[pythiafjext.kFinal], 0,
True)
parts_pythia_p_selected = parts_selector_p(parts_pythia_p)
hstatus = pythia.forceHadronLevel()
if not hstatus:
pwarning('forceHadronLevel false event', iev)
continue
# parts_pythia_h = pythiafjext.vectorize_select(pythia, [pythiafjext.kHadron, pythiafjext.kCharged])
parts_pythia_h = pythiafjext.vectorize_select(pythia,
[pythiafjext.kFinal], 0,
True)
parts_pythia_h_selected = parts_selector_h(parts_pythia_h)
parts_pythia_hch = pythiafjext.vectorize_select(
pythia, [pythiafjext.kFinal, pythiafjext.kCharged], 0, True)
parts_pythia_hch_selected = parts_selector_h(parts_pythia_hch)
# pinfo('debug partons...')
# for p in parts_pythia_p_selected:
# pyp = pythiafjext.getPythia8Particle(p)
# print(pyp.name())
# pinfo('debug hadrons...')
# for p in parts_pythia_h_selected:
# pyp = pythiafjext.getPythia8Particle(p)
# print(pyp.name())
# pinfo('debug ch. hadrons...')
# for p in parts_pythia_hch_selected:
# pyp = pythiafjext.getPythia8Particle(p)
# print(pyp.name())
# parts = pythiafjext.vectorize(pythia, True, -1, 1, False)
jets_p = fj.sorted_by_pt(jet_def(parts_pythia_p))
jets_h = fj.sorted_by_pt(jet_def(parts_pythia_h))
jets_ch_h = fj.sorted_by_pt(jet_selector(jet_def(parts_pythia_hch)))
sd = fjcontrib.SoftDrop(args.beta, 0.1, jet_R0)
for i, jchh in enumerate(jets_ch_h):
# match hadron (full) jet
for j, jh in enumerate(jets_h):
drhh = jchh.delta_R(jh)
if drhh < jet_R0 / 2.:
# match parton level jet
for k, jp in enumerate(jets_p):
dr = jh.delta_R(jp)
if dr < jet_R0 / 2.:
jchh_sd = sd.result(jchh)
jchh_sd_info = fjcontrib.get_SD_jet_info(jchh_sd)
jh_sd = sd.result(jh)
jh_sd_info = fjcontrib.get_SD_jet_info(jh_sd)
jp_sd = sd.result(jp)
jp_sd_info = fjcontrib.get_SD_jet_info(jp_sd)
# pwarning('event', iev)
# pinfo('matched jets: ch.h:', jchh.pt(), 'h:', jh.pt(), 'p:', jp.pt(), 'dr:', dr)
tw.fill_branch('iev', iev)
tw.fill_branch('ch', jchh)
tw.fill_branch('h', jh)
tw.fill_branch('p', jp)
tw.fill_branch('p_zg', jp_sd_info.z)
tw.fill_branch('p_Rg', jp_sd_info.dR)
tw.fill_branch('p_thg', jp_sd_info.dR / jet_R0)
tw.fill_branch('p_mug', jp_sd_info.mu)
tw.fill_branch('h_zg', jh_sd_info.z)
tw.fill_branch('h_Rg', jh_sd_info.dR)
tw.fill_branch('h_thg', jh_sd_info.dR / jet_R0)
tw.fill_branch('h_mug', jh_sd_info.mu)
tw.fill_branch('ch_zg', jchh_sd_info.z)
tw.fill_branch('ch_Rg', jchh_sd_info.dR)
tw.fill_branch('ch_thg', jchh_sd_info.dR / jet_R0)
tw.fill_branch('ch_mug', jchh_sd_info.mu)
tw.fill_tree()
#print(" |-> SD jet params z={0:10.3f} dR={1:10.3f} mu={2:10.3f}".format(sd_info.z, sd_info.dR, sd_info.mu))
pythia.stat()
outf.Write()
outf.Close()
