def model_landau(self,
seed=None,
h=None,
m=10000,
s=1000,
show=True,
thresh=False):
seed = self.Ana.draw_signal_distribution(
show=False) if seed is None else seed
h = deepcopy(seed) if h is None else h
h.SetName('h_ml')
n = seed.GetEntries()
h.Reset()
thresholds = [47 * i for i in [150, 160, 170]]
for _ in range(int(n)):
v = gRandom.Landau(m, s)
threshold = thresholds[int(gRandom.Rndm() * len(thresholds))]
h.Fill(v if v > threshold else 0 if thresh else v)
# h.Fill(v if v > 11421 else 0 if thresh else v)
delta = mean([(h.GetBinContent(i) - seed.GetBinContent(i))**2
for i in range(h.GetNbinsX()) if i is not h.FindBin(0)])
seed.SetFillColor(2)
h.SetFillColor(Draw.FillColor)
seed.SetFillStyle(3017)
h.SetFillStyle(3018)
l1 = Draw.make_legend(y2=.76)
l1.AddEntry(h, 'Simulation', 'f')
l1.AddEntry(seed, 'Original', 'f')
self.Draw(h, show=show, leg=l1)
self.Draw(seed,
show=show,
draw_opt='same',
canvas=gROOT.GetListOfCanvases()[-1])
seed.Draw('same')
return delta
def accept(self, x):
result = True
if self.leff:
p = self.efficiency(x)
r = gRandom.Rndm()
if r > p:
result = False
return result
def smear(xt):
xeff = 0.3 + (1.0 - 0.3) / 20 * (xt + 10.0)
# efficiency
x = gRandom.Rndm()
if x > xeff: return None
xsmear = gRandom.Gaus(-2.5, 0.2)
# bias and smear
return xt + xsmear
def mkBG2():
hlim=1.
llim=eta
nbins=10000
xx=[(hlim-llim)*ra.random()+llim for i in range(nbins-1)]+[hlim]
xx.sort()
xbin=[xx[0]-llim]+[xx[i]-xx[i-1] for i in range(1,nbins)]
areaswap=[dsigmade(xx[i])*xbin[i] for i in range(nbins)]
area=[]
area.append(areaswap[0])
for i in range(1,nbins):
area.append(area[i-1]+areaswap[i])
area=[area[i]/area[-1] for i in range(nbins)]
output=[]
for i in range(nn):
random0=gRandom.Rndm()
for j in range(nbins):
if random0<=area[j]:
output.append((j+1)*(hlim-llim)/nbins+llim)
break
return output
def acceptance(acc=0.8):
if gRandom.Rndm() < acc:
return True
else:
return False
DDG4.Geant4Random.setMainInstance(rndm1.get())
rndm1.showStatus()
# Move main geant random instance from rndm1 to rndm2:
# See how gRandom and HepRandom instances move
DDG4.Geant4Random.setMainInstance(rndm1.get())
print 'DEFAULT Engine:', DDG4.CLHEP.HepRandom.getTheEngine().name()
print 'DDG4 DEFAULT:', DDG4.Geant4Random.instance().engine().name()
rndm = DDG4.Geant4Random.instance()
rndm.setSeed(1234)
rndm.showStatus()
for i in xrange(10):
print rndm.name(
), ' -- 0 gRandome.Rndm() -- Shoot random[', i, ']= ', gRandom.Rndm(
)
rndm.setSeed(1234)
for i in xrange(10):
print rndm.name(
), ' -- 1 gRandome.Rndm() -- Shoot random[', i, ']= ', gRandom.Rndm(
)
rndm.setSeed(1234)
for i in xrange(10):
print rndm.name(
), ' -- 2 Geant4Random(CLHEP) -- Shoot random[', i, ']= ', rndm.rndm_clhep(
)
rndm.setSeed(1234)
for i in xrange(10):
# open connection to MySQL server on localhost
db = TSQLServer.Connect("mysql://localhost/test", "nobody", "")
# first clean table of old entries
res = db.Query("DELETE FROM runcatalog")
# start timer
timer = TStopwatch()
timer.Start()
# fill run catalog
for i in range(nfiles):
dataset = "testrun_%d" % i
rawfile = "/v1/data/lead/test/run_%d.root" % i
tag = int(gRandom.Rndm() * 10.)
sql = ins % (dataset, i, evt, evt + 10000, tag, 25.5, "test", "lead",
rawfile, "test run dummy data")
evt += 10000
res = db.Query(sql)
# print("%s" % sql)
# stop timer and print results
timer.Stop()
rtime = timer.RealTime()
ctime = timer.CpuTime()
print("")
print("%d files in run catalog" % nfiles)
print("RealTime=%f seconds, CpuTime=%f seconds" % (rtime, ctime))
# Move main geant random instance from rndm1 to rndm2:
# See how gRandom and HepRandom instances move
DDG4.Geant4Random.setMainInstance(rndm1.get())
logging.info('DEFAULT Engine: %s',
DDG4.CLHEP.HepRandom.getTheEngine().name())
logging.info('DDG4 DEFAULT: %s',
DDG4.Geant4Random.instance().engine().name())
rndm = DDG4.Geant4Random.instance()
rndm.setSeed(1234)
rndm.showStatus()
for i in xrange(10):
logging.info(
"%s -- 0 gRandome.Rndm() -- Shoot random[[%d]= %f",
rndm.name(), i, gRandom.Rndm())
rndm.setSeed(1234)
for i in xrange(10):
logging.info(
"%s -- 1 gRandome.Rndm() -- Shoot random[[%d]= %f",
rndm.name(), i, gRandom.Rndm())
rndm.setSeed(1234)
for i in xrange(10):
logging.info(
"%s -- 2 Geant4Random(CLHEP) -- Shoot random[[%d]= %f",
rndm.name(), i, rndm.rndm_clhep())
rndm.setSeed(1234)
for i in xrange(10):
# rndm2.showStatus()
DDG4.Geant4Random.setMainInstance(rndm1.get())
rndm1.showStatus()
# Move main geant random instance from rndm1 to rndm2:
# See how gRandom and HepRandom instances move
DDG4.Geant4Random.setMainInstance(rndm1.get())
logger.info('DEFAULT Engine: %s', DDG4.CLHEP.HepRandom.getTheEngine().name())
logger.info('DDG4 DEFAULT: %s', DDG4.Geant4Random.instance().engine().name())
rndm = DDG4.Geant4Random.instance()
rndm.setSeed(1234)
rndm.showStatus()
for i in range(10):
logger.info("%s -- 0 gRandome.Rndm() -- Shoot random[[%d]= %f", rndm.name(), i, gRandom.Rndm())
rndm.setSeed(1234)
for i in range(10):
logger.info("%s -- 1 gRandome.Rndm() -- Shoot random[[%d]= %f", rndm.name(), i, gRandom.Rndm())
rndm.setSeed(1234)
for i in range(10):
logger.info("%s -- 2 Geant4Random(CLHEP) -- Shoot random[[%d]= %f", rndm.name(), i, rndm.rndm_clhep())
rndm.setSeed(1234)
for i in range(10):
logger.info("%s -- 3 Geant4Random(CLHEP) -- Shoot random[[%d]= %f", rndm.name(), i, rndm.rndm_clhep())
rndm.setSeed(1234)
for i in range(10):
output_file.cd()
output_ntuple = TNtupleD(
"neutrino_tracks", "neutrino_tracks",
(":".join(variables_names_list[0:nb_saved_variables])))
event_container[variables_names_list.index(
"R_Earth_emitted"
)] = parameters["earth_radius"] + parameters["neutrino_altitude"]
energy = c_double()
c_theta = c_double()
print(toolbox.info, "Generating neutrino tracks...")
for i_event in tqdm(range(parameters["nb_events"])):
# sampling neutrino type, then sample energy / cos_theta
random_number = gRandom.Rndm() * neutrino_global_normalisation
for neutrino_name in neutrino_names_list:
if random_number < neutrino_type_threshold[neutrino_name]:
event_container[variables_names_list.index(
"PDG_code")] = neutrinos_PDG_codes[neutrino_name]
neutrino_spectra_dict[neutrino_name].GetRandom2(energy, c_theta)
break
event_container[variables_names_list.index("E_nu")] = energy.value
event_container[variables_names_list.index("cos_theta_SK")] = c_theta.value
event_container[variables_names_list.index(
"phi")] = gRandom.Rndm() * 2 * math.pi
# calculations
event_container[variables_names_list.index("delta_R_SK")] = 4
event_container[variables_names_list.index("delta_R_SK")] *= \
( event_container[variables_names_list.index("R_Earth_emitted")]**2 ) + \
