def create_nuSQuIDS():
global numuSQUIDSDict, numubarSQUIDSDict, nueSQUIDSDict, nuebarSQUIDSDict
# print 'MT: ',etau
# print 'TT: ',tautau
#nuSQBar = nsq.nuSQUIDSAtm(-1,1,400,mutau,tautau,0.0,0.0,beg_ene,end_ene,200,3,nsq.NeutrinoType.antineutrino,True,False)
nuSQ = nsq.nuSQUIDSAtm(-1, 1, 100, mutau, tautau, 0.0, 0.0, beg_ene,
end_ene, 200, 3, nsq.NeutrinoType.neutrino, True,
False)
#print nuSQ.GetNumCos(),nuSQ.GetNumE()
#Muon neutrinos
SetNSQParams(nuSQ, 1)
#SetNSQParams(this_zen,nuSQBar,1)
numu_filename = "/data/user/mamday/newSQuIDS/nuSQuIDS/resources/python/bindings/HD5Files/FourD/Atm-NuMu-Squid-%.4fMT_%.3fTT_%.3fTH_%.3fDM.hdf5" % (
mutau, tautau, th23, dm2)
# numubar_filename = "/data/user/mamday/newSQuIDS/nuSQuIDS/resources/python/bindings/HD5Files/Atm-NuMuBar-Squid-%.4fET%.3fEM.hdf5" % (mutau,tautau)
nue_filename = "/data/user/mamday/newSQuIDS/nuSQuIDS/resources/python/bindings/HD5Files/FourD/Atm-NuE-Squid-%.4fMT_%.3fTT_%.3fTH_%.3fDM.hdf5" % (
mutau, tautau, th23, dm2)
# nuebar_filename = "/data/user/mamday/newSQuIDS/nuSQuIDS/resources/python/bindings/HD5Files/Atm-NuEBar-Squid-%.4fET%.3fEM.hdf5" % (mutau,tautau)
# groupname = "/NuMu%.4fET%.3fEM" % (mutau, tautau)
#nuSQ.WriteStateHDF5(filename,groupname,True,"/")
#Current output
nuSQ.WriteStateHDF5(numu_filename)
#nuSQBar.WriteStateHDF5(numubar_filename)
#Electron neutrinos
SetNSQParams(nuSQ, 0)
#SetNSQParams(this_zen,nuSQBar,0)
#Current output
nuSQ.WriteStateHDF5(nue_filename)
def initialize_nuSQuIDS(self):
czens, energies, initial_flux = self._make_initial_data()
interactions = True
self.nsq_atm = nsq.nuSQUIDSAtm(czens, energies*pc.GeV, 3, nsq.NeutrinoType.both, interactions)
self.nsq_atm.Set_initial_state(initial_flux, nsq.Basis.flavor)
self.nsq_atm.Set_rel_error(1.0e-15)
self.nsq_atm.Set_abs_error(1.0e-15)
self.nsq_atm.EvolveState()
def create_nuSQuIDS():
nuSQ = nsq.nuSQUIDSAtm(-1,1,100,mutau,tautau,0.0,0.0,beg_ene,end_ene,200,3,nsq.NeutrinoType.both,True,True)
#### nuSQBar = nsq.nuSQUIDSAtm(-1,1,100,mutau,tautau,0.0,0.0,beg_ene,end_ene,200,3,nsq.NeutrinoType.antineutrino,True,True)
#Muon neutrinos
SetNSQParams(nuSQ,1)
#SetNSQParams(nuSQBar,1)
for ene in np.linspace(1,1011,1012):
print 'Neutrino',ene,nuSQ.EvalFlavor(1,-1.0,ene*nuSQ.units.GeV,0)
# print 'Anti-Neutrino',ene,nuSQBar.EvalFlavor(1,-1.0,ene*nuSQBar.units.GeV,0)
nuSQ.WriteStateHDF5("Test.hd5")
def make_squids(): file_name = file nuSQ = nsq.nuSQUIDSAtm(file_name) #Neutrinos print "NuToTau",ene,zen,nuSQ.EvalFlavor(2,zen,ene*nuSQ.units.GeV,0) print "NuToMu",ene,zen,nuSQ.EvalFlavor(1,zen,ene*nuSQ.units.GeV,0) print "NuToE",ene,zen,nuSQ.EvalFlavor(0,zen,ene*nuSQ.units.GeV,0) #Anti-Neutrinos print "NuBartoTau",ene,zen,nuSQ.EvalFlavor(2,zen,ene*nuSQ.units.GeV,1) print "NuBarToMu",ene,zen,nuSQ.EvalFlavor(1,zen,ene*nuSQ.units.GeV,1) print "NuBarToE",ene,zen,nuSQ.EvalFlavor(0,zen,ene*nuSQ.units.GeV,1)
def create_nuSQuIDS():
nuSQ = nsq.nuSQUIDSAtm(-1, 1, 100, mutau, tautau, 0.0, 0.0, beg_ene,
end_ene, 200, 3, nsq.NeutrinoType.both, True, True)
#### nuSQBar = nsq.nuSQUIDSAtm(-1,1,100,mutau,tautau,0.0,0.0,beg_ene,end_ene,200,3,nsq.NeutrinoType.antineutrino,True,True)
#Muon neutrinos
SetNSQParams(nuSQ, 1)
#SetNSQParams(nuSQBar,1)
for ene in np.linspace(1, 1011, 1012):
print 'Neutrino', ene, nuSQ.EvalFlavor(1, -1.0, ene * nuSQ.units.GeV,
0)
# print 'Anti-Neutrino',ene,nuSQBar.EvalFlavor(1,-1.0,ene*nuSQBar.units.GeV,0)
nuSQ.WriteStateHDF5("Test.hd5")
def make_squids():
file_name = file
nuSQ = nsq.nuSQUIDSAtm(file_name)
#Neutrinos
print "NuToTau", ene, zen, nuSQ.EvalFlavor(2, zen, ene * nuSQ.units.GeV, 0)
print "NuToMu", ene, zen, nuSQ.EvalFlavor(1, zen, ene * nuSQ.units.GeV, 0)
print "NuToE", ene, zen, nuSQ.EvalFlavor(0, zen, ene * nuSQ.units.GeV, 0)
#Anti-Neutrinos
print "NuBartoTau", ene, zen, nuSQ.EvalFlavor(2, zen, ene * nuSQ.units.GeV,
1)
print "NuBarToMu", ene, zen, nuSQ.EvalFlavor(1, zen, ene * nuSQ.units.GeV,
1)
print "NuBarToE", ene, zen, nuSQ.EvalFlavor(0, zen, ene * nuSQ.units.GeV,
1)
def create_nuSQuIDS(): global numuSQUIDSDict, numubarSQUIDSDict, nueSQUIDSDict, nuebarSQUIDSDict # print 'MT: ',etau # print 'TT: ',tautau #nuSQBar = nsq.nuSQUIDSAtm(-1,1,400,mutau,tautau,0.0,0.0,beg_ene,end_ene,200,3,nsq.NeutrinoType.antineutrino,True,False) nuSQ = nsq.nuSQUIDSAtm(-1,1,100,mutau,tautau,0.0,0.0,beg_ene,end_ene,200,3,nsq.NeutrinoType.neutrino,True,False) #print nuSQ.GetNumCos(),nuSQ.GetNumE() #Muon neutrinos SetNSQParams(nuSQ,1) #SetNSQParams(this_zen,nuSQBar,1) numu_filename = "/data/user/mamday/newSQuIDS/nuSQuIDS/resources/python/bindings/HD5Files/FourD/Atm-NuMu-Squid-%.4fMT_%.3fTT_%.3fTH_%.3fDM.hdf5" % (mutau,tautau,th23,dm2) # numubar_filename = "/data/user/mamday/newSQuIDS/nuSQuIDS/resources/python/bindings/HD5Files/Atm-NuMuBar-Squid-%.4fET%.3fEM.hdf5" % (mutau,tautau) nue_filename = "/data/user/mamday/newSQuIDS/nuSQuIDS/resources/python/bindings/HD5Files/FourD/Atm-NuE-Squid-%.4fMT_%.3fTT_%.3fTH_%.3fDM.hdf5" % (mutau,tautau,th23,dm2) # nuebar_filename = "/data/user/mamday/newSQuIDS/nuSQuIDS/resources/python/bindings/HD5Files/Atm-NuEBar-Squid-%.4fET%.3fEM.hdf5" % (mutau,tautau) # groupname = "/NuMu%.4fET%.3fEM" % (mutau, tautau) #nuSQ.WriteStateHDF5(filename,groupname,True,"/") #Current output nuSQ.WriteStateHDF5(numu_filename) #nuSQBar.WriteStateHDF5(numubar_filename) #Electron neutrinos SetNSQParams(nuSQ,0) #SetNSQParams(this_zen,nuSQBar,0) #Current output nuSQ.WriteStateHDF5(nue_filename)
interactions = True
E_min = 500.0*units.GeV
E_max = 1.0*units.PeV
E_nodes = 100
energy_nodes = nsq.logspace(E_min,E_max,E_nodes)
cth_min = -1.0
cth_max = 0.1
cth_nodes = 20
cth_nodes = nsq.linspace(cth_min,cth_max,cth_nodes)
neutrino_flavors = 3
nsq_atm = nsq.nuSQUIDSAtm(cth_nodes,energy_nodes,neutrino_flavors,nsq.NeutrinoType.both,interactions)
N0 = 1.0e18; Power = -1.0
Eflux = lambda E: N0*E**Power
AtmInitialFlux = np.zeros((len(cth_nodes),len(energy_nodes),2,neutrino_flavors))
for ic,cth in enumerate(nsq_atm.GetCosthRange()):
for ie,E in enumerate(nsq_atm.GetERange()):
AtmInitialFlux[ic][ie][0][0] = 0.0 # nue
AtmInitialFlux[ic][ie][1][0] = 0.0 # bar nue
AtmInitialFlux[ic][ie][0][1] = Eflux(E) # nu mu
AtmInitialFlux[ic][ie][1][1] = Eflux(E) # bar nu mu
AtmInitialFlux[ic][ie][0][2] = Eflux(E) # nu tau
AtmInitialFlux[ic][ie][1][2] = Eflux(E) # bar nu tau
nsq_atm.Set_initial_state(AtmInitialFlux,nsq.Basis.flavor)
def _compute_outputs(self, inputs=None):
"""Compute histograms for output channels."""
logging.debug('Entering nusquids._compute_outputs')
if not isinstance(inputs, MapSet):
raise AssertionError('inputs is not a MapSet object, instead '
'is type {0}'.format(type(inputs)))
# TODO(shivesh): oversampling
# TODO(shivesh): more options
# TODO(shivesh): static function
# TODO(shivesh): hashing
binning = self.input_binning.basename_binning
binning = binning.reorder_dimensions(('coszen', 'energy'),
use_basenames=True)
cz_binning = binning['coszen']
en_binning = binning['energy']
units = nsq.Const()
interactions = False
cz_min = cz_binning.bin_edges.min().m_as('radian')
cz_max = cz_binning.bin_edges.max().m_as('radian')
en_min = en_binning.bin_edges.min().m_as('GeV') * units.GeV
en_max = en_binning.bin_edges.max().m_as('GeV') * units.GeV
cz_centers = cz_binning.weighted_centers.m_as('radian')
en_centers = en_binning.weighted_centers.m_as('GeV') * units.GeV
cz_grid = np.array([cz_min] + cz_centers.tolist() + [cz_max])
en_grid = np.array([en_min] + en_centers.tolist() + [en_max])
nu_flavours = 3
nuSQ = nsq.nuSQUIDSAtm(cz_grid, en_grid, nu_flavours,
nsq.NeutrinoType.both, interactions)
nuSQ.Set_EvalThreads(multiprocessing.cpu_count())
theta12 = self.params['theta12'].value.m_as('radian')
theta13 = self.params['theta13'].value.m_as('radian')
theta23 = self.params['theta23'].value.m_as('radian')
deltam21 = self.params['deltam21'].value.m_as('eV**2')
deltam31 = self.params['deltam21'].value.m_as('eV**2')
# TODO(shivesh): check if deltacp should be in radians
deltacp = self.params['deltacp'].value.m_as('radian')
nuSQ.Set_MixingAngle(0, 1, theta12)
nuSQ.Set_MixingAngle(0, 2, theta13)
nuSQ.Set_MixingAngle(1, 2, theta23)
nuSQ.Set_SquareMassDifference(1, deltam21)
nuSQ.Set_SquareMassDifference(2, deltam31)
nuSQ.Set_CPPhase(0, 2, deltacp)
nuSQ.Set_rel_error(1.0e-10)
nuSQ.Set_abs_error(1.0e-10)
# Pad the edges of the energy, coszen space to cover the entire grid range
cz_shape = cz_binning.shape[0] + 2
en_shape = en_binning.shape[0] + 2
shape = (cz_shape, en_shape) + (2, 3)
initial_state = np.full(shape, np.nan)
def pad_inputs(x):
return np.pad(unp.nominal_values(x.hist), 1, 'edge')
# Third index is selecting nu(0), nubar(1)
# Fourth index is selecting flavour nue(0), numu(1), nutau(2)
initial_state[:, :, 0, 0] = pad_inputs(inputs['nue'])
initial_state[:, :, 1, 0] = pad_inputs(inputs['nuebar'])
initial_state[:, :, 0, 1] = pad_inputs(inputs['numu'])
initial_state[:, :, 1, 1] = pad_inputs(inputs['numubar'])
initial_state[:, :, 0, 2] = np.zeros(pad_inputs(inputs['nue']).shape)
initial_state[:, :, 1, 2] = np.zeros(pad_inputs(inputs['nue']).shape)
if np.any(np.isnan(initial_state)):
raise AssertionError('nan entries in initial_state: '
'{0}'.format(initial_state))
nuSQ.Set_initial_state(initial_state, nsq.Basis.flavor)
# TODO(shivesh): use verbosity level to set this
nuSQ.Set_ProgressBar(True)
nuSQ.EvolveState()
os = self.params['oversample'].value.m
os_binning = binning.oversample(os)
os_cz_binning = os_binning['coszen']
os_en_binning = os_binning['energy']
os_cz_centers = os_cz_binning.weighted_centers.m_as('radians')
os_en_centers = os_en_binning.weighted_centers.m_as('GeV')
fs = {}
for nu in self.output_names:
fs[nu] = np.full(os_binning.shape, np.nan)
for icz, cz_bin in enumerate(os_cz_centers):
for ie, en_bin in enumerate(os_en_centers):
en_bin_u = en_bin * units.GeV
fs['nue'][icz][ie] = nuSQ.EvalFlavor(0, cz_bin, en_bin_u, 0)
fs['nuebar'][icz][ie] = nuSQ.EvalFlavor(0, cz_bin, en_bin_u, 1)
fs['numu'][icz][ie] = nuSQ.EvalFlavor(1, cz_bin, en_bin_u, 0)
fs['numubar'][icz][ie] = nuSQ.EvalFlavor(
1, cz_bin, en_bin_u, 1)
fs['nutau'][icz][ie] = nuSQ.EvalFlavor(2, cz_bin, en_bin_u, 0)
fs['nutaubar'][icz][ie] = nuSQ.EvalFlavor(
2, cz_bin, en_bin_u, 1)
out_binning = self.input_binning.reorder_dimensions(
('coszen', 'energy'), use_basenames=True)
os_out_binning = out_binning.oversample(os)
outputs = []
for key in fs.iterkeys():
if np.any(np.isnan(fs[key])):
raise AssertionError(
'Invalid value computed for {0} oscillated output: '
'\n{1}'.format(key, fs[key]))
map = Map(name=key, binning=os_out_binning, hist=fs[key])
map = map.downsample(os) / float(os)
map = map.reorder_dimensions(self.input_binning)
outputs.append(map)
return MapSet(outputs)
def make_plots():
Emin = 1 * un.GeV
Emax = 10 * un.PeV
energies = nsq.logspace(Emin, Emax, 100)
angles = nsq.linspace(-0.99, -0.98, 2)
# just look at straight up/down
# get MCEq flux there
mag = 0.
angle = 0. #degrees
mceq = MCEqRun(interaction_model='SIBYLL23C',
primary_model=(crf.HillasGaisser2012, 'H3a'),
theta_deg=0.)
mceq.solve()
n_nu = 3
inistate = np.zeros(shape=(2, len(energies), 2, n_nu))
flux = {}
flux['e_grid'] = mceq.e_grid
flux['nue_flux'] = mceq.get_solution('nue', mag) + mceq.get_solution(
'pr_nue', mag)
flux['nue_bar_flux'] = mceq.get_solution(
'antinue', mag) + mceq.get_solution('pr_antinue', mag)
flux['numu_flux'] = mceq.get_solution('numu', mag) + mceq.get_solution(
'pr_numu', mag)
flux['numu_bar_flux'] = mceq.get_solution(
'antinumu', mag) + mceq.get_solution('pr_antinumu', mag)
flux['nutau_flux'] = mceq.get_solution('nutau', mag) + mceq.get_solution(
'pr_nutau', mag)
flux['nutau_bar_flux'] = mceq.get_solution(
'antinutau', mag) + mceq.get_solution('pr_antinutau', mag)
# propagate it with nusquids
for neut_type in range(2):
for flavor in range(n_nu):
flav_key = get_key(flavor, neut_type)
if flav_key == "":
continue
for energy_bin in range(len(energies)):
inistate[0][energy_bin][neut_type][flavor] = get_closest(
energies[energy_bin] / un.GeV, flux['e_grid'],
flux[flav_key])
inistate[1][energy_bin][neut_type][flavor] = get_closest(
energies[energy_bin] / un.GeV, flux['e_grid'],
flux[flav_key])
nus_atm = nsq.nuSQUIDSAtm(angles, energies, n_nu, nsq.NeutrinoType.both,
True)
nus_atm.Set_MixingAngle(0, 1, 0.563942)
nus_atm.Set_MixingAngle(0, 2, 0.154085)
nus_atm.Set_MixingAngle(1, 2, 0.785398)
nus_atm.Set_SquareMassDifference(1, 7.65e-05)
nus_atm.Set_SquareMassDifference(2, 0.00247)
nus_atm.SetNeutrinoCrossSections(xs)
#settting some zenith angle stuff
nus_atm.Set_rel_error(1.0e-6)
nus_atm.Set_abs_error(1.0e-6)
#nus_atm.Set_GSL_step(gsl_odeiv2_step_rk4)
nus_atm.Set_GSL_step(nsq.GSL_STEP_FUNCTIONS.GSL_STEP_RK4)
# we load in the initial state. Generating or Loading from a file
nus_atm.Set_initial_state(inistate, nsq.Basis.flavor)
print("Done setting initial state")
# we turn off the progress bar for jobs run on the cobalts
nus_atm.Set_ProgressBar(False)
nus_atm.Set_IncludeOscillations(True)
print("Evolving State")
nus_atm.EvolveState()
# Evaluate the flux at the energies, flavors, and shit we care about
eval_flux = {}
for flavor in range(3):
for nute in range(2):
key = get_key(flavor, nute)
if key == "":
continue
eval_flux[key] = np.zeros(len(energies))
for energy in range(len(energies)):
powed = energies[energy]
eval_flux[key][energy] = nus_atm.EvalFlavor(
flavor, -0.985, powed, nute)
# multiply the fluxes with total cross sections at that energy
conv_flux = {}
for flavor in flavors.keys():
if flavor == "electron":
i_flav = 0
elif flavor == "muon":
i_flav = 1
else:
i_flav = 2
for neut_type in neut_types.keys():
if neut_type == "neutrino":
i_neut = 0
else:
i_neut = 1
eval_key = get_key(i_flav, i_neut)
for current in currents.keys():
conv_key = "_".join([flavor, neut_type, current])
conv_flux[conv_key] = np.zeros(len(energies))
for energy in range(len(energies)):
powed = energies[energy]
conv_flux[conv_key][
energy] = eval_flux[eval_key][energy] * get_total_flux(
powed, flavors[flavor], neut_types[neut_type],
currents[current])
# sum up the cascades and compare them with the cross sections
casc_fluxes = np.zeros(len(energies))
track_fluxes = np.zeros(len(energies))
for key in conv_flux:
if is_cascade(key):
casc_fluxes += conv_flux[key]
else:
track_fluxes += conv_flux[key]
plt.plot(energies / un.GeV, casc_fluxes, label="Cascades")
plt.plot(energies / un.GeV, track_fluxes, label="Tracks")
plt.xscale('log')
plt.xlim([10**2, 10**7])
plt.yscale('log')
plt.legend()
plt.xlabel("Energy [GeV]", size=14)
plt.ylabel(r"Flux$\cdot\sigma_{total}$ [s GeV sr]$^{-1}$", size=14)
plt.show()