def fill_osc_prob(self, osc_prob_dict, ecen, czcen,
theta12=None, theta13=None, theta23=None,
deltam21=None, deltam31=None, deltacp=None,
energy_scale=None,**kwargs):
"""
Loops over ecen,czcen and fills the osc_prob_dict maps, with
probabilities calculated according to NuCraft
"""
#Setup NuCraft for the given oscillation parameters
#TODO: compatible with new NuCraft version?
mass_splitting = (1., deltam21, deltam31)
mixing_angles = [(1,2,np.rad2deg(theta12)),
(1,3,np.rad2deg(theta13),np.rad2deg(deltacp)),
(2,3,np.rad2deg(theta23))]
# NOTE: (TCA - 25 March 2015) We are not using
# self.earth_model, because the earth models are configured
# according to prob3 specifications, but NuCraft needs a
# completely different type of earth model, because it is
# treated differently. For now, don't change the earth model
# version in default NuCraft until we figure out how to
# standardize it.
engine = NuCraft(mass_splitting, mixing_angles)
#earthModel = self.earth_model)
engine.detectorDepth = self.detector_depth
if self.prop_height != 'sample':
# Fix neutrino production height and detector depth for
# simulating reactor experiments.
# In this case, there should be only one zenith angle corresponding
# to the baseline B. It can be calculated according to:
# cos(zen) = ( (r_E - detectorDepth)**2 + B**2 (r_E + atmHeight)**2 ) \
# / ( 2 * (r_E + detectorDepth) * B)
# with r_E = 6371. km
engine.atmHeight = self.prop_height
# Make input arrays in correct format (nucraft input type 1)
zs, es = np.meshgrid(czcen, ecen)
zs, es = zs.flatten(), es.flatten()
# we need flat lists with probabilities for further processing
shape = int(len(ecen)*len(czcen))
# Apply Energy scaling factor:
if energy_scale is not None:
es *= energy_scale
for prim in osc_prob_dict:
if 'bins' in prim: continue
#Convert the particle into a list of IceCube particle IDs
ps = np.ones_like(es)*get_PDG_ID(prim.rsplit('_', 1)[0])
# run it
logging.debug("Calculating oscillation probabilities for %s at %u points..."
%(prim.rsplit('_', 1)[0], len(ps)))
probs = engine.CalcWeights((ps, es, np.arccos(zs)),
atmMode=self.height_mode,
numPrec=self.num_prec)
logging.debug("...done")
#Bring into correct shape
probs = np.array([ x.reshape(shape).T for x in np.array(probs).T ])
#Fill probabilities into dict
for i, sec in enumerate(['nue', 'numu', 'nutau']):
sec_key = sec+'_bar' if 'bar' in prim else sec
osc_prob_dict[prim][sec_key] = probs[i]
evals,czvals = np.meshgrid(ecen,czcen,indexing='ij')
return evals.flatten(),czvals.flatten()
