def get_paramsets(args, nuisance_paramset):
"""Make the paramsets for generating the Asmimov MC sample and also running
the MCMC.
"""
asimov_paramset = []
llh_paramset = []
gf_nuisance = [x for x in nuisance_paramset.from_tag(ParamTag.NUISANCE)]
llh_paramset.extend(gf_nuisance)
for parm in llh_paramset:
parm.value = args.__getattribute__(parm.name)
llh_paramset = ParamSet(llh_paramset)
if args.data is not DataType.REAL:
flavor = fr_utils.fr_to_angles(args.injected_ratio)
else:
flavor = fr_utils.fr_to_angles([1, 1, 1])
tag = ParamTag.BESTFIT
asimov_paramset.extend(gf_nuisance)
asimov_paramset.extend([
Param(name='astroFlavorAngle1', value=flavor[0], ranges=[ 0., 1.], std=0.2, tag=tag),
Param(name='astroFlavorAngle2', value=flavor[1], ranges=[-1., 1.], std=0.2, tag=tag),
])
asimov_paramset = ParamSet(asimov_paramset)
return asimov_paramset, llh_paramset
def get_paramsets(args, nuisance_paramset):
"""Make the paramsets for generating the Asmimov MC sample and also running
the MCMC.
"""
asimov_paramset = []
llh_paramset = []
gf_nuisance = [x for x in nuisance_paramset.from_tag(ParamTag.NUISANCE)]
llh_paramset.extend(
[x for x in nuisance_paramset.from_tag(ParamTag.SM_ANGLES)])
llh_paramset.extend(gf_nuisance)
for parm in llh_paramset:
parm.value = args.__getattribute__(parm.name)
boundaries = fr_utils.SCALE_BOUNDARIES[args.dimension]
tag = ParamTag.SCALE
llh_paramset.append(
Param(
name='logLam', value=np.mean(boundaries), ranges=boundaries, std=3,
tex=r'{\rm log}_{10}\left (\Lambda^{-1}' + \
misc_utils.get_units(args.dimension)+r'\right )',
tag=tag
)
)
llh_paramset = ParamSet(llh_paramset)
tag = ParamTag.BESTFIT
if args.data is not DataType.REAL:
flavor_angles = fr_utils.fr_to_angles(args.injected_ratio)
else:
flavor_angles = fr_utils.fr_to_angles([1, 1, 1])
asimov_paramset.extend(gf_nuisance)
asimov_paramset.extend([
Param(name='astroFlavorAngle1',
value=flavor_angles[0],
ranges=[0., 1.],
std=0.2,
tag=tag),
Param(name='astroFlavorAngle2',
value=flavor_angles[1],
ranges=[-1., 1.],
std=0.2,
tag=tag),
])
asimov_paramset = ParamSet(asimov_paramset)
return asimov_paramset, llh_paramset
def get_paramsets(args, nuisance_paramset):
"""Make the paramsets for generating the Asmimov MC sample and also running
the MCMC.
"""
asimov_paramset = []
hypo_paramset = []
hypo_paramset.extend(
[x for x in nuisance_paramset.from_tag(ParamTag.SM_ANGLES)]
)
for parm in hypo_paramset:
parm.value = args.__getattribute__(parm.name)
hypo_paramset = ParamSet(hypo_paramset)
tag = ParamTag.BESTFIT
flavor_angles = fr_utils.fr_to_angles(args.source_ratio)
asimov_paramset.extend([
Param(name='astroFlavorAngle1', value=flavor_angles[0], ranges=[ 0., 1.], std=0.2, tag=tag),
Param(name='astroFlavorAngle2', value=flavor_angles[1], ranges=[-1., 1.], std=0.2, tag=tag),
])
asimov_paramset = ParamSet(asimov_paramset)
return asimov_paramset, hypo_paramset
def triangle_llh(theta, args, asimov_paramset, llh_paramset):
"""Log likelihood function for a given theta."""
if len(theta) != len(llh_paramset):
raise AssertionError(
'Length of MCMC scan is not the same as the input '
'params\ntheta={0}\nparamset]{1}'.format(theta, llh_paramset))
hypo_paramset = asimov_paramset
for param in llh_paramset.from_tag(ParamTag.NUISANCE):
hypo_paramset[param.name].value = param.value
spectral_index = -hypo_paramset['astroDeltaGamma'].value
# Assigning llh_paramset values from theta happens in this function.
fr = fr_utils.flux_averaged_BSMu(theta, args, spectral_index, llh_paramset)
flavor_angles = fr_utils.fr_to_angles(fr)
# print('flavor_angles', list(map(float, flavor_angles)))
for idx, param in enumerate(hypo_paramset.from_tag(ParamTag.BESTFIT)):
param.value = flavor_angles[idx]
if args.likelihood is Likelihood.GOLEMFIT:
llh = gf_utils.get_llh(hypo_paramset)
elif args.likelihood is Likelihood.GF_FREQ:
llh = gf_utils.get_llh_freq(hypo_paramset)
return llh