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"Vub",
"delta"
],
"values": {
"distribution": "multivariate_normal",
"central_value": list(val),
"standard_deviation": err.tolist(),
"correlation": corr.tolist()
}
}
]
with open(file_path, 'w') as f:
yaml.dump(dat, f)
for name, ckm_scheme in get_ckm_schemes().items():
file_path = '{}_{}.yaml'.format(FILE,name)
save_ckm(ckm_scheme,file_path,N=10000)
elements in the SM. If set to True, the CKM elements are fixed to
their SM values, which can lead to inconsistent results, but also
to a significant speedup in specific cases.
- ckm_scheme: A string with the name of the class defining the CKM
scheme.
"""
self.eft = eft
self.basis = basis or self._default_bases[self.eft]
par_dict = par_dict or {} # initialize empty if not given
# take missing parameters from flavio defaults
self.par_dict_default = flavio.default_parameters.get_central_all()
self.par_dict_default.update(par_dict)
self._par_dict_sm = None
self.fix_ckm = fix_ckm
try:
self._ckm_scheme = get_ckm_schemes()[ckm_scheme]
self._ckm_scheme_name = ckm_scheme
except:
raise ValueError("CKM scheme '{}' is not defined.".format(ckm_scheme))
self.likelihoods = {}
self.fast_likelihoods = {}
self._custom_likelihoods_dict = custom_likelihoods or {}
self.custom_likelihoods = {}
self._load_likelihoods(include_likelihoods=include_likelihoods,
exclude_likelihoods=exclude_likelihoods)
self._Nexp = Nexp
if exp_cov_folder is not None:
self.load_exp_covariances(exp_cov_folder)
self._sm_cov_loaded = False
try:
if sm_cov_folder is None:
self.load_sm_covariances(get_datapath('smelli', 'data/cache'))