def from_dict(cls, copula_dict):
"""Create a new instance from a parameters dictionary.
Args:
params (dict):
Parameters of the distribution, in the same format as the one
returned by the ``to_dict`` method.
Returns:
Multivariate:
Instance of the distribution defined on the parameters.
"""
instance = cls()
instance.univariates = []
instance.columns = copula_dict['columns']
for parameters in copula_dict['univariates']:
instance.univariates.append(Univariate.from_dict(parameters))
instance.covariance = np.array(copula_dict['covariance'])
instance.fitted = True
warnings.warn('`covariance` will be renamed to `correlation` in v0.4.0',
DeprecationWarning)
return instance
def from_dict(cls, copula_dict):
"""Set attributes with provided values."""
instance = cls()
instance.univariates = []
instance.columns = copula_dict['columns']
for parameters in copula_dict['univariates']:
instance.univariates.append(Univariate.from_dict(parameters))
instance.covariance = np.array(copula_dict['covariance'])
instance.fitted = copula_dict['fitted']
instance.distribution = copula_dict['distribution']
if isinstance(instance.distribution, dict):
for k, v in instance.distribution.items():
instance.distribution[k] = Univariate.from_dict(v)
return instance
def from_dict(cls, copula_dict):
"""Set attributes with provided values."""
instance = cls()
instance.distribs = {}
for name, parameters in copula_dict['distribs'].items():
instance.distribs[name] = Univariate.from_dict(parameters)
instance.covariance = np.array(copula_dict['covariance'])
instance.fitted = copula_dict['fitted']
instance.distribution = copula_dict['distribution']
return instance