alea.examples package

Submodules

class alea.examples.gaussian_model.GaussianModel(parameter_definition: Optional[Union[Dict[str, dict], List[str]]] = None, **kwargs)[source]

Gaussian measurement model with parameters mu and sigma.

Illustrates how required nominal parameters can be added to the initializer; sigma is fixed in this example.

Parameters: parameter_definition (dict or list, optional (default=None)) – definition of the parameters of the model

Caution

You must define the nominal values of the parameters (mu, sigma) in the parameters definition.

__init__(parameter_definition: Optional[Union[Dict[str, dict], List[str]]] = None, **kwargs)[source]: Initialise a gaussian model.

_generate_data(mu=None, sigma=None)[source]

Generate data from the model.

Parameters

mu (float, optional (default=None)) – mean of the gaussian, if None, the nominal value is used
sigma (float, optional (default=None)) – standard deviation of the gaussian, if None, the nominal value is used

Returns

data generated from the model

Return type

list

_ll(mu=None, sigma=None)[source]

Log-likelihood of the model.

Parameters

mu (float, optional (default=None)) – mean of the gaussian, if None, the nominal value is used
sigma (float, optional (default=None)) – standard deviation of the gaussian, if None, the nominal value is used