alea.examples package

Submodules

alea.examples.gaussian_model module

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

Bases: StatisticalModel

A model of a gaussian measurement, where the model has parameters mu and sigma. For illustration, we show how required nominal parameters can be added to the init 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

Module contents