biogeme.model_elements.model_elements module

class biogeme.model_elements.model_elements.ModelElements(expressions, use_jit, database, number_of_draws=None, draws_management=None, user_defined_draws=None, expressions_registry=None)

Bases: object

Container for all key components required to define and estimate a model.

Parameters:

• expressions (dict[str, Expression]) – Dict of expressions to be evaluated.

• use_jit (bool)

• database (Database | None)

• number_of_draws (int | None)

• draws_management (DrawsManagement | None)

• user_defined_draws (dict[str:RandomNumberGeneratorTuple] | None)

• expressions_registry (ExpressionRegistry)

audit()

Audit the model elements

Return type:

AuditTuple

property database: Database

property formula_names: list[str]

classmethod from_expression_and_weight(log_like, database, use_jit, weight=None, number_of_draws=0, draws_management=None, user_defined_draws=None)

Alternative constructor for two expressions.

Parameters:

• log_like (Expression) – Expression for the log-likelihood.

• weight (Expression | None) – Expression for the weight.

• database (Database) – The database containing data.

• number_of_draws (int) – Number of Monte Carlo draws.

• draws_management (DrawsManagement | None) – Optional object managing the draws.

• use_jit (bool)

• user_defined_draws (dict[slice(<class 'str'>, <class 'biogeme.draws.native_draws.RandomNumberGeneratorTuple'>, None)] | None)

Return type:

ModelElements

generate_named_output(function_output)

Assigns parameter name to the entries of the gradient and the hessian

Return type:

NamedFunctionOutput

Parameters:

function_output (FunctionOutput)

is_panel()

Return type:

bool

property loglikelihood: Expression | None

property number_of_observations: int

on_database_update(updated_index)

Update the draws object to remain consistent with the new database

Parameters:

updated_index (Index)

property sample_size: int

property weight: Expression | None