Initialization

The class is initialized by passing the following arguments:

location_set

- A dataset of locations to be chosen from.

sampler

- A fully qualified name of the module for sampling alternatives. Default value is ``opus_core.samplers.weighted_sampler''. If this argument is set to None, no sampling is performed.

utilities

- A fully qualified name of the module for computing utilities (see Section 7.6.1). Default value is ``opus_core.linear_utilities''.

probabilities

- A fully qualified name of the module for computing probabilities (see Section 7.6.2). Default value is ``opus_core.mnl_probabilities''.

choices

- A fully qualified name of the module for determining final choices (see Section 7.6.3). Default value is ``opus_core.random_choices''.

interaction_pkg

- This argument is only relevant if there is an explicit implementation of an interaction dataset that corresponds to interaction between agents and choices (such as those from Table 8.2). It then determines the package in which the module lives. Default value is ``urbansim.datasets''.

filter

- It is either a string specifying an attribute name of the filter, or a 1D/2D array giving the filter directly, or a dictionary specifying filter for each submodel. If it is None (default), no filter is applied.

submodel_string

- If model contains submodels, this character string specifies what agent's attribute determines those submodels. If it is None (default), no division into submodels is applied.

run_config

- A collection of additional arguments that control a simulation run. It should be of class Resources.

estimate_config

- A collection of additional arguments that control an estimation run. It should be of class Resources.

The method calls the constructor of its parent class. Then, it creates a Sampler object from the argument sampler using SamplerFactory. It sets value of the argument filter as a class property filter