def prepare_for_estimate(self, agent_set=None, index_to_unplace=None, portion_to_unplace=1.0, compute_lambda=False, grouping_location_set=None, movers_variable=None, movers_index=None, location_id_variable=None, data_objects={}, *args, **kwargs ): """Put 'location_id_variable' always in, if the location id is to be computed on the estimation set, i.e. if it is not a primary attribute of the estimation set. Set 'index_to_unplace' to None, if 'compute_lambda' is True. In such a case, the annual supply is estimated without unplacing agents. 'grouping_location_set', 'movers_variable' and 'movers_index' must be given, if 'compute_lambda' is True. """ from urbansim.functions import compute_supply_and_add_to_location_set if (agent_set is not None) and (index_to_unplace is not None): if self.location_id_string is not None: agent_set.compute_variables(self.location_id_string, resources=Resources(data_objects)) if portion_to_unplace < 1: unplace_size = int(portion_to_unplace*index_to_unplace.size) end_index_to_unplace = sample_noreplace(index_to_unplace, unplace_size) else: end_index_to_unplace = index_to_unplace logger.log_status("Unplace " + str(end_index_to_unplace.size) + " agents.") agent_set.modify_attribute(self.choice_set.get_id_name()[0], resize(array([-1]), end_index_to_unplace.size), end_index_to_unplace) if compute_lambda: movers = zeros(agent_set.size(), dtype="bool8") if movers_index is not None: movers[movers_index] = 1 agent_set.add_primary_attribute(movers, "potential_movers") self.estimate_config["weights_for_estimation_string"] = self.estimate_config["weights_for_estimation_string"]+"_from_lambda" compute_supply_and_add_to_location_set(self.choice_set, grouping_location_set, self.run_config["number_of_units_string"], self.run_config["capacity_string"], movers_variable, self.estimate_config["weights_for_estimation_string"], resources=Resources(data_objects)) specification, index = prepare_for_estimate(agent_set=agent_set, *args, **kwargs) return (specification, index)
def prepare_for_estimate(self, agent_set=None, filter=None, data_objects=None, *args, **kwargs): specification, agents_index = prepare_for_estimate(agent_set=agent_set, data_objects=data_objects, *args, **kwargs) if filter is not None: filter_condition = agent_set.compute_variables(filter, resources=Resources(data_objects)) agents_index = where(filter_condition)[0] return specification, agents_index