def get_model(
self,
location_set,
sampler="opus_core.samplers.weighted_sampler",
utilities="opus_core.linear_utilities",
choices="opus_core.random_choices",
probabilities="opus_core.mnl_probabilities",
estimation="opus_core.bhhh_mnl_estimation",
sample_proportion_locations=None,
sample_size_locations=30,
estimation_size_agents=1.0,
compute_capacity_flag=True,
filter=None,
submodel_string=None,
location_id_string=None,
demand_string=None, # if not None, the aggregate demand for locations will be stored in this attribute
run_config=None,
estimate_config=None,
debuglevel=0,
dataset_pool=None):
run_config = merge_resources_if_not_None(
run_config,
[("sample_proportion_locations", sample_proportion_locations),
("sample_size_locations", sample_size_locations),
("compute_capacity_flag", compute_capacity_flag)])
run_config = merge_resources_with_defaults(
run_config,
[("capacity_string", self.capacity_string_default),
("number_of_agents_string", self.number_of_agents_string_default),
("number_of_units_string", self.number_of_units_string_default)])
if demand_string:
run_config["demand_string"] = demand_string
estimate_config = merge_resources_if_not_None(
estimate_config,
[("estimation", estimation),
("sample_proportion_locations", sample_proportion_locations),
("sample_size_locations", sample_size_locations),
("estimation_size_agents", estimation_size_agents)])
estimate_config = merge_resources_with_defaults(
estimate_config, [("weights_for_estimation_string",
self.estimation_weight_string_default)])
return AgentLocationChoiceModel(
location_set,
model_name="Household Location Choice Model",
short_name="HLCM",
sampler=sampler,
utilities=utilities,
probabilities=probabilities,
choices=choices,
filter=filter,
submodel_string=submodel_string,
location_id_string=location_id_string,
run_config=run_config,
estimate_config=estimate_config,
debuglevel=debuglevel,
dataset_pool=dataset_pool)
def get_model(self,
location_set,
sampler="opus_core.samplers.weighted_sampler",
utilities="opus_core.linear_utilities",
choices="opus_core.random_choices",
probabilities="opus_core.mnl_probabilities",
estimation="opus_core.bhhh_mnl_estimation",
sample_proportion_locations=None,
sample_size_locations=20,
estimation_size_agents=1.0,
compute_capacity_flag=False,
filter=None,
submodel_string="sector_id",
run_config=None,
estimate_config=None,
debuglevel=0):
run_config = merge_resources_if_not_None(
run_config,
[("sample_proportion_locations", sample_proportion_locations),
("sample_size_locations", sample_size_locations),
("compute_capacity_flag", compute_capacity_flag)])
run_config = merge_resources_with_defaults(
run_config, [("capacity_string", self.capacity_string_default)])
estimate_config = merge_resources_if_not_None(
estimate_config,
[("estimation", estimation),
("sample_proportion_locations", sample_proportion_locations),
("sample_size_locations", sample_size_locations),
("estimation_size_agents", estimation_size_agents)])
estimate_config = merge_resources_with_defaults(
estimate_config, [("weights_for_estimation_string",
self.estimation_weight_string_default)])
return AgentLocationChoiceModel(location_set, agent_name="job",
model_name="Employment Location Choice Model", \
short_name="ELCM", sampler=sampler, utilities=utilities,
probabilities=probabilities, choices=choices, filter=filter, submodel_string=submodel_string,
run_config=run_config, estimate_config=estimate_config,
debuglevel=debuglevel)
