def test_do_nothing_if_no_agents(self):
storage = StorageFactory().get_storage("dict_storage")
storage.write_table(table_name="households", table_data={"household_id": array([], dtype="int32")})
hh_set = HouseholdDataset(in_storage=storage, in_table_name="households")
storage.write_table(table_name="rates", table_data=self.annual_relocation_rates_for_households_data)
hh_rateset = HouseholdRelocationRateDataset(in_storage=storage, in_table_name="rates")
hrm_resources = Resources({"annual_household_relocation_rate": hh_rateset})
hrm = HouseholdRelocationModelCreator().get_model(debuglevel=2)
hrm_relocation_results = hrm.run(hh_set, resources=hrm_resources)
should_be = 0
self.assertEqual(hrm_relocation_results.size, should_be, msg="Error ")
def test_hrm_all_households_relocate_with_100_percent_probability(self):
"""Creates four groups of households as defined in the setUp method,
and assigns their probability of relocate as 100% (1 because it is a ratio).
Ensure that all 15,000 households decide to relocate.
"""
storage = StorageFactory().get_storage("dict_storage")
storage.write_table(table_name="households", table_data=self.household_data)
hh_set = HouseholdDataset(in_storage=storage, in_table_name="households")
storage.write_table(table_name="rates", table_data=self.annual_relocation_rates_for_households_data)
hh_rateset = HouseholdRelocationRateDataset(in_storage=storage, in_table_name="rates")
hrm_resources = Resources({"annual_household_relocation_rate": hh_rateset})
hrm = HouseholdRelocationModelCreator().get_model(debuglevel=1)
hrm_relocation_results = hrm.run(hh_set, resources=hrm_resources)
should_be = 1500
self.assertEqual(hrm_relocation_results.size, should_be, msg="Error ")
def test_hrm_no_households_relocate_with_0_percent_probability(self):
"""Creates four groups of households as defined in the setUp method,
and assigns their probability of relocate as 0%.
Ensure that all 15,000 households do not decide to relocate.
"""
storage = StorageFactory().get_storage('dict_storage')
annual_relocation_rates_for_households_data = self.annual_relocation_rates_for_households_data
annual_relocation_rates_for_households_data['probability_of_relocating'] = array(4*[0.0])
storage.write_table(table_name = 'households', table_data = self.household_data)
storage.write_table(table_name = 'rates', table_data = annual_relocation_rates_for_households_data)
hh_set = HouseholdDataset(in_storage=storage, in_table_name='households')
hh_rateset = HouseholdRelocationRateDataset(in_storage=storage, in_table_name='rates')
hrm_resources = Resources({'rate_set':hh_rateset})
hrm = HouseholdRelocationModelCreator().get_model(debuglevel=1)
hrm_relocation_results = hrm.run(hh_set,resources=hrm_resources)
should_be = 0
self.assertEqual(hrm_relocation_results.size, should_be, msg = 'Error ')
logger.log_status("submarket defined by %s x %s " % (options.submarket_geography, options.submarket_attribute) )
estimator = HLCMEstimator(config=my_configuration,
save_estimation_results=False)
estimator.simulation_state.set_current_time(2000)
attribute_cache = AttributeCache()
sc = SessionConfiguration()
CLOSE = 0.005 #criterion for convergence
sc.put_data({'CLOSE':CLOSE, 'info_file':info_file})
seed(71) # was: seed(71,110)
## relocate movers
from urbansim.models.household_relocation_model_creator import HouseholdRelocationModelCreator
hrm = HouseholdRelocationModelCreator().get_model(probabilities='urbansim.household_relocation_probabilities',
location_id_name='building_id' )
hrm_resources = hrm.prepare_for_run(rate_storage=attribute_cache,
rate_table='annual_relocation_rates_for_households',
what='households')
hrm_index = hrm.run(agent_set=sc.get_dataset_from_pool('household'),
resources=hrm_resources)
estimator.estimate(spec_py=hlcm_specification,
movers_index=hrm_index,
submarket_definition=(options.submarket_geography, options.submarket_attribute),
alt_sample_size=alt_sample_size,
sampler=sampler,
weight_string = options.weight_string,
aggregate_demand=options.aggregate_demand,
sample_size_from_each_stratum = int(options.sample_size_from_each_stratum),
)
estimator = HLCMEstimator(config=my_configuration,
save_estimation_results=False)
estimator.simulation_state.set_current_time(2000)
attribute_cache = AttributeCache()
sc = SessionConfiguration()
CLOSE = 0.005 #criterion for convergence
sc.put_data({'CLOSE': CLOSE, 'info_file': info_file})
seed(71) # was: seed(71,110)
## relocate movers
from urbansim.models.household_relocation_model_creator import HouseholdRelocationModelCreator
hrm = HouseholdRelocationModelCreator().get_model(
probabilities='urbansim.household_relocation_probabilities',
location_id_name='building_id')
hrm_resources = hrm.prepare_for_run(
rate_storage=attribute_cache,
rate_table='annual_relocation_rates_for_households',
what='households')
hrm_index = hrm.run(agent_set=sc.get_dataset_from_pool('household'),
resources=hrm_resources)
estimator.estimate(
spec_py=hlcm_specification,
movers_index=hrm_index,
submarket_definition=(options.submarket_geography,
options.submarket_attribute),
alt_sample_size=alt_sample_size,
sampler=sampler,