本文整理汇总了Python中opus_core.session_configuration.SessionConfiguration.remove_all_datasets方法的典型用法代码示例。如果您正苦于以下问题：Python SessionConfiguration.remove_all_datasets方法的具体用法？Python SessionConfiguration.remove_all_datasets怎么用？Python SessionConfiguration.remove_all_datasets使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类opus_core.session_configuration.SessionConfiguration的用法示例。
在下文中一共展示了SessionConfiguration.remove_all_datasets方法的2个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: SimulationState
# 需要导入模块: from opus_core.session_configuration import SessionConfiguration [as 别名]
# 或者: from opus_core.session_configuration.SessionConfiguration import remove_all_datasets [as 别名]
SimulationState().set_cache_directory(cache_directory)
# SimulationState().set_current_time(year)
SessionConfiguration(new_instance=True,
package_order=package_order,
in_storage=AttributeCache())
for year in range(base_year+1, end_year+1, 1):
SimulationState().set_current_time(year)
# SessionConfiguration(new_instance=True,
# package_order=package_order,
# in_storage=AttributeCache())
dataset_pool=SessionConfiguration().get_dataset_pool()
dataset_pool.remove_all_datasets()
# dataset_pool = DatasetPool(
# package_order=['psrc','urbansim','opus_core'],
# storage=AttributeCache())
proposal_set = dataset_pool.get_dataset("development_project_proposal")
template_component = dataset_pool.get_dataset("development_template_component")
from urbansim_parcel.datasets.development_project_proposal_component_dataset import create_from_proposals_and_template_components
proposal_component = create_from_proposals_and_template_components(proposal_set,
template_component,
dataset_pool=dataset_pool)
proposal_component.write_dataset(out_storage=AttributeCache().get_flt_storage_for_year(year),
out_table_name="development_project_proposal_components")示例2: TestDoingRefinement
# 需要导入模块: from opus_core.session_configuration import SessionConfiguration [as 别名]
# 或者: from opus_core.session_configuration.SessionConfiguration import remove_all_datasets [as 别名]
#.........这里部分代码省略.........
self.assert_(os.path.exists(backup_dir))
expected_dataset_names = [ os.path.basename(p) for p in glob( os.path.join(self.cache_dir, '2020', '*')) ]
dataset_names = [ os.path.basename(p) for p in glob(os.path.join(backup_dir, '*'))]
self.assert_(set(dataset_names).issubset(set(expected_dataset_names)))
self.assertEqual(set(dataset_names).symmetric_difference( set(expected_dataset_names) ), set([]) )
def test_doing_refinements_from_specified_refinement_dataset(self):
self.prepare_cache()
os.system("%(python)s %(script)s -c %(cache_directory)s -s %(start_year)s -e %(end_year)s --refinements-directory=%(refinement_directory)s" %
{'python': sys.executable, 'script': self.script, 'cache_directory': self.cache_dir,
'start_year': 2021, 'end_year': 2022,
'refinement_directory': os.path.join(self.cache_dir, '2000')}
)
simulation_state = SimulationState()
## test refinement for 2021
simulation_state.set_current_time(2021)
jobs = self.dataset_pool.get_dataset('job')
buildings = self.dataset_pool.get_dataset('building')
jobs13_raz3 = jobs.compute_variables('numpy.logical_and(job.sector_id==13, job.disaggregate(parcel.raz_id==3, intermediates=[building]))',
dataset_pool=self.dataset_pool)
jobs13_raz4 = jobs.compute_variables('numpy.logical_and(job.sector_id==13, job.disaggregate(parcel.raz_id, intermediates=[building])==4)',
dataset_pool=self.dataset_pool)
jobs13_raz5 = jobs.compute_variables('numpy.logical_and(job.sector_id==13, job.disaggregate(parcel.raz_id, intermediates=[building])==5 )',
dataset_pool=self.dataset_pool)
jobs_raz5 = jobs.compute_variables('job.disaggregate(parcel.raz_id, intermediates=[building])==5',
dataset_pool=self.dataset_pool)
#check results
self.assertEqual(jobs13_raz3.sum(), 0)
self.assertEqual(jobs13_raz4.sum(), 0)
self.assertEqual(jobs13_raz5.sum() >= 5, True)
self.assertEqual(jobs_raz5.sum(), 7)
expected_nr_sqft = array([6, 0, 3, 6, 1, 6, 5, 0])
## was array([6, 2, 3, 6, 1, 2, 5, 0]),
self.assert_(allclose(buildings.get_attribute('non_residential_sqft'), expected_nr_sqft))
self.dataset_pool.remove_all_datasets()
## test refinement for 2022
simulation_state.set_current_time(2022)
hhs = self.dataset_pool.get_dataset('household')
buildings = self.dataset_pool.get_dataset('building')
hhs_raz6 = hhs.compute_variables('household.disaggregate(building.disaggregate(parcel.raz_id)==6)',
dataset_pool=self.dataset_pool)
hhs_bldg = buildings.compute_variables('building.number_of_agents(household)',
dataset_pool=self.dataset_pool)
#check results
self.assertEqual(hhs_raz6.sum(), 7)
self.assert_(hhs_bldg.sum(), 7 )
self.assert_((hhs_bldg!=0).sum(), 2)
self.assert_(buildings.get_attribute('residential_units').sum(), 7)
self.dataset_pool.remove_all_datasets()
def test_doing_other_refinements(self):
self.prepare_cache()
os.system("%(python)s %(script)s -c %(cache_directory)s -s %(start_year)s -e %(end_year)s" %
{'python': sys.executable, 'script': self.script, 'cache_directory':self.cache_dir,
'start_year': 2023, 'end_year': 2027 }
)
simulation_state = SimulationState()
## test refinement for 2023
simulation_state.set_current_time(2023)
hhs = self.dataset_pool.get_dataset('household')
hhs_p5 = hhs.compute_variables('household.persons>5')
#check results
self.assert_(hhs.size(), 2)
self.assertEqual(hhs_p5.sum(), 0)
self.dataset_pool.remove_all_datasets()
## test refinement for 2027
simulation_state.set_current_time(2027)
hhs = self.dataset_pool.get_dataset('household')
buildings = self.dataset_pool.get_dataset('building')
persons = self.dataset_pool.get_dataset('person')
hhs_raz6 = hhs.compute_variables('household.disaggregate(building.disaggregate(parcel.raz_id)==6)',
dataset_pool=self.dataset_pool)
hhs_bldg = buildings.compute_variables('building.number_of_agents(household)',
dataset_pool=self.dataset_pool)
#check results
self.assertEqual(hhs_raz6.sum(), 3)
self.assert_(hhs_bldg.sum(), 3 )
self.assert_((hhs_bldg!=0).sum(), 2)
self.assert_(allclose(persons.get_attribute('job_id'), array([-1, -1, -1, -1, 3, 4, 7])))