def test_distribute_unplaced_jobs_model(self):
# Places 1750 jobs of sector 15
# gridcell has expected about
# 1 4000 sector 15 jobs 5000 sector 15 jobs
# 1000 sector 1 jobs 1000 sector 1 jobs
# 2 2000 sector 15 jobs 2500 sector 15 jobs
# 1000 sector 1 jobs 1000 sector 1 jobs
# 3 1000 sector 15 jobs 1250 sector 15 jobs
# 1000 sector 1 jobs 1000 sector 1 jobs
# unplaced 1750 sector 15 jobs 0
# create jobs
storage = StorageFactory().get_storage("dict_storage")
job_data = {
"job_id": arange(11750) + 1,
"sector_id": array(7000 * [15] + 3000 * [1] + 1750 * [15]),
"grid_id": array(4000 * [1] + 2000 * [2] + 1000 * [3] + 1000 * [1] + 1000 * [2] + 1000 * [3] + 1750 * [-1]),
}
jobs_table_name = "jobs"
storage.write_table(table_name=jobs_table_name, table_data=job_data)
jobs = JobDataset(in_storage=storage, in_table_name=jobs_table_name)
storage = StorageFactory().get_storage("dict_storage")
building_types_table_name = "building_types"
storage.write_table(table_name=building_types_table_name, table_data={"grid_id": arange(3) + 1})
gridcells = GridcellDataset(in_storage=storage, in_table_name=building_types_table_name)
# run model
model = DistributeUnplacedJobsModel(debuglevel=4)
model.run(gridcells, jobs)
# get results
# no jobs are unplaced
result1 = where(jobs.get_attribute("grid_id") < 0)[0]
self.assertEqual(result1.size, 0)
# the first 10000jobs kept their locations
result2 = jobs.get_attribute_by_index("grid_id", arange(10000))
# logger.log_status(result2)
self.assertEqual(ma.allclose(result2, job_data["grid_id"][0:10000], rtol=0), True)
# run model with filter
# unplace first 500 jobs of sector 15
jobs.modify_attribute(name="grid_id", data=zeros(500), index=arange(500))
# unplace first 500 jobs of sector 1
jobs.modify_attribute(name="grid_id", data=zeros(500), index=arange(7000, 7501))
# place only unplaced jobs of sector 1
model.run(gridcells, jobs, agents_filter="job.sector_id == 1")
# 500 jobs of sector 15 should be unplaced
result3 = where(jobs.get_attribute("grid_id") <= 0)[0]
self.assertEqual(result3.size, 500)
# jobs of sector 1 are placed
result4 = jobs.get_attribute_by_index("grid_id", arange(7000, 7501))
self.assertEqual((result4 <= 0).sum(), 0)
def test_run_model_with_known_buildings(self):
storage = self.storage
storage.write_table(
table_name = 'buildings',
table_data = {
'building_id': array([1,2,3,4,5,6,7]),
'parcel_id': array([1,1,2,2,2,3,3]),
'is_residential': array([0,0,0,1,1,0,0])
}
)
storage.write_table(
table_name = 'employment_events',
table_data = {
'parcel_id': array([2, 2, -1, -1, 1]),
'building_id': array([-1, -1, 6, 7, -1]),
'scheduled_year': array([2006, 2006, 2006, 2006, 2006]),
'number_of_non_home_based_jobs': array([3500, 500, -100, 0, 100]),
'number_of_home_based_jobs': array([0, 20, 0, 10, 0]),
'sector_id': array([1, 2, 15, 2, 1]),
'replace_non_home_based_jobs': array([0, 0, 0, 1, 0])
}
)
# change in 2006
############
# parcel/sector 1 2 3
# 1 +100nhb +3500nhb --
# 2 =0nhb +500nhb/+20hb +10hb
# 15 -- -- -100nhb
dataset_pool = DatasetPool(storage=storage, package_order=['urbansim_parcel', 'urbansim'])
job_set = JobDataset(in_storage=storage)
job_set.modify_attribute('building_id', array(6000*[1] + 4000*[3] + 3000*[6]))
dataset_pool.add_datasets_if_not_included({'job':job_set})
model = EmploymentEventsModel(dataset_pool=dataset_pool)
model.run(dataset_pool.get_dataset('employment_event'), job_set, current_year=2006)
buildings = dataset_pool.get_dataset('building')
jobs_in_sec_1 = buildings.compute_variables(['urbansim_parcel.building.number_of_jobs_of_sector_1'],
dataset_pool=dataset_pool)
jobs_in_sec_2 = buildings.compute_variables(['urbansim_parcel.building.number_of_jobs_of_sector_2'],
dataset_pool=dataset_pool)
jobs_in_sec_15 = buildings.compute_variables(['urbansim_parcel.building.number_of_jobs_of_sector_15'],
dataset_pool=dataset_pool)
self.assertEqual(jobs_in_sec_1[0:2].sum()==4100, True) # parcel 1
self.assertEqual(jobs_in_sec_1[2] == 5500, True) # parcel 2 non-residential
self.assertEqual(jobs_in_sec_1[5:7].sum()==1000, True) # parcel 3
self.assertEqual(jobs_in_sec_2[0:2].sum()==1000, True) # parcel 1
self.assertEqual(jobs_in_sec_2[2] == 1500, True) # parcel 2 non-residential
self.assertEqual(jobs_in_sec_2[3:5].sum() == 20, True) # parcel 2 residential
self.assertEqual(jobs_in_sec_2[5]==100, True) # parcel 3, building 6
self.assertEqual(jobs_in_sec_2[6]==10, True) # parcel 3, building 7
self.assertEqual(jobs_in_sec_15[0:2].sum()==1000, True) # parcel 2 non-residential
self.assertEqual(jobs_in_sec_15[2] == 1000, True) # parcel 2 residential
self.assertEqual(jobs_in_sec_15[5]==900, True) # parcel 3, building 6
def test_same_distribution_after_job_subtraction(self):
"""Removes 1,750 sector_1 jobs, without specifying the distribution across gridcells (so it is assumed equal)
Test that the distribution (in %) of sector 1 jobs across gridcells before and after the subtraction are
relatively equal.
"""
storage = StorageFactory().get_storage('dict_storage')
jobs_set_table_name = 'jobs_set'
storage.write_table(table_name=jobs_set_table_name, table_data=self.jobs_data)
jobs_set = JobDataset(in_storage=storage, in_table_name=jobs_set_table_name)
ect_set_table_name = 'ect_set'
storage.write_table(table_name=ect_set_table_name, table_data=self.annual_employment_control_totals_data)
ect_set = ControlTotalDataset(in_storage=storage, in_table_name=ect_set_table_name, what="employment")
# unplace some jobs
jobs_set.modify_attribute(name="grid_id", data=zeros(int(jobs_set.size()/2)), index=arange(int(jobs_set.size()/2)))
#run model with input Datasets
model = EmploymentTransitionModel()
model.run(year=2000, job_set=jobs_set, control_totals=ect_set, job_building_types=self.job_building_types)
results = jobs_set.size()
should_be = [11250]
self.assertEqual(ma.allequal(should_be, results), True, "Error")
def run_model():
storage = StorageFactory().get_storage('dict_storage')
jobs_set_table_name = 'jobs_set'
storage.write_table(
table_name=jobs_set_table_name,
table_data=self.jobs_data,
)
jobs_set = JobDataset(in_storage=storage, in_table_name=jobs_set_table_name)
model = EmploymentTransitionModel()
model.run(year=2000, job_set=jobs_set, control_totals=ect_set, job_building_types=self.job_building_types)
# check that the distribution of jobs is the same before and after subtracting jobs
results = self.get_count_all_sectors_and_gridcells(jobs_set)
return results
expected_results = array([4000.0/7000.0*5250.0, 1000, 1000, 2000.0/7000.0*5250.0, 1000,
1000, 1000.0/7000.0*5250.0, 1000, 1000])
self.run_stochastic_test(__file__, run_model, expected_results, 10)
def run_model2():
storage = StorageFactory().get_storage('dict_storage')
jobs_set_table_name = 'jobs_set'
storage.write_table(
table_name=jobs_set_table_name,
table_data=self.jobs_data,
)
jobs_set = JobDataset(in_storage=storage, in_table_name=jobs_set_table_name)
model = EmploymentTransitionModel()
model.run(year=2000, job_set=jobs_set, control_totals=ect_set, job_building_types=self.job_building_types)
# check that the distribution of building type is the same before and after subtracting jobs
jobs_set.compute_variables(["urbansim.job.is_in_employment_sector_1_industrial",
"urbansim.job.is_in_employment_sector_2_industrial",
"urbansim.job.is_in_employment_sector_1_commercial",
"urbansim.job.is_in_employment_sector_2_commercial",
"urbansim.job.is_in_employment_sector_1_governmental",
"urbansim.job.is_in_employment_sector_2_governmental"],
resources = Resources({"job_building_type":self.job_building_types}))
result = array([jobs_set.get_attribute("is_in_employment_sector_1_industrial").sum(),
jobs_set.get_attribute("is_in_employment_sector_2_industrial").sum(),
jobs_set.get_attribute("is_in_employment_sector_1_commercial").sum(),
jobs_set.get_attribute("is_in_employment_sector_2_commercial").sum(),
jobs_set.get_attribute("is_in_employment_sector_1_governmental").sum(),
jobs_set.get_attribute("is_in_employment_sector_2_governmental").sum()
])
return result
expected_results = array([3500.0/7000.0*5250.0, 900, 3500.0/7000.0*5250.0, 1800, 0, 300])
self.run_stochastic_test(__file__, run_model2, expected_results, 20)
def test_distribute_unplaced_jobs_model(self):
# Places 1750 jobs of sector 15
# gridcell has expected about
# 1 4000 sector 15 jobs 5000 sector 15 jobs
# 1000 sector 1 jobs 1000 sector 1 jobs
# 2 2000 sector 15 jobs 2500 sector 15 jobs
# 1000 sector 1 jobs 1000 sector 1 jobs
# 3 1000 sector 15 jobs 1250 sector 15 jobs
# 1000 sector 1 jobs 1000 sector 1 jobs
# unplaced 1750 sector 15 jobs 0
# create jobs
storage = StorageFactory().get_storage('dict_storage')
job_data = {
"job_id": arange(11750)+1,
"sector_id": array(7000*[15]+3000*[1]+1750*[15]),
"grid_id":array(4000*[1]+2000*[2]+1000*[3]+1000*[1]+1000*[2]+1000*[3]+1750*[-1])
}
jobs_table_name = 'jobs'
storage.write_table(table_name=jobs_table_name, table_data=job_data)
jobs = JobDataset(in_storage=storage, in_table_name=jobs_table_name)
storage = StorageFactory().get_storage('dict_storage')
building_types_table_name = 'building_types'
storage.write_table(
table_name=building_types_table_name,
table_data={
"grid_id":arange(3)+1
}
)
gridcells = GridcellDataset(in_storage=storage, in_table_name=building_types_table_name)
# run model
model = DistributeUnplacedJobsModel(debuglevel=4)
model.run(gridcells, jobs)
# get results
# no jobs are unplaced
result1 = where(jobs.get_attribute("grid_id")<0)[0]
self.assertEqual(result1.size, 0)
# the first 10000jobs kept their locations
result2 = jobs.get_attribute_by_index("grid_id", arange(10000))
# logger.log_status(result2)
self.assertEqual(ma.allclose(result2, job_data["grid_id"][0:10000], rtol=0), True)
# run model with filter
# unplace first 500 jobs of sector 15
jobs.modify_attribute(name='grid_id', data=zeros(500), index=arange(500))
# unplace first 500 jobs of sector 1
jobs.modify_attribute(name='grid_id', data=zeros(500), index=arange(7000, 7501))
# place only unplaced jobs of sector 1
model.run(gridcells, jobs, agents_filter='job.sector_id == 1')
# 500 jobs of sector 15 should be unplaced
result3 = where(jobs.get_attribute("grid_id")<=0)[0]
self.assertEqual(result3.size, 500)
# jobs of sector 1 are placed
result4 = jobs.get_attribute_by_index("grid_id", arange(7000, 7501))
self.assertEqual((result4 <= 0).sum(), 0)
def test_run_model_with_known_buildings(self):
storage = self.storage
storage.write_table(table_name='buildings',
table_data={
'building_id': array([1, 2, 3, 4, 5, 6, 7]),
'parcel_id': array([1, 1, 2, 2, 2, 3, 3]),
'is_residential': array([0, 0, 0, 1, 1, 0, 0])
})
storage.write_table(table_name='employment_events',
table_data={
'parcel_id':
array([2, 2, -1, -1, 1]),
'building_id':
array([-1, -1, 6, 7, -1]),
'scheduled_year':
array([2006, 2006, 2006, 2006, 2006]),
'number_of_non_home_based_jobs':
array([3500, 500, -100, 0, 100]),
'number_of_home_based_jobs':
array([0, 20, 0, 10, 0]),
'sector_id':
array([1, 2, 15, 2, 1]),
'replace_non_home_based_jobs':
array([0, 0, 0, 1, 0])
})
# change in 2006
############
# parcel/sector 1 2 3
# 1 +100nhb +3500nhb --
# 2 =0nhb +500nhb/+20hb +10hb
# 15 -- -- -100nhb
dataset_pool = DatasetPool(
storage=storage, package_order=['urbansim_parcel', 'urbansim'])
job_set = JobDataset(in_storage=storage)
job_set.modify_attribute('building_id',
array(6000 * [1] + 4000 * [3] + 3000 * [6]))
dataset_pool.add_datasets_if_not_included({'job': job_set})
model = EmploymentEventsModel(dataset_pool=dataset_pool)
model.run(dataset_pool.get_dataset('employment_event'),
job_set,
current_year=2006)
buildings = dataset_pool.get_dataset('building')
jobs_in_sec_1 = buildings.compute_variables(
['urbansim_parcel.building.number_of_jobs_of_sector_1'],
dataset_pool=dataset_pool)
jobs_in_sec_2 = buildings.compute_variables(
['urbansim_parcel.building.number_of_jobs_of_sector_2'],
dataset_pool=dataset_pool)
jobs_in_sec_15 = buildings.compute_variables(
['urbansim_parcel.building.number_of_jobs_of_sector_15'],
dataset_pool=dataset_pool)
self.assertEqual(jobs_in_sec_1[0:2].sum() == 4100, True) # parcel 1
self.assertEqual(jobs_in_sec_1[2] == 5500,
True) # parcel 2 non-residential
self.assertEqual(jobs_in_sec_1[5:7].sum() == 1000, True) # parcel 3
self.assertEqual(jobs_in_sec_2[0:2].sum() == 1000, True) # parcel 1
self.assertEqual(jobs_in_sec_2[2] == 1500,
True) # parcel 2 non-residential
self.assertEqual(jobs_in_sec_2[3:5].sum() == 20,
True) # parcel 2 residential
self.assertEqual(jobs_in_sec_2[5] == 100, True) # parcel 3, building 6
self.assertEqual(jobs_in_sec_2[6] == 10, True) # parcel 3, building 7
self.assertEqual(jobs_in_sec_15[0:2].sum() == 1000,
True) # parcel 2 non-residential
self.assertEqual(jobs_in_sec_15[2] == 1000,
True) # parcel 2 residential
self.assertEqual(jobs_in_sec_15[5] == 900,
True) # parcel 3, building 6
def test_same_distribution_after_job_subtraction(self):
"""Removes 1,750 sector_1 jobs, without specifying the distribution across gridcells (so it is assumed equal)
Test that the distribution (in %) of sector 1 jobs across gridcells before and after the subtraction are
relatively equal.
"""
storage = StorageFactory().get_storage('dict_storage')
jobs_set_table_name = 'jobs_set'
storage.write_table(table_name=jobs_set_table_name,
table_data=self.jobs_data)
jobs_set = JobDataset(in_storage=storage,
in_table_name=jobs_set_table_name)
ect_set_table_name = 'ect_set'
storage.write_table(
table_name=ect_set_table_name,
table_data=self.annual_employment_control_totals_data)
ect_set = ControlTotalDataset(in_storage=storage,
in_table_name=ect_set_table_name,
what="employment")
# unplace some jobs
jobs_set.modify_attribute(name="grid_id",
data=zeros(int(jobs_set.size() / 2)),
index=arange(int(jobs_set.size() / 2)))
#run model with input Datasets
model = EmploymentTransitionModel()
model.run(year=2000,
job_set=jobs_set,
control_totals=ect_set,
job_building_types=self.job_building_types)
results = jobs_set.size()
should_be = [11250]
self.assertEqual(ma.allequal(should_be, results), True, "Error")
def run_model():
storage = StorageFactory().get_storage('dict_storage')
jobs_set_table_name = 'jobs_set'
storage.write_table(
table_name=jobs_set_table_name,
table_data=self.jobs_data,
)
jobs_set = JobDataset(in_storage=storage,
in_table_name=jobs_set_table_name)
model = EmploymentTransitionModel()
model.run(year=2000,
job_set=jobs_set,
control_totals=ect_set,
job_building_types=self.job_building_types)
# check that the distribution of jobs is the same before and after subtracting jobs
results = self.get_count_all_sectors_and_gridcells(jobs_set)
return results
expected_results = array([
4000.0 / 7000.0 * 5250.0, 1000, 1000, 2000.0 / 7000.0 * 5250.0,
1000, 1000, 1000.0 / 7000.0 * 5250.0, 1000, 1000
])
self.run_stochastic_test(__file__, run_model, expected_results, 10)
def run_model2():
storage = StorageFactory().get_storage('dict_storage')
jobs_set_table_name = 'jobs_set'
storage.write_table(
table_name=jobs_set_table_name,
table_data=self.jobs_data,
)
jobs_set = JobDataset(in_storage=storage,
in_table_name=jobs_set_table_name)
model = EmploymentTransitionModel()
model.run(year=2000,
job_set=jobs_set,
control_totals=ect_set,
job_building_types=self.job_building_types)
# check that the distribution of building type is the same before and after subtracting jobs
jobs_set.compute_variables([
"urbansim.job.is_in_employment_sector_1_industrial",
"urbansim.job.is_in_employment_sector_2_industrial",
"urbansim.job.is_in_employment_sector_1_commercial",
"urbansim.job.is_in_employment_sector_2_commercial",
"urbansim.job.is_in_employment_sector_1_governmental",
"urbansim.job.is_in_employment_sector_2_governmental"
],
resources=Resources({
"job_building_type":
self.job_building_types
}))
result = array([
jobs_set.get_attribute(
"is_in_employment_sector_1_industrial").sum(),
jobs_set.get_attribute(
"is_in_employment_sector_2_industrial").sum(),
jobs_set.get_attribute(
"is_in_employment_sector_1_commercial").sum(),
jobs_set.get_attribute(
"is_in_employment_sector_2_commercial").sum(),
jobs_set.get_attribute(
"is_in_employment_sector_1_governmental").sum(),
jobs_set.get_attribute(
"is_in_employment_sector_2_governmental").sum()
])
return result
expected_results = array([
3500.0 / 7000.0 * 5250.0, 900, 3500.0 / 7000.0 * 5250.0, 1800, 0,
300
])
self.run_stochastic_test(__file__, run_model2, expected_results, 20)
