def run_model_2():
storage = StorageFactory().get_storage('dict_storage')
storage.write_table(table_name='households',
table_data=household_data)
households = HouseholdDataset(in_storage=storage,
in_table_name='households')
storage.write_table(table_name='gridcells',
table_data=gridcell_data)
gridcells = GridcellDataset(in_storage=storage,
in_table_name='gridcells')
hlcm = HouseholdLocationChoiceModelCreator().get_model(
location_set=gridcells,
compute_capacity_flag=False,
choices="opus_core.random_choices_from_index",
sample_size_locations=8)
hlcm.run(specification,
coefficients,
agent_set=households,
debuglevel=1)
# get results
gridcells.compute_variables(
["urbansim.gridcell.number_of_households"],
resources=Resources({"household": households}))
result_more_attractive = gridcells.get_attribute_by_id(
"number_of_households",
arange(ngcs_attr) + 1)
result_less_attractive = gridcells.get_attribute_by_id(
"number_of_households", arange(ngcs_attr + 1, ngcs + 1))
return array(
[result_more_attractive.sum(),
result_less_attractive.sum()])
def run_ALCM(niter):
nhhs = 100
ngcs = 10
ngcs_attr = ngcs/2
ngcs_noattr = ngcs - ngcs_attr
hh_grid_ids = array(nhhs*[-1])
storage = StorageFactory().get_storage('dict_storage')
households_table_name = 'households'
storage.write_table(
table_name = households_table_name,
table_data = {
'household_id': arange(nhhs)+1,
'grid_id': hh_grid_ids
}
)
gridcells_table_name = 'gridcells'
storage.write_table(
table_name = gridcells_table_name,
table_data = {
'grid_id': arange(ngcs)+1,
'cost':array(ngcs_attr*[100]+ngcs_noattr*[1000])
}
)
households = HouseholdDataset(in_storage=storage, in_table_name=households_table_name)
gridcells = GridcellDataset(in_storage=storage, in_table_name=gridcells_table_name)
# create coefficients and specification
coefficients = Coefficients(names=('costcoef', ), values=(-0.001,))
specification = EquationSpecification(variables=('gridcell.cost', ), coefficients=('costcoef', ))
logger.be_quiet()
result = zeros((niter,ngcs))
for iter in range(niter):
hlcm = HouseholdLocationChoiceModelCreator().get_model(location_set=gridcells, compute_capacity_flag=False,
choices = 'opus_core.random_choices_from_index',
sampler=None,
#sample_size_locations = 30
)
hlcm.run(specification, coefficients, agent_set=households, debuglevel=1,
chunk_specification={'nchunks':1})
# get results
gridcells.compute_variables(['urbansim.gridcell.number_of_households'],
resources=Resources({'household':households}))
result_more_attractive = gridcells.get_attribute_by_id('number_of_households', arange(ngcs_attr)+1)
result_less_attractive = gridcells.get_attribute_by_id('number_of_households', arange(ngcs_attr+1, ngcs+1))
households.set_values_of_one_attribute(attribute='grid_id', values=hh_grid_ids)
gridcells.delete_one_attribute('number_of_households')
result[iter,:] = concatenate((result_more_attractive, result_less_attractive))
#print result #, result_more_attractive.sum(), result_less_attractive.sum()
return result
def run_model_2():
storage = StorageFactory().get_storage('dict_storage')
storage.write_table(table_name = 'households', table_data = household_data)
households = HouseholdDataset(in_storage=storage, in_table_name='households')
storage.write_table(table_name = 'gridcells', table_data = gridcell_data)
gridcells = GridcellDataset(in_storage=storage, in_table_name='gridcells')
hlcm = HouseholdLocationChoiceModelCreator().get_model(location_set=gridcells, compute_capacity_flag=False,
choices = "opus_core.random_choices_from_index", sample_size_locations = 8)
hlcm.run(specification, coefficients, agent_set=households, debuglevel=1)
# get results
gridcells.compute_variables(["urbansim.gridcell.number_of_households"],
resources=Resources({"household":households}))
result_more_attractive = gridcells.get_attribute_by_id("number_of_households", arange(ngcs_attr)+1)
result_less_attractive = gridcells.get_attribute_by_id("number_of_households", arange(ngcs_attr+1, ngcs+1))
return array([result_more_attractive.sum(), result_less_attractive.sum()])
def test_agents_do_not_go_to_inferior_locations(self):
"""100 gridcells - 99 with attractiveness 2000, 1 with attractiveness 1, no capacity restrictions
10,000 households
We set the coefficient value for attracitiveness to 1.
"""
storage = StorageFactory().get_storage('dict_storage')
#create households
storage.write_table(table_name='households',
table_data={
'household_id': arange(10000) + 1,
'grid_id': array(10000 * [-1])
})
households = HouseholdDataset(in_storage=storage,
in_table_name='households')
# create gridcells
storage.write_table(table_name='gridcells',
table_data={
'grid_id': arange(100) + 1,
'attractiveness': array(99 * [2000] + [1])
})
gridcells = GridcellDataset(in_storage=storage,
in_table_name='gridcells')
# create coefficients and specification
coefficients = Coefficients(names=("attractcoef", ), values=(1, ))
specification = EquationSpecification(
variables=("gridcell.attractiveness", ),
coefficients=("attractcoef", ))
# run the model
hlcm = HouseholdLocationChoiceModelCreator().get_model(
location_set=gridcells,
compute_capacity_flag=False,
choices="opus_core.random_choices_from_index",
sample_size_locations=30)
hlcm.run(specification,
coefficients,
agent_set=households,
debuglevel=1)
# get results
gridcells.compute_variables(["urbansim.gridcell.number_of_households"],
resources=Resources(
{"household": households}))
result = gridcells.get_attribute_by_id("number_of_households", 100)
# nobody should choose gridcell 100
self.assertEqual(result, 0, "Error: %s is not equal to 0" % (result, ))
def xtest_gracefully_handle_empty_choice_sets(self):
storage = StorageFactory().get_storage('dict_storage')
#create households
storage.write_table(table_name='households',
table_data={
'household_id': arange(10000) + 1,
'grid_id': array(100 * range(100)) + 1
})
households = HouseholdDataset(in_storage=storage,
in_table_name='households')
# create gridcells
storage.write_table(table_name='gridcells',
table_data={
'grid_id': arange(100) + 1,
'residential_units': array(100 * [100])
})
gridcells = GridcellDataset(in_storage=storage,
in_table_name='gridcells')
# create coefficients and specification
coefficients = Coefficients(names=("dummy", ), values=(0, ))
specification = EquationSpecification(
variables=("gridcell.residential_units", ),
coefficients=("dummy", ))
# run the model
hlcm = HouseholdLocationChoiceModelCreator().get_model(
location_set=gridcells,
choices="opus_core.random_choices_from_index",
sample_size_locations=30)
hlcm.run(specification,
coefficients,
agent_set=households,
debuglevel=1)
# get results
gridcells.compute_variables(["urbansim.gridcell.number_of_households"],
resources=Resources(
{"household": households}))
result = gridcells.get_attribute_by_id("number_of_households", 100)
# nobody should choose gridcell 100
self.assertEqual(ma.allclose(result.sum(), 0, rtol=0), True,
"Error: %s is not equal to 0" % (result.sum(), ))
def test_agents_do_not_go_to_inferior_locations(self):
"""100 gridcells - 99 with attractiveness 2000, 1 with attractiveness 1, no capacity restrictions
10,000 households
We set the coefficient value for attracitiveness to 1.
"""
storage = StorageFactory().get_storage('dict_storage')
#create households
storage.write_table(table_name='households',
table_data = {
'household_id': arange(10000)+1,
'grid_id': array(10000*[-1])
}
)
households = HouseholdDataset(in_storage=storage, in_table_name='households')
# create gridcells
storage.write_table(table_name='gridcells',
table_data = {
'grid_id': arange(100)+1,
'attractiveness':array(99*[2000]+[1])
}
)
gridcells = GridcellDataset(in_storage=storage, in_table_name='gridcells')
# create coefficients and specification
coefficients = Coefficients(names=("attractcoef", ), values=(1,))
specification = EquationSpecification(variables=("gridcell.attractiveness", ), coefficients=("attractcoef", ))
# run the model
hlcm = HouseholdLocationChoiceModelCreator().get_model(location_set=gridcells, compute_capacity_flag=False,
choices = "opus_core.random_choices_from_index", sample_size_locations = 30)
hlcm.run(specification, coefficients, agent_set = households, debuglevel=1)
# get results
gridcells.compute_variables(["urbansim.gridcell.number_of_households"],
resources=Resources({"household":households}))
result = gridcells.get_attribute_by_id("number_of_households", 100)
# nobody should choose gridcell 100
self.assertEqual(result, 0, "Error: %s is not equal to 0" % (result,))
def xtest_gracefully_handle_empty_choice_sets(self):
storage = StorageFactory().get_storage('dict_storage')
#create households
storage.write_table(table_name='households',
table_data = {
'household_id': arange(10000)+1,
'grid_id': array(100*range(100))+1
}
)
households = HouseholdDataset(in_storage=storage, in_table_name='households')
# create gridcells
storage.write_table(table_name='gridcells',
table_data = {
'grid_id': arange(100)+1,
'residential_units':array(100*[100])
}
)
gridcells = GridcellDataset(in_storage=storage, in_table_name='gridcells')
# create coefficients and specification
coefficients = Coefficients(names=("dummy",), values=(0,))
specification = EquationSpecification(variables=("gridcell.residential_units",), coefficients=("dummy",))
# run the model
hlcm = HouseholdLocationChoiceModelCreator().get_model( location_set=gridcells,
choices = "opus_core.random_choices_from_index", sample_size_locations = 30)
hlcm.run(specification, coefficients, agent_set=households, debuglevel=1)
# get results
gridcells.compute_variables(["urbansim.gridcell.number_of_households"],
resources=Resources({"household":households}))
result = gridcells.get_attribute_by_id("number_of_households", 100)
# nobody should choose gridcell 100
self.assertEqual(ma.allclose(result.sum(), 0 , rtol=0),
True, "Error: %s is not equal to 0" % (result.sum(),))
def test_place_agents_to_correct_areas(self):
"""10 gridcells - 5 in area 1, 5 in area 2, with equal cost, no capacity restrictions
100 households - 70 live in area 1, 30 live in area 2.
We set the coefficient value for cost -0.001.
"""
storage = StorageFactory().get_storage('dict_storage')
nhhs = 100
ngcs = 10
ngcs_attr = ngcs/2
hh_grid_ids = array(nhhs*[-1])
lareas = array(ngcs_attr*[1] + ngcs_attr*[2])
hh_lareas = array(70*[1] + 30*[2])
household_data = {
'household_id': arange(nhhs)+1,
'grid_id': hh_grid_ids,
'faz_id': hh_lareas
}
gridcell_data = {
'grid_id': arange(ngcs)+1,
'cost':array(ngcs*[100]),
'faz_id': lareas
}
storage.write_table(table_name = 'households', table_data = household_data)
storage.write_table(table_name = 'gridcells', table_data = gridcell_data)
households = HouseholdDataset(in_storage=storage, in_table_name='households')
gridcells = GridcellDataset(in_storage=storage, in_table_name='gridcells')
# create coefficients and specification
coefficients = Coefficients(names=("costcoef", ), values=(-0.001,))
specification = EquationSpecification(variables=("gridcell.cost", ), coefficients=("costcoef", ))
# check the individual gridcells
def run_model():
households = HouseholdDataset(in_storage=storage, in_table_name='households')
hlcm = SubareaHouseholdLocationChoiceModel(location_set=gridcells, compute_capacity_flag=False,
choices = "opus_core.random_choices_from_index", sample_size_locations = 4, subarea_id_name="faz_id")
hlcm.run(specification, coefficients, agent_set=households, debuglevel=1)
# get results
gridcells.compute_variables(["urbansim.gridcell.number_of_households"],
resources=Resources({"household":households}))
result_area1 = gridcells.get_attribute_by_id("number_of_households", arange(ngcs_attr)+1)
result_area2 = gridcells.get_attribute_by_id("number_of_households", arange(ngcs_attr+1, ngcs+1))
gridcells.delete_one_attribute("number_of_households")
result = concatenate((result_area1, result_area2))
return result
expected_results = array(ngcs_attr*[nhhs*0.7/float(ngcs_attr)] + ngcs_attr*[nhhs*0.3/float(ngcs_attr)])
self.run_stochastic_test(__file__, run_model, expected_results, 10)
# check the exact sum
hlcm = SubareaHouseholdLocationChoiceModel(location_set=gridcells, compute_capacity_flag=False,
choices = "opus_core.random_choices_from_index", sample_size_locations = 4, subarea_id_name="faz_id")
hlcm.run(specification, coefficients, agent_set=households, debuglevel=1)
gridcells.compute_variables(["urbansim.gridcell.number_of_households"],
resources=Resources({"household":households}))
result_area1 = gridcells.get_attribute_by_id("number_of_households", arange(ngcs_attr)+1).sum()
result_area2 = gridcells.get_attribute_by_id("number_of_households", arange(ngcs_attr+1, ngcs+1)).sum()
results = array([result_area1, result_area2])
expected_results = array([70, 30])
self.assertEqual(ma.allequal(expected_results, results), True, "Error, should_be: %s, but result: %s" % (
expected_results, results))
def test_place_agents_to_correct_areas(self):
"""10 gridcells - 5 in area 1, 5 in area 2, with equal cost, no capacity restrictions
100 households - 70 live in area 1, 30 live in area 2.
We set the coefficient value for cost -0.001.
"""
storage = StorageFactory().get_storage('dict_storage')
nhhs = 100
ngcs = 10
ngcs_attr = ngcs/2
hh_grid_ids = array(nhhs*[-1])
lareas = array(ngcs_attr*[1] + ngcs_attr*[2])
hh_lareas = array(70*[1] + 30*[2])
household_data = {
'household_id': arange(nhhs)+1,
'grid_id': hh_grid_ids,
'faz_id': hh_lareas
}
gridcell_data = {
'grid_id': arange(ngcs)+1,
'cost':array(ngcs*[100]),
'faz_id': lareas
}
storage.write_table(table_name = 'households', table_data = household_data)
storage.write_table(table_name = 'gridcells', table_data = gridcell_data)
households = HouseholdDataset(in_storage=storage, in_table_name='households')
gridcells = GridcellDataset(in_storage=storage, in_table_name='gridcells')
# create coefficients and specification
coefficients = Coefficients(names=("costcoef", ), values=(-0.001,))
specification = EquationSpecification(variables=("gridcell.cost", ), coefficients=("costcoef", ))
# check the individual gridcells
def run_model():
households = HouseholdDataset(in_storage=storage, in_table_name='households')
hlcm = SubareaHouseholdLocationChoiceModel(location_set=gridcells, compute_capacity_flag=False,
choices = "opus_core.random_choices_from_index", sample_size_locations = 4, subarea_id_name="faz_id")
hlcm.run(specification, coefficients, agent_set=households, debuglevel=1)
# get results
gridcells.compute_variables(["urbansim.gridcell.number_of_households"],
resources=Resources({"household":households}))
result_area1 = gridcells.get_attribute_by_id("number_of_households", arange(ngcs_attr)+1)
result_area2 = gridcells.get_attribute_by_id("number_of_households", arange(ngcs_attr+1, ngcs+1))
gridcells.delete_one_attribute("number_of_households")
result = concatenate((result_area1, result_area2))
return result
expected_results = array(ngcs_attr*[nhhs*0.7/float(ngcs_attr)] + ngcs_attr*[nhhs*0.3/float(ngcs_attr)])
self.run_stochastic_test(__file__, run_model, expected_results, 10)
# check the exact sum
hlcm = SubareaHouseholdLocationChoiceModel(location_set=gridcells, compute_capacity_flag=False,
choices = "opus_core.random_choices_from_index", sample_size_locations = 4, subarea_id_name="faz_id")
hlcm.run(specification, coefficients, agent_set=households, debuglevel=1)
gridcells.compute_variables(["urbansim.gridcell.number_of_households"],
resources=Resources({"household":households}))
result_area1 = gridcells.get_attribute_by_id("number_of_households", arange(ngcs_attr)+1).sum()
result_area2 = gridcells.get_attribute_by_id("number_of_households", arange(ngcs_attr+1, ngcs+1)).sum()
results = array([result_area1, result_area2])
expected_results = array([70, 30])
self.assertEqual(ma.allequal(expected_results, results), True, "Error, should_be: %s, but result: %s" % (
expected_results, results))
def run_ALCM(niter):
nhhs = 100
ngcs = 10
ngcs_attr = ngcs / 2
ngcs_noattr = ngcs - ngcs_attr
hh_grid_ids = array(nhhs * [-1])
storage = StorageFactory().get_storage('dict_storage')
households_table_name = 'households'
storage.write_table(table_name=households_table_name,
table_data={
'household_id': arange(nhhs) + 1,
'grid_id': hh_grid_ids
})
gridcells_table_name = 'gridcells'
storage.write_table(table_name=gridcells_table_name,
table_data={
'grid_id': arange(ngcs) + 1,
'cost':
array(ngcs_attr * [100] + ngcs_noattr * [1000])
})
households = HouseholdDataset(in_storage=storage,
in_table_name=households_table_name)
gridcells = GridcellDataset(in_storage=storage,
in_table_name=gridcells_table_name)
# create coefficients and specification
coefficients = Coefficients(names=('costcoef', ), values=(-0.001, ))
specification = EquationSpecification(variables=('gridcell.cost', ),
coefficients=('costcoef', ))
logger.be_quiet()
result = zeros((niter, ngcs))
for iter in range(niter):
hlcm = HouseholdLocationChoiceModelCreator().get_model(
location_set=gridcells,
compute_capacity_flag=False,
choices='opus_core.random_choices_from_index',
sampler=None,
#sample_size_locations = 30
)
hlcm.run(specification,
coefficients,
agent_set=households,
debuglevel=1,
chunk_specification={'nchunks': 1})
# get results
gridcells.compute_variables(['urbansim.gridcell.number_of_households'],
resources=Resources(
{'household': households}))
result_more_attractive = gridcells.get_attribute_by_id(
'number_of_households',
arange(ngcs_attr) + 1)
result_less_attractive = gridcells.get_attribute_by_id(
'number_of_households', arange(ngcs_attr + 1, ngcs + 1))
households.set_values_of_one_attribute(attribute='grid_id',
values=hh_grid_ids)
gridcells.delete_one_attribute('number_of_households')
result[iter, :] = concatenate(
(result_more_attractive, result_less_attractive))
#print result #, result_more_attractive.sum(), result_less_attractive.sum()
return result
