def run(self, location_set, agent_set, agents_index=None, data_objects=None, **kwargs):
if agents_index is None:
agents_index = arange(agent_set.size())
regions = agent_set.get_attribute(self.subarea_id_name)
location_region = location_set.compute_one_variable_with_unknown_package(variable_name="%s" % (self.subarea_id_name), dataset_pool=self.dataset_pool)
valid_region = where(regions[agents_index] > 0)[0]
if valid_region.size > 0:
unique_regions = unique(regions[agents_index][valid_region])
cond_array = zeros(agent_set.size(), dtype="bool8")
cond_array[agents_index[valid_region]] = True
for area in unique_regions:
new_index = where(logical_and(cond_array, regions == area))[0]
self.filter = "%s.%s == %s" % (location_set.get_dataset_name(), self.subarea_id_name, area)
logger.log_status("SJM for area %s" % area)
ScalingJobsModel.run(self, location_set, agent_set, agents_index=new_index, **kwargs)
no_region = where(regions[agents_index] <= 0)[0]
if no_region.size > 0: # run the model for jobs that don't have assigned region
self.filter = None
logger.log_status("SJM for jobs with no area assigned")
choices = ScalingJobsModel.run(self, location_set, agent_set, agents_index=agents_index[no_region], **kwargs)
where_valid_choice = where(choices > 0)[0]
choices_index = location_set.get_id_index(choices[where_valid_choice])
chosen_regions = location_set.get_attribute_by_index(self.subarea_id_name, choices_index)
agent_set.modify_attribute(name=self.subarea_id_name, data=chosen_regions,
index=no_region[where_valid_choice])
def run(self,
location_set,
agent_set,
agents_index=None,
data_objects=None,
**kwargs):
if agents_index is None:
agents_index = arange(agent_set.size())
regions = agent_set.get_attribute(self.subarea_id_name)
location_region = location_set.compute_one_variable_with_unknown_package(
variable_name="%s" % (self.subarea_id_name),
dataset_pool=self.dataset_pool)
valid_region = where(regions[agents_index] > 0)[0]
if valid_region.size > 0:
unique_regions = unique(regions[agents_index][valid_region])
cond_array = zeros(agent_set.size(), dtype="bool8")
cond_array[agents_index[valid_region]] = True
for area in unique_regions:
new_index = where(logical_and(cond_array, regions == area))[0]
self.filter = "%s.%s == %s" % (location_set.get_dataset_name(),
self.subarea_id_name, area)
logger.log_status("SJM for area %s" % area)
ScalingJobsModel.run(self,
location_set,
agent_set,
agents_index=new_index,
**kwargs)
no_region = where(regions[agents_index] <= 0)[0]
if no_region.size > 0: # run the model for jobs that don't have assigned region
self.filter = None
logger.log_status("SJM for jobs with no area assigned")
choices = ScalingJobsModel.run(
self,
location_set,
agent_set,
agents_index=agents_index[no_region],
**kwargs)
where_valid_choice = where(choices > 0)[0]
choices_index = location_set.get_id_index(
choices[where_valid_choice])
chosen_regions = location_set.get_attribute_by_index(
self.subarea_id_name, choices_index)
agent_set.modify_attribute(name=self.subarea_id_name,
data=chosen_regions,
index=no_region[where_valid_choice])
def run(self, geography_set, location_set, agent_set, agents_index=None, **kwargs):
if agents_index is None:
agents_index = arange(agent_set.size())
cond_array = zeros(agent_set.size(), dtype="bool8")
cond_array[agents_index] = True
geography_ids = geography_set.get_id_attribute()
geography_id_name = geography_set.get_id_name()[0]
geographies_of_agents = agent_set.compute_variables(["urbansim_parcel.job.%s" % geography_id_name], dataset_pool = self.dataset_pool)
orig_filter = self.filter
for geography_id in geography_ids:
new_index = where(logical_and(cond_array, geographies_of_agents == geography_id))[0]
if orig_filter is not None:
self.filter = "(urbansim_parcel.building.%s == %s) * %s" % (geography_id_name, geography_id, orig_filter)
else:
self.filter = "urbansim_parcel.building.%s == %s" % (geography_id_name, geography_id)
logger.log_status("SJM for %s %s" % (geography_set.get_dataset_name(), geography_id))
ScalingJobsModel.run(self, location_set, agent_set,
agents_index=new_index, **kwargs)
agent_set.flush_dataset()
def run(self,
geography_set,
location_set,
agent_set,
agents_index=None,
**kwargs):
if agents_index is None:
agents_index = arange(agent_set.size())
cond_array = zeros(agent_set.size(), dtype="bool8")
cond_array[agents_index] = True
geography_ids = geography_set.get_id_attribute()
geography_id_name = geography_set.get_id_name()[0]
geographies_of_agents = agent_set.compute_variables(
["urbansim_parcel.job.%s" % geography_id_name],
dataset_pool=self.dataset_pool)
orig_filter = self.filter
for geography_id in geography_ids:
new_index = where(
logical_and(cond_array,
geographies_of_agents == geography_id))[0]
if orig_filter is not None:
self.filter = "(urbansim_parcel.building.%s == %s) * %s" % (
geography_id_name, geography_id, orig_filter)
else:
self.filter = "urbansim_parcel.building.%s == %s" % (
geography_id_name, geography_id)
logger.log_status("SJM for %s %s" %
(geography_set.get_dataset_name(), geography_id))
ScalingJobsModel.run(self,
location_set,
agent_set,
agents_index=new_index,
**kwargs)
agent_set.flush_dataset()
# self.choice_set.flush_dataset()
# set the right parcels
parcels = agent_set.compute_variables(
["job.disaggregate(building.parcel_id)"],
dataset_pool=self.dataset_pool)
agent_set.modify_attribute(name="parcel_id", data=parcels)