def on_config_entity_post_save_layer(sender, **kwargs):
"""
Sync tilestache to a ConfigEntity class after the latter is saved
:param **kwargs: optional "db_entity_keys" to limit the layers created to those DbEntities
"""
from footprint.client.configuration.fixture import LayerConfigurationFixture
from footprint.client.configuration.utils import resolve_fixture
# Disable post save publishing on individual layers. The ConfigEntity is controlling publishing
config_entity = InstanceBundle.extract_single_instance(**kwargs)
logger.info("Handler: on_config_entity_post_save_layer for %s" %
config_entity.full_name)
# Create LayerLibrary instances based on each LayerLibrary configuration if the configuration's scope
# matches that of config_entity
client_layer_fixture = resolve_fixture("presentation",
"layer",
LayerConfigurationFixture,
config_entity.schema(),
config_entity=config_entity)
layer_library_configurations = FixtureList(
client_layer_fixture.layer_libraries()).matching_scope(
class_scope=config_entity.__class__)
logger.info("Processing LayerLibrary Configurations %s" % ', '.join(
map(
lambda layer_library_configuration: layer_library_configuration.
key, layer_library_configurations)))
for layer_library_configuration in layer_library_configurations:
_update_or_create_layer_library_and_layers(
config_entity, layer_library_configuration, **kwargs)
reset_queries()
def built_form_sets(self):
return FixtureList([
dict(
scope=GlobalConfig,
key='uf_urban_placetypes',
name='UF Placetypes',
description='BuiltFormSet containing only placetypes',
attribute='building_attribute_set',
clazz=UrbanPlacetype,
client='default'
),
dict(
scope=GlobalConfig,
key='uf_building_types',
name='UF BuildingTypes',
description='BuiltFormSet containing only buildingtypes',
attribute='building_attribute_set',
clazz=BuildingType,
client='default'
)
# We never present a Building BuiltFormSet
# dict(
# scope=GlobalConfig,
# key='uf_buildings',
# name='Buildings',
# description='BuiltFormSet containing only buildings',
# attribute='building_attribute_set',
#
# clazz=Building,
# client='default'
# )
]).matching_scope(class_scope=self.config_entity and self.config_entity.__class__)
def default_analysis_module_configurations(self, class_scope=None):
config_entity = self.config_entity
uf_analysis_module = lambda module: 'footprint.main.models.analysis_module.%s' % module
# The Behavior keyspace
behavior_key = BehaviorKey.Fab.ricate
# Used to load Behaviors defined elsewhere
get_behavior = lambda key: Behavior.objects.get(key=behavior_key(key))
return map(
lambda configuration: AnalysisModuleConfiguration.
analysis_module_configuration(config_entity, **configuration),
FixtureList([
dict(class_scope=Scenario,
key=AnalysisModuleKey.MERGE_MODULE,
name='Merge Feature Module',
analysis_tools=[
dict(class_name=uf_analysis_module(
'merge_module.merge_updater_tool.MergeUpdaterTool'
),
key=AnalysisToolKey.MERGE_UPDATER_TOOL,
behavior=get_behavior('update_tool'))
])
]).matching_scope(
class_scope=config_entity and config_entity.__class__))
def regions(self, region_keys=None, class_scope=None):
return FixtureList([
dict(
key='scag',
name='The SCAG Region',
description='Jurisdictions of the SCAG Region',
media=[
MediumFixture(
key=ConfigEntityMediumKey.Fab.ricate('scag_logo'),
name='SCAG Logo',
url='/static/client/{0}/logos/scag_dm.png'.format(
settings.CLIENT))
],
#defaulting to an Irvine view for the moment
bounds=MultiPolygon([
Polygon((
(-117.869537353516, 33.5993881225586),
(-117.869537353516, 33.7736549377441),
(-117.678024291992, 33.7736549377441),
(-117.678024291992, 33.5993881225586),
(-117.869537353516, 33.5993881225586),
))
]))
]).matching_keys(key=region_keys).matching_scope(
class_scope=class_scope)
def default_remote_db_entities(self):
# A list of simple dictionaries containing a key, url and optional hosts array, that describe how to
# configure a remote db_entity. If this method is not overridden, it simply delegates to the parent fixture
is_own_parent = self.parent_fixture.__class__ == self.__class__
return self.parent_fixture.default_remote_db_entities(
) if self.ancestor_config_entity and not is_own_parent else FixtureList(
[])
def users(self, **kwargs):
key = self.config_entity.key
return FixtureList(
# A Region level user for the county
[dict(groups=[self.config_entity.user_group_name(UserGroupKey.ADMIN)],
class_scope=Region,
username='******',
password='******',
email='*****@*****.**'),
# A Project manager level user for each city
dict(groups=[self.config_entity.user_group_name(UserGroupKey.MANAGER)],
class_scope=Project,
# User name is [city]_manager
username='******' % key,
password='******' % key,
email='*****@*****.**' % key),
# A Project user level user for each city
dict(groups=[self.config_entity.user_group_name(UserGroupKey.USER)],
class_scope=Project,
# User name is [city]_manager
username='******' % key,
password='******' % key,
email='*****@*****.**' % key)]
# No Scenario level users (although a group for each Scenario does exist)
).matching_scope(class_scope=self.config_entity.__class__, delete_scope_keys=True)
def users(self, **kwargs):
# A sample user who belongs to the client ConfigEntity's director group
# This user therefore has full permission to all config_entities of the demo client
# A Region level user
region_admin = {
'groups': [self.config_entity.user_group_name(UserGroupKey.ADMIN)],
'class_scope': Region,
'username': '******',
'password': '******',
'first_name': 'scag_dm',
'last_name': 'admin',
'email': '*****@*****.**'
}
# A Project level user for each city
project_manager = {
'groups':
[self.config_entity.user_group_name(UserGroupKey.MANAGER)],
'class_scope': Project,
# User name is [city]_manager
'username': '******' % self.config_entity.key,
'password': '******' % self.config_entity.key,
'first_name': self.config_entity.name,
'last_name': 'Manager',
'email': '*****@*****.**' % self.config_entity.key,
}
# A Scenario level user for each city
user = {
# Make sure to include the groups of all sibling scenarios. Even if they haven't all been
# created yet, the final scenario will capture all scenario groups
#'groups': [scenario.user_group_name(UserGroupKey.USER) for
# scenario in self.config_entity.parent_config_entity.children()],
#'class_scope': Scenario,
# User name is [city]_[i]
#'username': '******' % self.config_entity.parent_config_entity.name.replace(" ", "").lower(),
#'password': '******' % self.config_entity.parent_config_entity.name.replace(" ", "").strip(),
#'first_name': self.config_entity.parent_config_entity.name,
#'last_name': 'Planner',
#'email': '*****@*****.**' % self.config_entity.parent_config_entity.name.replace(" ", "").lower()
'groups': [self.config_entity.user_group_name(UserGroupKey.USER)],
'class_scope': Project,
'username': '******' % self.config_entity.key,
'password': '******' % self.config_entity.key,
'first_name': self.config_entity.name,
'last_name': 'Planner',
'email': '*****@*****.**' % self.config_entity.key,
}
# TODO:
# This is an experiment to not create users that are in the
# fixtures in order to test footprint_init performance without
# as many users. For now, we simply return pass as emtpty array
# to FixtureList()
return FixtureList([region_admin, project_manager,
user]).matching_scope(
class_scope=self.config_entity.__class__,
delete_scope_keys=True)
def import_db_entity_configurations(self, **kwargs):
project = self.config_entity
# The Behavior keyspace
behavior_key = BehaviorKey.Fab.ricate
# Used to load Behaviors defined elsewhere
get_behavior = lambda key: Behavior.objects.get(key=behavior_key(key))
return map(
lambda db_entity_dict: update_or_create_db_entity(project, db_entity_dict['value']),
FixtureList([
# This fixtures tests uploading a layer that came from UF by exporting to GDB
# It verifies that we can handle an existing id column, which gets renamed to id_1
# so that we can add a new primary key
dict(
value=DbEntity(
name='RPLines0414',
key='rplines0414_1111',
url='file:///srv/calthorpe_media/test_uploads/dataset_57180_ed0d4399083743dbbc607a2d6a92c330.sql.zip',
creator=get_user_model().objects.get(username=UserGroupKey.SUPERADMIN),
feature_behavior=FeatureBehavior(
behavior=get_behavior('reference'),
intersection=GeographicIntersection.polygon_to_polygon
),
_categories=[Category(key=DbEntityCategoryKey.KEY_CLASSIFICATION, value=DbEntityCategoryKey.REFERENCE)]
)),
# This fixture tests a largish dataset
dict(
value=DbEntity(
name='CPAD',
key='cpad_1454089444918',
url='file:///tmp/dataset_48424_45cbd88ea090485f93c72df2fd905701.sql.zip',
creator=get_user_model().objects.get(username=UserGroupKey.SUPERADMIN),
feature_behavior=FeatureBehavior(
behavior=get_behavior('reference'),
intersection=GeographicIntersection.polygon_to_polygon
),
_categories=[Category(key=DbEntityCategoryKey.KEY_CLASSIFICATION, value=DbEntityCategoryKey.REFERENCE)]
)),
# This fixture tests a small dataset
dict(
value=DbEntity(
name='Lightrail',
key='lightrail_111111',
url='dataset_48708_d60bf2da001a44e8ab534dced4fb7478.sql.zip',
creator=get_user_model().objects.get(username=UserGroupKey.SUPERADMIN),
feature_behavior=FeatureBehavior(
behavior=get_behavior('reference'),
intersection=GeographicIntersection.polygon_to_polygon
),
_categories=[Category(key=DbEntityCategoryKey.KEY_CLASSIFICATION, value=DbEntityCategoryKey.REFERENCE)]
)),
]))
def default_analysis_module_configurations(self, **kwargs):
config_entity = self.config_entity
uf_analysis_module = lambda module: 'footprint.main.models.analysis_module.%s' % module
behavior_key = BehaviorKey.Fab.ricate
get_behavior = lambda key: Behavior.objects.get(key=behavior_key(key))
return map(
lambda configuration:
AnalysisModuleConfiguration.analysis_module_configuration(config_entity, **configuration),
FixtureList([]).matching_scope(class_scope=self.config_entity and self.config_entity.__class__)
)
def built_form_sets(self):
return self.parent_fixture.built_form_sets() + FixtureList([
dict(
scope=Region,
key='scag_land_uses',
attribute='scag_land_use_definition',
name='SCAG Land Uses',
description='SCAG Land Use Codes',
client='scag_dm',
clazz=BuildingType,
),
]).matching_scope(
class_scope=self.config_entity and self.config_entity.__class__)
def projects(self,
region=None,
region_keys=None,
project_keys=None,
class_scope=None):
return FixtureList([{
'key': 'elk_grv',
'import_key': 'elk_grove',
'name': 'City of Elk Grove',
'description': "City of Elk Grove",
'base_year': 2013,
'region_key': 'sac_cnty',
'media': [],
}]).matching_keys(
region_keys=region_keys,
key=project_keys).matching_scope(class_scope=class_scope)
def scenarios(self, project=None, region_keys=None, project_keys=None, scenario_keys=None, class_scope=None):
# The Behavior keyspace
behavior_key = BehaviorKey.Fab.ricate
# Used to load Behaviors defined elsewhere
get_behavior = lambda key: Behavior.objects.get(key=behavior_key(key))
return FixtureList([
{
'class_scope': BaseScenario,
'key': '{0}_s'.format(project.key),
'scope': project.schema(),
'name': '{0}'.format(project.name),
'description': '{0} layers {1}'.format('2014', project.name),
'year': 2014,
'behavior': get_behavior('base_scenario'),
'categories': [Category(key='category', value='base_year')]
}]).matching_keys(region_key=region_keys, project_key=project.key if project else project_keys, key=scenario_keys).\
matching_scope(class_scope=class_scope)
def update_or_create_layer_library_and_layers(config_entity, **kwargs):
# Create LayerLibrary instances based on each LayerLibrary configuration if the configuration's scope
# matches that of config_entity
client_layer_fixture = resolve_fixture("presentation",
"layer",
LayerConfigurationFixture,
config_entity.schema(),
config_entity=config_entity)
layer_library_configurations = FixtureList(
client_layer_fixture.layer_libraries()).matching_scope(
class_scope=config_entity.__class__)
logger.info("Processing LayerLibrary Configurations %s" % ', '.join(
map(
lambda layer_library_configuration: layer_library_configuration.
key, layer_library_configurations)))
for layer_library_configuration in layer_library_configurations:
_update_or_create_layer_library_and_layers(
config_entity, layer_library_configuration, **kwargs)
def result_libraries(self):
"""
Used to update or create ResultLibraries per ConfigEntity instance
Returns the result library(ies) scoped for the class of self.config_entity
:return:
"""
return FixtureList(
map(
lambda result_library_key: ResultLibraryConfiguration(
key=result_library_key,
name='{0} %s Result Library' % capitalize(
result_library_key),
description='The %s result library for {0}' %
capitalize(result_library_key)), [
ResultLibraryKey.DEFAULT, ResultLibraryKey.APPLICATION,
ResultLibraryKey.WATER, ResultLibraryKey.ENERGY,
ResultLibraryKey.VMT, ResultLibraryKey.FISCAL,
ResultLibraryKey.AGRICULTURE_ANALYSIS,
ResultLibraryKey.PUBLIC_HEALTH
]))
def built_form_sets(self):
return self.parent_fixture.built_form_sets() + FixtureList([
dict(
scope=Region,
key='sacog_building_type',
attribute='building_attribute_set',
name='SACOG Buildingtypes',
description='Built Forms for SACOG',
client='sacog',
clazz=BuildingType,
),
dict(
scope=Region,
key='sacog_rucs',
name='RUCS Types',
attribute='agriculture_attribute_set',
description='SACOG RUCS types',
client=False,
clazz=CropType,
),
]).matching_scope(
class_scope=self.config_entity and self.config_entity.__class__)
def import_scenarios(self, origin_instance):
return FixtureList([
dict(
class_scope=FutureScenario,
key=origin_instance.key[0:10:]+'_future_clone',
name=origin_instance.name[0:10]+' Future Clone',
parent_config_entity=origin_instance.parent_config_entity,
origin_instance=origin_instance,
bounds=origin_instance.bounds,
description=origin_instance.description+' Future Clone',
year=origin_instance.year
),
dict(
class_scope=BaseScenario,
key=origin_instance.key[0:10]+'_base_clone',
name=origin_instance.name[0:10]+' Base Clone',
parent_config_entity=origin_instance.parent_config_entity,
origin_instance=origin_instance,
bounds=origin_instance.bounds,
description=origin_instance.description+' Base Clone',
year=origin_instance.year
)
]).matching_scope(class_scope=origin_instance.__class__)
def regions(self, region_keys=None, class_scope=None):
return FixtureList([
{
'key':
'sac_cnty',
'name':
'Sacramento County',
'description':
'Sacramento County',
'bounds':
MultiPolygon([
Polygon((
(-122.719, 37.394), # bottom left
(-122.719, 38.059), # top left
(-121.603, 38.059), # top right
(-121.603, 37.394), # bottom right
(-122.719,
37.394), # bottom leftsample_config_entities
))
])
},
]).matching_keys(key=region_keys).matching_scope(
class_scope=class_scope)
def scenarios(self,
project=None,
region_keys=None,
project_keys=None,
scenario_keys=None,
class_scope=None):
# The Behavior keyspace
behavior_key = BehaviorKey.Fab.ricate
# Used to load Behaviors defined elsewhere
get_behavior = lambda key: Behavior.objects.get(key=behavior_key(key))
return FixtureList([
{
'class_scope': BaseScenario,
'key': 'base_condition',
'scope': project.schema(),
'name': 'Base Condition',
'description': '{0} Base Scenario {1}'.format('2012', project.name),
'year': 2012,
# Used on the front-end only.
'behavior': get_behavior('base_scenario')
},
{
'class_scope': FutureScenario,
'key': 'scenario_a',
'scope': project.schema(),
'name': 'Scenario A',
'description': 'Future Scenario for {0}'.format(project.name),
'year': 2050,
# Used on the front-end only
'behavior': get_behavior('future_scenario')
}]).matching_keys(
region_key=region_keys,
project_key=project.key if project else None,
key=scenario_keys).\
matching_scope(class_scope=class_scope)
def default_db_entities(self):
"""
Scenarios define DbEntities specific to the Scenario. Creates a list a dictionary of configuration functionality.
These are filtered based on whether the given scenario matches the scope in the configuration
:return:
"""
project = self.config_entity.parent_config_entity_subclassed
scenario = self.config_entity
# The DbEntity keyspace. These keys have no prefix
Key = ScagDmDbEntityKey
# The Behavior keyspace
behavior_key = BehaviorKey.Fab.ricate
# Used to load Behaviors defined elsewhere
get_behavior = lambda key: Behavior.objects.get(key=behavior_key(key))
return super(ScagDmScenarioFixture, self).default_db_entities() + map(
lambda db_entity_dict: update_or_create_db_entity(
scenario, db_entity_dict['value']),
FixtureList([
dict(
class_scope=BaseScenario,
value=DbEntity(
name='2016 SCAG Existing Land Use Parcels',
key=Key.EXISTING_LAND_USE_PARCELS_2016,
feature_class_configuration=FeatureClassConfiguration(
abstract_class=ExistingLandUseParcel,
import_from_db_entity_key=Key.
REGION_EXISTING_LAND_USE_PARCELS,
filter_query=dict(city=project.name),
# primary_geography=True,
# primary_key='source_id',
# primary_key_type='int',
fields=dict(),
related_fields=dict(land_use_definition=dict(
single=True,
related_class_name=
'footprint.client.configuration.scag_dm.built_form.scag_dm_land_use_definition.ScagDmLandUseDefinition',
related_class_join_field_name='land_use',
source_class_join_field_name='scag_lu16'))),
feature_behavior=FeatureBehavior(
behavior=get_behavior('editable_feature')),
_categories=[
Category(
key=DbEntityCategoryKey.KEY_CLASSIFICATION,
value=DbEntityCategoryKey.EDITABLE_LAYER)
])),
dict(
class_scope=BaseScenario,
value=DbEntity(
name='2016 SCAG General Plan Parcels',
key=Key.GENERAL_PLAN_PARCELS,
feature_class_configuration=FeatureClassConfiguration(
abstract_class=GeneralPlanParcels,
primary_key='source_id',
primary_key_type='int',
import_from_db_entity_key=Key.
REGION_GENERAL_PLAN_PARCELS,
filter_query=dict(city=project.name),
fields=dict(),
related_fields=dict(land_use_definition=dict(
single=True,
related_class_name=
'footprint.client.configuration.scag_dm.built_form.scag_dm_land_use_definition.ScagDmLandUseDefinition',
# Use this for the resource type, since we don't want a client-specific resource URL
# TODO not wired up yet
resource_model_class_name=
'footprint.main.models.built_form.ClientLandUseDefinition',
related_class_join_field_name='land_use',
source_class_join_field_name='scag_gp_code16')
)),
feature_behavior=FeatureBehavior(
behavior=get_behavior('editable_feature'),
intersection=AttributeIntersection()),
_categories=[
Category(
key=DbEntityCategoryKey.KEY_CLASSIFICATION,
value=DbEntityCategoryKey.EDITABLE_LAYER)
])),
dict(
class_scope=BaseScenario,
value=DbEntity(
name='2016 SCAG Specific Plan Parcels',
key=Key.SPECIFIC_PLAN_PARCELS,
feature_class_configuration=FeatureClassConfiguration(
abstract_class=SpecificPlanParcels,
primary_key='source_id',
primary_key_type='int',
import_from_db_entity_key=Key.
REGION_SPECIFIC_PLAN_PARCELS,
filter_query=dict(city=project.name),
fields=dict(),
related_fields=dict(land_use_definition=dict(
single=True,
related_class_name=
'footprint.client.configuration.scag_dm.built_form.scag_dm_land_use_definition.ScagDmLandUseDefinition',
resource_model_class_name=
'footprint.main.models.built_form.ClientLandUseDefinition',
related_class_join_field_name='land_use',
source_class_join_field_name='scag_sp_code16')
)),
feature_behavior=FeatureBehavior(
behavior=get_behavior('editable_feature'),
intersection=AttributeIntersection()),
_categories=[
Category(
key=DbEntityCategoryKey.KEY_CLASSIFICATION,
value=DbEntityCategoryKey.EDITABLE_LAYER)
])),
dict(class_scope=BaseScenario,
value=DbEntity(
name='2016 SCAG Infill Parcels',
key=Key.INFILL_PARCELS,
feature_class_configuration=FeatureClassConfiguration(
abstract_class=InfillParcels,
import_from_db_entity_key=Key.
REGION_INFILL_PARCELS,
filter_query=dict(city=project.name),
),
feature_behavior=FeatureBehavior(
behavior=get_behavior('editable_feature'),
intersection=AttributeIntersection()),
_categories=[
Category(
key=DbEntityCategoryKey.KEY_CLASSIFICATION,
value=DbEntityCategoryKey.EDITABLE_LAYER)
])),
dict(
class_scope=BaseScenario,
value=DbEntity(
name='2016 SCAG Zoning Parcels',
key=Key.ZONING_PARCELS,
feature_class_configuration=FeatureClassConfiguration(
abstract_class=ZoningParcels,
primary_key='source_id',
primary_key_type='int',
import_from_db_entity_key=Key.
REGION_ZONING_PARCELS,
filter_query=dict(city=project.name),
fields=dict(),
related_fields=dict(land_use_definition=dict(
single=True,
related_class_name=
'footprint.client.configuration.scag_dm.built_form.scag_dm_land_use_definition.ScagDmLandUseDefinition',
resource_model_class_name=
'footprint.main.models.built_form.ClientLandUseDefinition',
related_class_join_field_name='land_use',
source_class_join_field_name='scag_zn_code16')
)),
feature_behavior=FeatureBehavior(
behavior=get_behavior('editable_feature'),
intersection=AttributeIntersection()),
_categories=[
Category(
key=DbEntityCategoryKey.KEY_CLASSIFICATION,
value=DbEntityCategoryKey.EDITABLE_LAYER)
])),
dict(class_scope=BaseScenario,
value=DbEntity(
name='2016 SCAG Entitlement Parcels',
key=Key.ENTITLEMENT_PARCELS_2016,
feature_class_configuration=FeatureClassConfiguration(
abstract_class=EntitlementParcels,
primary_key='source_id',
primary_key_type='int',
import_from_db_entity_key=Key.
REGION_ENTITLEMENT_PARCELS_2016,
filter_query=dict(city=project.name),
fields=dict()),
feature_behavior=FeatureBehavior(
behavior=get_behavior('editable_feature'),
intersection=GeographicIntersection.
polygon_to_centroid),
_categories=[
Category(
key=DbEntityCategoryKey.KEY_CLASSIFICATION,
value=DbEntityCategoryKey.EDITABLE_LAYER)
])),
dict(class_scope=BaseScenario,
value=DbEntity(
key=Key.SCENARIO_PLANNING_ZONES,
feature_class_configuration=FeatureClassConfiguration(
abstract_class=ScenarioPlanningZones,
import_from_db_entity_key=Key.
REGION_SCENARIO_PLANNING_ZONES,
filter_query=dict(city=project.name),
),
feature_behavior=FeatureBehavior(
behavior=get_behavior('editable_feature'),
intersection=GeographicIntersection.
polygon_to_centroid),
_categories=[
Category(
key=DbEntityCategoryKey.KEY_CLASSIFICATION,
value=DbEntityCategoryKey.REFERENCE)
])),
dict(class_scope=BaseScenario,
value=DbEntity(
name='City/Tier2 TAZ',
key=Key.TIER2_TAZ,
feature_class_configuration=FeatureClassConfiguration(
abstract_class=Tier2Taz,
import_from_db_entity_key=Key.REGION_TIER2_TAZ,
filter_query=dict(city=project.name),
),
feature_behavior=FeatureBehavior(
behavior=get_behavior('sed_editor_tool'),
intersection=AttributeIntersection()),
_categories=[
Category(
key=DbEntityCategoryKey.KEY_CLASSIFICATION,
value=DbEntityCategoryKey.EDITABLE_LAYER)
]))
]).matching_scope(class_scope=self.config_entity
and self.config_entity.__class__))
def default_db_entities(self, **kwargs):
"""
Region specific SACOG db_entity_setups
:param default_dict:
:return:
"""
config_entity = self.config_entity
parent_region_fixture = self.parent_fixture
default_db_entities = parent_region_fixture.default_db_entities()
Key = SacogDbEntityKey
# The Behavior keyspace
behavior_key = BehaviorKey.Fab.ricate
# Used to load Behaviors defined elsewhere
get_behavior = lambda key: Behavior.objects.get(key=behavior_key(key))
if self.config_entity.key == 'sacog':
# Block the client-level region. We just want real regions
return []
remote_db_entity_setups = FixtureList(
map(
lambda db_entity: update_or_create_db_entity(
config_entity, db_entity),
self.default_remote_db_entities()))
# TODO: Disabled the 'sacog_background' 'remote db entity' b/c it is throwing errors (2016-07-06)
# return default_db_entities + remote_db_entity_setups + FixtureList([
return default_db_entities + FixtureList([
update_or_create_db_entity(
config_entity,
DbEntity(
key=DbEntityKey.REGION_PRIMARY_GEOGRAPHY,
# Override. If a name override is supplied, put it in. Otherwise leave null to derive it from the key
name='Urban Base Canvas (UF)',
# name=get_property_path(kwargs, 'overrides.%s.name' % Key.BASE),
feature_class_configuration=FeatureClassConfiguration(
abstract_class=CanvasFeature,
# The Base Feature is normally considered a primary_geography unless overridden
primary_geography=True,
primary_key='geography_id',
primary_key_type='int',
# The Base Feature is normally associated to a subclass of Geography unless overridden
geography_class_name=get_property_path(
kwargs, 'overrides.%s.geography_class_name' %
Key.BASE_CANVAS)
or 'footprint.main.models.geographies.parcel.Parcel',
# Create a built_form ForeignKey to a single BuiltForm,
# by initially joining our 'built_form_key' attribute to its 'key' attribute
related_fields=dict(built_form=dict(
single=True,
related_class_name=uf_model(
'built_form.built_form.BuiltForm'),
source_class_join_field_name='built_form_key',
related_class_join_field_name='key',
))),
feature_behavior=FeatureBehavior(
behavior=get_behavior('base_feature'), ),
_categories=[
Category(key=DbEntityCategoryKey.KEY_CLASSIFICATION,
value=DbEntityCategoryKey.REFERENCE)
])),
update_or_create_db_entity(
config_entity,
DbEntity(key=Key.CENSUS_TRACTS,
feature_class_configuration=FeatureClassConfiguration(
abstract_class=CensusTract),
feature_behavior=FeatureBehavior(
behavior=get_behavior('reference'),
intersection=GeographicIntersection.
polygon_to_polygon),
_categories=[
Category(
key=DbEntityCategoryKey.KEY_CLASSIFICATION,
value=DbEntityCategoryKey.REFERENCE)
])),
update_or_create_db_entity(
config_entity,
DbEntity(key=Key.CENSUS_BLOCKGROUPS,
feature_class_configuration=FeatureClassConfiguration(
abstract_class=CensusBlockgroup),
feature_behavior=FeatureBehavior(
behavior=get_behavior('reference'),
intersection=GeographicIntersection.
polygon_to_centroid),
_categories=[
Category(
key=DbEntityCategoryKey.KEY_CLASSIFICATION,
value=DbEntityCategoryKey.REFERENCE)
])),
update_or_create_db_entity(
config_entity,
DbEntity(key=Key.CENSUS_BLOCK,
feature_class_configuration=FeatureClassConfiguration(
abstract_class=CensusBlock),
feature_behavior=FeatureBehavior(
behavior=get_behavior('reference'),
intersection=GeographicIntersection.
polygon_to_centroid),
_categories=[
Category(
key=DbEntityCategoryKey.KEY_CLASSIFICATION,
value=DbEntityCategoryKey.REFERENCE)
])),
update_or_create_db_entity(
config_entity,
DbEntity(key=Key.LIGHT_RAIL,
feature_class_configuration=FeatureClassConfiguration(
abstract_class=SacogLightRailFeature),
feature_behavior=FeatureBehavior(
behavior=get_behavior('reference'),
intersection=GeographicIntersection.
polygon_to_polygon),
_categories=[
Category(
key=DbEntityCategoryKey.KEY_CLASSIFICATION,
value=DbEntityCategoryKey.REFERENCE)
])),
update_or_create_db_entity(
config_entity,
DbEntity(key=Key.LIGHT_RAIL_STOPS,
feature_class_configuration=FeatureClassConfiguration(
abstract_class=SacogLightRailStopsFeature),
feature_behavior=FeatureBehavior(
behavior=get_behavior('reference'),
intersection=GeographicIntersection.
polygon_to_polygon),
_categories=[
Category(
key=DbEntityCategoryKey.KEY_CLASSIFICATION,
value=DbEntityCategoryKey.REFERENCE)
])),
update_or_create_db_entity(
config_entity,
DbEntity(
key=Key.LIGHT_RAIL_STOPS_ONE_MILE,
feature_class_configuration=FeatureClassConfiguration(
abstract_class=SacogLightRailStopsOneMileFeature, ),
feature_behavior=FeatureBehavior(
behavior=get_behavior('reference'),
intersection=GeographicIntersection.polygon_to_polygon
),
_categories=[
Category(key=DbEntityCategoryKey.KEY_CLASSIFICATION,
value=DbEntityCategoryKey.REFERENCE)
])),
update_or_create_db_entity(
config_entity,
DbEntity(
key=Key.LIGHT_RAIL_STOPS_HALF_MILE,
feature_class_configuration=FeatureClassConfiguration(
abstract_class=SacogLightRailStopsHalfMileFeature),
feature_behavior=FeatureBehavior(
behavior=get_behavior('reference'),
intersection=GeographicIntersection.polygon_to_polygon
),
_categories=[
Category(key=DbEntityCategoryKey.KEY_CLASSIFICATION,
value=DbEntityCategoryKey.REFERENCE)
])),
update_or_create_db_entity(
config_entity,
DbEntity(
key=Key.LIGHT_RAIL_STOPS_QUARTER_MILE,
feature_class_configuration=FeatureClassConfiguration(
abstract_class=SacogLightRailStopsQuarterMileFeature),
feature_behavior=FeatureBehavior(
behavior=get_behavior('reference'),
intersection=GeographicIntersection.polygon_to_polygon
),
_categories=[
Category(key=DbEntityCategoryKey.KEY_CLASSIFICATION,
value=DbEntityCategoryKey.REFERENCE)
])),
update_or_create_db_entity(
config_entity,
DbEntity(
key=Key.VERNAL_POOL,
feature_class_configuration=FeatureClassConfiguration(
abstract_class=SacogVernalPoolFeature),
feature_behavior=FeatureBehavior(
behavior=get_behavior('environmental_constraint')),
_categories=[
Category(key=DbEntityCategoryKey.KEY_CLASSIFICATION,
value=DbEntityCategoryKey.REFERENCE)
])),
update_or_create_db_entity(
config_entity,
DbEntity(
key=Key.WETLAND,
feature_class_configuration=FeatureClassConfiguration(
abstract_class=SacogWetlandFeature),
feature_behavior=FeatureBehavior(
behavior=get_behavior('environmental_constraint')),
_categories=[
Category(key=DbEntityCategoryKey.KEY_CLASSIFICATION,
value=DbEntityCategoryKey.REFERENCE)
])),
update_or_create_db_entity(
config_entity,
DbEntity(
key=Key.STREAM,
feature_class_configuration=FeatureClassConfiguration(
abstract_class=SacogStreamFeature),
feature_behavior=FeatureBehavior(
behavior=get_behavior('environmental_constraint')),
_categories=[
Category(key=DbEntityCategoryKey.KEY_CLASSIFICATION,
value=DbEntityCategoryKey.REFERENCE)
])),
])
def layers(self, class_scope=None):
# Combine parent fixture layers with the layers matching the given ConfigEntity scope
return self.parent_fixture.layers() + FixtureList([
# LayerConfiguration(
# library_keys=[LayerLibraryKey.APPLICATION],
# name='Existing Land Use Parcels 2012',
# db_entity_key=ScagDmDbEntityKey.EXISTING_LAND_USE_PARCELS_2012,
# column_alias_lookup=dict(land_use_definition__id='land_use_definition_id'),
# built_form_set_key='scag_land_uses',
# layer_style=primary_base_layer_style(ScagDmLandUseDefinition, True)
# ),
LayerConfiguration(
library_keys=[LayerLibraryKey.APPLICATION],
name='Existing Land Use Parcels 2016',
db_entity_key=ScagDmDbEntityKey.EXISTING_LAND_USE_PARCELS_2016,
# visible=True,
column_alias_lookup=dict(
land_use_definition__id='land_use_definition_id'),
built_form_set_key='scag_land_uses',
layer_style=primary_base_layer_style(ScagDmLandUseDefinition,
True)),
LayerConfiguration(
library_keys=[LayerLibraryKey.APPLICATION],
db_entity_key=ScagDmDbEntityKey.GENERAL_PLAN_PARCELS,
visible=True,
column_alias_lookup=dict(
land_use_definition__id='land_use_definition_id'),
built_form_set_key='scag_land_uses',
layer_style=primary_base_layer_style(ScagDmLandUseDefinition)),
LayerConfiguration(
library_keys=[LayerLibraryKey.APPLICATION],
db_entity_key=ScagDmDbEntityKey.SPECIFIC_PLAN_PARCELS,
column_alias_lookup=dict(
land_use_definition__id='land_use_definition_id'),
built_form_set_key='scag_land_uses',
layer_style=primary_base_layer_style(ScagDmLandUseDefinition)),
LayerConfiguration(
library_keys=[LayerLibraryKey.APPLICATION],
db_entity_key=ScagDmDbEntityKey.ZONING_PARCELS,
column_alias_lookup=dict(
land_use_definition__id='land_use_definition_id'),
built_form_set_key='scag_land_uses',
layer_style=primary_base_layer_style(ScagDmLandUseDefinition)),
LayerConfiguration(
library_keys=[LayerLibraryKey.APPLICATION],
db_entity_key=ScagDmDbEntityKey.ENTITLEMENT_PARCELS_2016,
layer_style=dict(
geometry_type=GeometryTypeKey.POLYGON,
style_attributes=[
dict(attribute='is_modified',
opacity=0.5,
style_type=StyleTypeKey.CATEGORICAL,
style_value_contexts=[
StyleValueContext(value='true',
symbol='=',
style=Style(
polygon_fill='#FF530D',
line_color='#66a0b2',
line_width=1,
polygon_opacity=0.4)),
StyleValueContext(value='false',
symbol='=',
style=Style(
polygon_fill='#2AE824',
line_color='#66a0b2',
line_width=1,
polygon_opacity=0.4))
])
])),
LayerConfiguration(
library_keys=[LayerLibraryKey.APPLICATION],
db_entity_key=ScagDmDbEntityKey.SCENARIO_PLANNING_ZONES,
layer_style=dict(geometry_type=GeometryTypeKey.POLYGON,
style_attributes=[
dict(style_type=StyleTypeKey.SINGLE,
style_value_contexts=[
StyleValueContext(
value=None,
symbol=None,
style=Style(
line_color='#E60000',
line_width=3))
])
])),
LayerConfiguration(
library_keys=[LayerLibraryKey.APPLICATION],
db_entity_key=ScagDmDbEntityKey.REGION_SPHERE_OF_INFLUENCE,
layer_style=dict(geometry_type=GeometryTypeKey.POLYGON,
style_attributes=[
dict(style_type=StyleTypeKey.SINGLE,
style_value_contexts=[
StyleValueContext(
value=None,
symbol=None,
style=Style(
line_color='#FFCC00',
line_width=5,
line_opacity=0.8))
])
])),
LayerConfiguration(library_keys=[LayerLibraryKey.APPLICATION],
db_entity_key=ScagDmDbEntityKey.TIER2_TAZ,
layer_style=dict(
geometry_type=GeometryTypeKey.POLYGON,
style_attributes=[
dict(style_type=StyleTypeKey.SINGLE,
style_value_contexts=[
StyleValueContext(
value=None,
symbol=None,
style=Style(
line_color='#00CC99',
line_width=4))
])
])),
LayerConfiguration(
library_keys=[LayerLibraryKey.APPLICATION],
db_entity_key=ScagDmDbEntityKey.HABITAT_CONSERVATION_AREA,
layer_style=dict(geometry_type=GeometryTypeKey.POLYGON,
style_attributes=[
dict(opacity=0.5,
style_type=StyleTypeKey.SINGLE,
style_value_contexts=[
StyleValueContext(
value=None,
symbol=None,
style=Style(
polygon_fill='#009966',
line_color='#006644',
line_width=1,
polygon_opacity=0.4))
])
])),
LayerConfiguration(
library_keys=[LayerLibraryKey.APPLICATION],
db_entity_key=ScagDmDbEntityKey.ENDANGERED_SPECIES,
layer_style=dict(geometry_type=GeometryTypeKey.POLYGON,
style_attributes=[
dict(style_type=StyleTypeKey.SINGLE,
style_value_contexts=[
StyleValueContext(
value=None,
symbol=None,
style=Style(
line_color='#009929',
line_opacity=1,
line_width=3))
])
])),
LayerConfiguration(library_keys=[LayerLibraryKey.APPLICATION],
db_entity_key=ScagDmDbEntityKey.COUNTY_BOUNDARY,
layer_style=dict(
geometry_type=GeometryTypeKey.POLYGON,
style_attributes=[
dict(style_type=StyleTypeKey.SINGLE,
style_value_contexts=[
StyleValueContext(
value=None,
symbol=None,
style=Style(
line_color='#FFFFCC',
line_opacity=1,
line_width=6))
])
])),
LayerConfiguration(
library_keys=[LayerLibraryKey.APPLICATION],
name='2040 Transit Priority Areas',
db_entity_key=ScagDmDbEntityKey.TRANSIT_PRIORITY_AREAS,
layer_style=dict(geometry_type=GeometryTypeKey.POLYGON,
style_attributes=[
dict(style_type=StyleTypeKey.SINGLE,
style_value_contexts=[
StyleValueContext(
value=None,
symbol=None,
style=Style(
line_color='#CC00FF',
line_width=2))
])
])),
LayerConfiguration(
library_keys=[LayerLibraryKey.APPLICATION],
name='2040 Major Transit Stops',
db_entity_key=ScagDmDbEntityKey.MAJOR_TRANSIT_STOPS,
layer_style=dict(
geometry_type=GeometryTypeKey.POINT,
style_attributes=[
dict(style_type=StyleTypeKey.SINGLE,
style_value_contexts=[
StyleValueContext(
value=None,
symbol=None,
style=Style(marker_fill='#000080',
marker_width=10,
marker_line_color='white',
marker_line_width=1))
])
])),
LayerConfiguration(
library_keys=[LayerLibraryKey.APPLICATION],
name='2040 High Quality Transit Areas',
db_entity_key=ScagDmDbEntityKey.HIGH_QUALITY_TRANSIT_AREAS,
layer_style=dict(geometry_type=GeometryTypeKey.POLYGON,
style_attributes=[
dict(style_type=StyleTypeKey.SINGLE,
style_value_contexts=[
StyleValueContext(
value=None,
symbol=None,
style=Style(
polygon_fill='#CC00FF',
polygon_opacity=0.15,
line_color='#CC00FF',
line_width=4,
line_opacity=0.5))
])
])),
LayerConfiguration(
library_keys=[LayerLibraryKey.APPLICATION],
name='2040 High Quality Transit Corridors',
db_entity_key=ScagDmDbEntityKey.HIGH_QUALITY_TRANSIT_CORRIDORS,
layer_style=dict(geometry_type=GeometryTypeKey.LINESTRING,
style_attributes=[
dict(style_type=StyleTypeKey.SINGLE,
style_value_contexts=[
StyleValueContext(
value=None,
symbol=None,
style=Style(
line_color='#660066',
line_width=6))
])
])),
LayerConfiguration(library_keys=[LayerLibraryKey.APPLICATION],
db_entity_key=ScagDmDbEntityKey.CENSUS_TRACTS,
layer_style=dict(
geometry_type=GeometryTypeKey.POLYGON,
style_attributes=[
dict(style_type=StyleTypeKey.SINGLE,
style_value_contexts=[
StyleValueContext(
value=None,
symbol=None,
style=Style(
line_color='#990000',
line_opacity=0.8,
line_width=3))
])
])),
LayerConfiguration(library_keys=[LayerLibraryKey.APPLICATION],
db_entity_key=ScagDmDbEntityKey.SUB_REGION,
layer_style=dict(
geometry_type=GeometryTypeKey.POLYGON,
style_attributes=[
dict(style_type=StyleTypeKey.SINGLE,
style_value_contexts=[
StyleValueContext(
value=None,
symbol=None,
style=Style(
line_color='#FFCC00',
line_width=6,
line_opacity=0.8))
])
])),
LayerConfiguration(library_keys=[LayerLibraryKey.APPLICATION],
db_entity_key=ScagDmDbEntityKey.CITY_BOUNDARY,
visible=True,
layer_style=dict(
geometry_type=GeometryTypeKey.POLYGON,
style_attributes=[
dict(style_type=StyleTypeKey.SINGLE,
style_value_contexts=[
StyleValueContext(
value=None,
symbol=None,
style=Style(
line_color='#000000',
line_opacity=1,
line_width=3))
])
])),
LayerConfiguration(library_keys=[LayerLibraryKey.APPLICATION],
db_entity_key=ScagDmDbEntityKey.SEA_LEVEL_RISE,
layer_style=dict(
geometry_type=GeometryTypeKey.POLYGON,
style_attributes=[
dict(style_type=StyleTypeKey.SINGLE,
style_value_contexts=[
StyleValueContext(
value=None,
symbol=None,
style=Style(
polygon_fill='#00007f',
line_color='#808080',
polygon_opacity=0.1))
])
])),
# LayerConfiguration(
# library_keys=[LayerLibraryKey.APPLICATION],
# db_entity_key=ScagDmDbEntityKey.BIKE_LANE,
# layer_style=dict(
# geometry_type=GeometryTypeKey.LINESTRING,
# style_attributes=[
# dict(
# attribute='status',
# style_type=StyleTypeKey.CATEGORICAL,
# style_value_contexts=[
# StyleValueContext(value='Existing', symbol='=', style=Style(
# line_color='#00cc88',
# line_width=4
# )),
#
# StyleValueContext(value='Proposed', symbol='=', style=Style(
# line_color='#ff9a00',
# line_width=4
# ))
# ]
# )
# ]
# )
# ),
LayerConfiguration(
library_keys=[LayerLibraryKey.APPLICATION],
db_entity_key=ScagDmDbEntityKey.FLOOD_ZONES,
layer_style=dict(
geometry_type=GeometryTypeKey.POLYGON,
style_attributes=[
dict(attribute='scag_fld_zone',
style_type=StyleTypeKey.CATEGORICAL,
style_value_contexts=[
StyleValueContext(
value='100-year Flood Hazard Zone',
symbol='=',
style=Style(
polygon_fill='#A900E6',
line_color='#d3d3d3',
line_width=1,
line_opacity=0.8,
polygon_opacity=0.4,
)),
StyleValueContext(
value='500-year Flood Hazard Zone',
symbol='=',
style=Style(
polygon_fill='#73B2FF',
line_color='#d3d3d3',
line_width=1,
line_opacity=0.8,
polygon_opacity=0.4,
))
])
])),
LayerConfiguration(
library_keys=[LayerLibraryKey.APPLICATION],
db_entity_key=ScagDmDbEntityKey.CPAD_HOLDINGS,
layer_style=dict(
global_opacity=0.6,
geometry_type=GeometryTypeKey.POLYGON,
style_attributes=[
dict(
attribute='layer_scag',
style_type=StyleTypeKey.CATEGORICAL,
style_value_contexts=[
StyleValueContext(
value=
'California Department of Fish and Wildlife',
symbol='=',
style=Style(
line_color='#594',
line_width=1,
polygon_fill='#1A2E14',
)),
StyleValueContext(
value=
'California Department of Parks and Recreation',
symbol='=',
style=Style(
line_color='#594',
line_width=1,
polygon_fill='#00c5ff',
)),
StyleValueContext(value="City",
symbol='=',
style=Style(
line_color='#594',
line_width=1,
polygon_fill='#ff73df',
)),
StyleValueContext(value="County",
symbol='=',
style=Style(
line_color='#594',
line_width=1,
polygon_fill='#a900e6',
)),
StyleValueContext(
value="National Park Service",
symbol='=',
style=Style(
line_color='#594',
line_width=1,
polygon_fill='#c89445',
)),
StyleValueContext(
value="Non Governmental Organization",
symbol='=',
style=Style(
line_color='#594',
line_width=1,
polygon_fill='#a87000',
)),
StyleValueContext(value="Other Federal",
symbol='=',
style=Style(
line_color='#594',
line_width=1,
polygon_fill='#aaaa66',
)),
StyleValueContext(value="Other State",
symbol='=',
style=Style(
line_color='#594',
line_width=1,
polygon_fill='#6699cd',
)),
StyleValueContext(value="Private",
symbol='=',
style=Style(
line_color='#594',
line_width=1,
polygon_fill='#559944',
)),
StyleValueContext(value="Special District",
symbol='=',
style=Style(
line_color='#594',
line_width=1,
polygon_fill='#ffbee8',
)),
StyleValueContext(
value="US Bureau of Land Management",
symbol='=',
style=Style(
line_color='#594',
line_width=1,
polygon_fill='#ffd37f',
)),
StyleValueContext(
value="US Fish and Wildlife Service",
symbol='=',
style=Style(
line_color='#594',
line_width=1,
polygon_fill='#aaff00',
)),
StyleValueContext(value="US Forest Service",
symbol='=',
style=Style(
line_color='#594',
line_width=1,
polygon_fill='#7af5ca',
)),
StyleValueContext(value="US Military/Defense",
symbol='=',
style=Style(
line_color='#594',
line_width=1,
polygon_fill='#686868',
))
])
])),
LayerConfiguration(
library_keys=[LayerLibraryKey.APPLICATION],
db_entity_key=ScagDmDbEntityKey.FARMLAND,
layer_style=dict(
geometry_type=GeometryTypeKey.POLYGON,
global_opacity=0.6,
style_attributes=[
dict(attribute='scag_type',
style_type=StyleTypeKey.CATEGORICAL,
style_value_contexts=[
StyleValueContext(value='P',
symbol='=',
style=Style(
line_color='#594',
line_width=1,
polygon_fill='#8DB359',
polygon_opacity=0.4)),
StyleValueContext(value='S',
symbol='=',
style=Style(
line_color='#594',
line_width=1,
polygon_fill='#BED984',
polygon_opacity=0.4)),
StyleValueContext(value='U',
symbol='=',
style=Style(
line_color='#594',
line_width=1,
polygon_fill='#E2F7B0',
polygon_opacity=0.4)),
StyleValueContext(value='G',
symbol='=',
style=Style(
line_color='#594',
line_width=1,
polygon_fill='#E3DBC5',
polygon_opacity=0.4)),
StyleValueContext(value='L',
symbol='=',
style=Style(
line_color='#594',
line_width=1,
polygon_fill='#F9FCDE',
polygon_opacity=0.4)),
StyleValueContext(value='LP',
symbol='=',
style=Style(
line_color='#594',
line_width=1,
polygon_fill='#FCF6F2',
polygon_opacity=0.4)),
StyleValueContext(value='X',
symbol='=',
style=Style(
line_color='#594',
line_width=1,
polygon_fill='#EBECED',
polygon_opacity=0.4)),
StyleValueContext(value='CI',
symbol='=',
style=Style(
line_color='#594',
line_width=1,
polygon_fill='#B37B59',
polygon_opacity=0.4)),
StyleValueContext(value='nv',
symbol='=',
style=Style(
line_color='#594',
line_width=1,
polygon_fill='#DBC49A',
polygon_opacity=0.4)),
StyleValueContext(value='V',
symbol='=',
style=Style(
line_color='#594',
line_width=1,
polygon_fill='#D3D2D4',
polygon_opacity=0.4)),
StyleValueContext(value='R',
symbol='=',
style=Style(
line_color='#594',
line_width=1,
polygon_fill='#F2CED3',
polygon_opacity=0.4)),
StyleValueContext(value='sAC',
symbol='=',
style=Style(
line_color='#594',
line_width=1,
polygon_fill='#F5D489',
polygon_opacity=0.4)),
StyleValueContext(value='D',
symbol='=',
style=Style(
line_color='#594',
line_width=1,
polygon_fill='#F29DAA',
polygon_opacity=0.4)),
StyleValueContext(value='W',
symbol='=',
style=Style(
line_color='#594',
line_width=1,
polygon_fill='#96D0D6',
polygon_opacity=0.4)),
StyleValueContext(value='I',
symbol='=',
style=Style(
line_color='#594',
line_width=1,
polygon_fill='#ACC7A5',
polygon_opacity=0.4)),
StyleValueContext(value='N',
symbol='=',
style=Style(
line_color='#594',
line_width=1,
polygon_fill='#F0F0C2',
polygon_opacity=0.4)),
StyleValueContext(value='Z',
symbol='=',
style=Style(
line_color='#594',
line_width=1,
polygon_fill='#D4CFC7',
polygon_opacity=0.4)),
])
]))
])
def layer_libraries(self, class_scope=None):
return self.parent_fixture.layer_libraries(FixtureList(self.layers()))
def results(self):
"""
Used to update or create Results per ConfigEntity instance
Returns the result library(ies) scoped for the class of self.config_entity.
The Result will belong to the ResultLibrary specified by result_library_key
:return:
"""
return FixtureList(
# Basic Core result query that summarizes increments
self.parent_fixture.results() + [
ResultConfiguration(
result_type='bar_graph',
library_keys=[ResultLibraryKey.APPLICATION],
result_db_entity_key=ResultKey.BASE_EMPLOYMENT_BY_TYPE,
source_db_entity_key=DbEntityKey.BASE_CANVAS,
name='Base: Employment by Sector',
attributes=[
'retail', 'office', 'industrial', 'public', 'other'
],
db_column_lookup=dict(
retail='emp_ret',
office='emp_off',
industrial='emp_ind',
public='emp_pub',
other='emp_military',
),
labels=[
'Retail', 'Office', 'Industrial', 'Public', 'Other'
],
stackable=True,
is_stacked=False,
create_query=lambda result_config: self.
employment_breakdown_query(DbEntityKey.BASE_CANVAS),
sort_priority=ResultSort.BASE),
ResultConfiguration(
result_type='bar_graph',
library_keys=[ResultLibraryKey.APPLICATION],
result_db_entity_key=ResultKey.BASE_DWELLING_UNITS_BY_TYPE,
source_db_entity_key=DbEntityKey.BASE_CANVAS,
name='Base: Dwelling Units by Type',
attributes=['single_family', 'attached', 'multifamily'],
db_column_lookup=dict(single_family='du_detsf',
attached='du_attsf',
multifamily='du_mf'),
labels=['Single Family', 'Attached', 'Multifamily'],
stackable=True,
is_stacked=False,
create_query=self.simple_aggregate,
sort_priority=ResultSort.BASE),
ResultConfiguration(
library_keys=[ResultLibraryKey.APPLICATION],
result_type='bar_graph',
result_db_entity_key=ResultKey.INCREMENTS,
source_db_entity_key=DbEntityKey.INCREMENT,
name='Increments: All Metrics',
attributes=['population', 'dwelling_units', 'employment'],
db_column_lookup=dict(population='pop',
dwelling_units='du',
employment='emp'),
extent_lookup=dict(
population=dict(min=-25000, max=25000),
dwelling_units=dict(min=-2500, max=2500),
employment=dict(min=-2500, max=2500),
),
labels=['Population', 'Dwelling Units', 'Employment'],
stackable=False,
is_stacked=False,
create_query=self.simple_aggregate,
sort_priority=ResultSort.FUTURE),
# DB Entity Core result query that summarizes dwellings by type
ResultConfiguration(
library_keys=[ResultLibraryKey.APPLICATION],
result_type='bar_graph',
result_db_entity_key=ResultKey.
INCREMENTS_DWELLING_UNITS_BY_TYPE,
source_db_entity_key=DbEntityKey.INCREMENT,
name='Increments: Dwelling Units by Type',
attributes=[
'single_family_large_lot', 'single_family_small_lot',
'multifamily', 'attached_single_family'
],
db_column_lookup=dict(
single_family_large_lot='du_detsf_ll',
single_family_small_lot='du_detsf_sl',
multifamily='du_mf',
attached_single_family='du_attsf',
),
labels=[
'SF Large Lot', 'SF Small Lot', 'MF', 'Attached SF'
],
stackable=False,
is_stacked=False,
create_query=self.simple_aggregate,
sort_priority=ResultSort.FUTURE),
ResultConfiguration(
library_keys=[ResultLibraryKey.APPLICATION],
result_type='bar_graph',
result_db_entity_key=ResultKey.
END_STATE_DWELLING_UNITS_BY_TYPE,
source_db_entity_key=DbEntityKey.END_STATE,
name='End State: Dwelling Units by Type',
attributes=[
'single_family_large_lot', 'single_family_small_lot',
'multifamily', 'attached_single_family'
],
db_column_lookup=dict(
single_family_large_lot='du_detsf_ll',
single_family_small_lot='du_detsf_sl',
multifamily='du_mf',
attached_single_family='du_attsf',
),
labels=[
'SF Large Lot', 'SF Small Lot', 'MF', 'Attached SF'
],
stackable=True,
is_stacked=False,
show_attrs_as_percents=True,
create_query=self.simple_aggregate,
sort_priority=ResultSort.FUTURE),
ResultConfiguration(
library_keys=[ResultLibraryKey.APPLICATION],
result_type='bar_graph',
result_db_entity_key=ResultKey.
INCREMENTS_EMPLOYMENT_BY_TYPE,
source_db_entity_key=DbEntityKey.INCREMENT,
name='Increments: Employment by Sector',
attributes=[
'retail', 'office', 'industrial', 'public', 'other'
],
db_column_lookup=dict(
retail='emp_ret',
office='emp_off',
industrial='emp_ind',
public='emp_pub',
other='emp_military',
),
labels=[
'Retail', 'Office', 'Industrial', 'Public', 'Other'
],
stackable=False,
is_stacked=False,
create_query=lambda result_config: self.
employment_breakdown_query(DbEntityKey.INCREMENT),
sort_priority=ResultSort.FUTURE),
ResultConfiguration(
library_keys=[ResultLibraryKey.APPLICATION],
result_type='bar_graph',
result_db_entity_key=ResultKey.
END_STATE_EMPLOYMENT_BY_TYPE,
source_db_entity_key=DbEntityKey.END_STATE,
name='End State: Employment by Sector',
attributes=[
'retail', 'office', 'industrial', 'public', 'other'
],
db_column_lookup=dict(
retail='emp_ret',
office='emp_off',
industrial='emp_ind',
public='emp_pub',
other='emp_military',
),
labels=[
'Retail', 'Office', 'Industrial', 'Public', 'Other'
],
stackable=True,
is_stacked=False,
create_query=lambda result_config: self.
employment_breakdown_query(DbEntityKey.END_STATE),
sort_priority=ResultSort.FUTURE),
ResultConfiguration(
library_keys=[ResultLibraryKey.APPLICATION],
result_type='analytic_bars',
result_db_entity_key=ResultKey.INCREMENTS_BARS,
source_db_entity_key=DbEntityKey.END_STATE,
name='Results Increments',
attributes=['population', 'dwelling_units', 'employment'],
db_column_lookup=dict(population='pop',
dwelling_units='du',
employment='emp'),
extent_lookup=dict(population=dict(min=0, max=5000000),
dwelling_units=dict(min=0, max=1000000),
employment=dict(min=0, max=1000000)),
labels=['Population', 'Dwelling Units', 'Employment'],
stackable=False,
is_stacked=False,
create_query=self.simple_aggregate,
sort_priority=ResultSort.FUTURE),
ResultConfiguration(
library_keys=[ResultLibraryKey.FISCAL],
result_type='analytic_result',
result_db_entity_key=ResultKey.FISCAL,
source_db_entity_key=DbEntityKey.FISCAL,
name='Fiscal',
attributes=[
'capital_costs', 'operations_maintenance', 'revenue'
],
db_column_lookup=dict(
capital_costs='residential_capital_costs',
operations_maintenance=
'residential_operations_maintenance_costs',
revenue='residential_revenue'),
labels=[
'capital_costs', 'operations_maintenance', 'revenue'
],
stackable=False,
is_stacked=False,
create_query=self.simple_aggregate,
sort_priority=ResultSort.FUTURE),
ResultConfiguration(
result_type='analytic_result',
library_keys=[ResultLibraryKey.VMT],
result_db_entity_key=ResultKey.VMT,
source_db_entity_key=DbEntityKey.VMT,
name='VMT',
attributes=[
'annual_vmt', 'daily_vmt', 'daily_vmt_per_hh',
'annual_vmt_per_capita'
],
db_column_lookup=dict(
annual_vmt='vmt_annual_w_trucks',
daily_vmt='vmt_daily_w_trucks',
daily_vmt_per_hh='vmt_daily_per_hh',
annual_vmt_per_capita='vmt_annual_per_capita'),
labels=[
'Annual VMT', 'Daily VMT', 'Daily VMT Per HH',
'Annual VMT Per Capita'
],
stackable=False,
is_stacked=False,
create_query=lambda result_config:
'SELECT SUM(vmt_annual_w_trucks) as annual_vmt__sum, SUM(vmt_daily_w_trucks) as daily_vmt__sum, Case when SUM(hh) > 0 then SUM(vmt_daily_w_trucks) / SUM(hh) else 0 end as daily_vmt_per_hh__sum, Case when SUM(hh) > 0 then SUM(vmt_daily_w_trucks) * 350 / SUM(hh) else 0 end as annual_vmt_per_hh__sum, Case when SUM(pop) > 0 then SUM(vmt_daily_w_trucks) * 350 / SUM(pop) else 0 end as annual_vmt_per_capita__sum, Case when SUM(pop) > 0 then SUM(vmt_daily_w_trucks) / SUM(pop) else 0 end as daily_vmt_per_capita__sum, Case when SUM(emp) > 0 then SUM(vmt_daily_w_trucks) / SUM(emp) else 0 end as daily_vmt_per_emp__sum, Case when SUM(emp) > 0 then SUM(vmt_daily_w_trucks) * 350 / SUM(emp) else 0 end as annual_vmt_per_emp__sum FROM %({0})s'
.format(DbEntityKey.VMT),
sort_priority=ResultSort.FUTURE),
ResultConfiguration(
result_type='analytic_result',
library_keys=[ResultLibraryKey.ENERGY],
result_db_entity_key=ResultKey.ENERGY,
source_db_entity_key=DbEntityKey.ENERGY,
name='Energy',
attributes=[
'total_gas_use', 'total_electricity_use',
'residential_gas_use', 'residential_electricity_use',
'commercial_gas_use', 'commercial_electricity_use'
],
db_column_lookup=dict(
total_gas_use='total_gas_use',
total_electricity_use='total_electricity_use',
residential_gas_use='residential_gas_use',
residential_electricity_use=
'residential_electricity_use',
commercial_gas_use='commercial_gas_use',
commercial_electricity_use='commercial_electricity_use'
),
labels=[
'total_gas_use', 'total_electricity_use',
'residential_gas_use', 'residential_electricity_use',
'commercial_gas_use', 'commercial_electricity_use'
],
stackable=False,
is_stacked=False,
create_query=lambda result_config:
'SELECT SUM(total_gas_use) as total_gas_use__sum, SUM(total_electricity_use) as total_electricity_use__sum, SUM(residential_gas_use) as residential_gas_use__sum, SUM(residential_electricity_use) as residential_electricity_use__sum, SUM(commercial_gas_use) as commercial_gas_use__sum, SUM(commercial_electricity_use) as commercial_electricity_use__sum, Case when SUM(hh) > 0 then SUM(residential_gas_use) / SUM(hh) else 0 end as residenital_per_hh_gas_use__sum, Case when SUM(hh) > 0 then SUM(residential_electricity_use) / SUM(hh) else 0 end as residenital_per_hh_electricity_use__sum, Case when SUM(total_commercial_sqft) > 0 then SUM(commercial_gas_use) / SUM(emp) else 0 end as commercial_per_emp_gas_use__sum, Case when SUM(total_commercial_sqft) > 0 then SUM(commercial_electricity_use) / SUM(emp) else 0 end as commercial_per_emp_electricity_use__sum FROM %({0})s'
.format(DbEntityKey.ENERGY),
sort_priority=ResultSort.FUTURE),
ResultConfiguration(
result_type='analytic_result',
library_keys=[ResultLibraryKey.WATER],
result_db_entity_key=ResultKey.WATER,
source_db_entity_key=DbEntityKey.WATER,
name='Water',
attributes=[
'total_water_use', 'residential_water_use',
'commercial_water_use', 'residential_indoor_water_use',
'residential_outdoor_water_use',
'commercial_indoor_water_use',
'commercial_outdoor_water_use'
],
db_column_lookup=dict(
total_water_use='total_water_use',
residential_water_use='residential_water_use',
commercial_water_use='commercial_water_use',
residential_indoor_water_use=
'residential_indoor_water_use',
residential_outdoor_water_use=
'residential_outdoor_water_use',
commercial_indoor_water_use=
'commercial_indoor_water_use',
commercial_outdoor_water_use=
'commercial_outdoor_water_use'),
labels=[
'total_water_use', 'residential_water_use',
'commercial_water_use', 'residential_indoor_water_use',
'residential_outdoor_water_use',
'commercial_indoor_water_use',
'commercial_outdoor_water_use'
],
stackable=False,
is_stacked=False,
create_query=self.simple_aggregate,
sort_priority=ResultSort.FUTURE),
# Aggregate result from the Analytic Bars
ResultConfiguration(
result_type='analytic_bars',
library_keys=[ResultLibraryKey.APPLICATION],
result_db_entity_key=ResultKey.Fab.ricate('base_bars'),
source_db_entity_key=DbEntityKey.BASE_CANVAS,
name='Base Results',
attributes=['employment', 'dwelling_units', 'population'],
db_column_lookup=dict(employment='emp',
dwelling_units='du',
population='pop'),
extent_lookup=dict(population=dict(min=0, max=5000000),
dwelling_units=dict(min=0, max=1000000),
employment=dict(min=0, max=1000000)),
labels=['Employees', 'Dwelling Units', 'Population'],
stackable=False,
create_query=self.simple_aggregate,
sort_priority=ResultSort.BASE),
#result configurartions for water analysis
ResultConfiguration(
result_type='bar_graph',
library_keys=[ResultLibraryKey.WATER],
result_db_entity_key=ResultKey.WATER_INDOOR_OUTDOOR,
source_db_entity_key=DbEntityKey.WATER,
name='Water Use (gal): Indoor and Outdoor ',
attributes=[
'residential_indoor_water_use',
'residential_outdoor_water_use',
'commercial_indoor_water_use',
'commercial_outdoor_water_use'
],
db_column_lookup=dict(residential_indoor_water_use=
'residential_indoor_water_use',
residential_outdoor_water_use=
'residential_outdoor_water_use',
commercial_indoor_water_use=
'commercial_indoor_water_use',
commercial_outdoor_water_use=
'commercial_outdoor_water_use'),
labels=[
'Res-Indoor', 'Res-Outdoor', 'Com-Indoor',
'Com-Outdoor'
],
stackable=False,
is_stacked=False,
create_query=self.simple_aggregate,
sort_priority=ResultSort.BASE),
ResultConfiguration(
result_type='bar_graph',
library_keys=[ResultLibraryKey.WATER],
result_db_entity_key=ResultKey.WATER_TOTAL,
source_db_entity_key=DbEntityKey.WATER,
name='Water Use (gal): Residential and Commercial',
attributes=[
'residential_water_use', 'commercial_water_use'
],
db_column_lookup=dict(
residential_water_use='residential_water_use',
commercial_water_use='commercial_water_use'),
labels=['Residential', 'Commercial'],
stackable=False,
is_stacked=False,
create_query=self.simple_aggregate,
sort_priority=ResultSort.BASE),
ResultConfiguration(
result_type='bar_graph',
library_keys=[ResultLibraryKey.WATER],
result_db_entity_key=ResultKey.WATER_COSTS_TOTAL,
source_db_entity_key=DbEntityKey.WATER,
name='Water Costs ($-2014): Residential and Commercial',
attributes=[
'residential_water_use', 'commercial_water_use'
],
db_column_lookup=dict(
residential_water_use='residential_water_use',
commercial_water_use='commercial_water_use'),
labels=['Residential', 'Commercial'],
stackable=False,
is_stacked=False,
create_query=lambda result_config:
'SELECT SUM(residential_water_use) / 325851.431889 * 1349.0 as residential_water_use__sum, SUM(commercial_water_use) / 325851.431889 * 1349.0 as commercial_water_use__sum from %({0})s'
.format(DbEntityKey.WATER),
sort_priority=ResultSort.BASE),
ResultConfiguration(
result_type='bar_graph',
library_keys=[ResultLibraryKey.ENERGY],
result_db_entity_key=ResultKey.ENERGY_TOTAL,
source_db_entity_key=DbEntityKey.ENERGY,
name='Energy Use (MMBTU): Residential and Commercial',
attributes=[
'residential_energy_use', 'commercial_energy_use'
],
db_column_lookup=dict(
residential_energy_use='residential_energy_use',
commercial_energy_use='commercial_energy_use'),
labels=['Residential', 'Commercial'],
stackable=False,
is_stacked=False,
create_query=lambda result_config:
'SELECT SUM(residential_electricity_use) * 0.0034095106405145 + sum(residential_gas_use) * 0.1 as residential_energy_use__sum, SUM(commercial_electricity_use) * 0.0034095106405145 + sum(commercial_gas_use) * 0.1 as commercial_energy_use__sum from %({0})s'
.format(DbEntityKey.ENERGY),
sort_priority=ResultSort.BASE),
ResultConfiguration(
result_type='bar_graph',
library_keys=[ResultLibraryKey.ENERGY],
result_db_entity_key=ResultKey.ENERGY_RES_USE,
source_db_entity_key=DbEntityKey.ENERGY,
name='Energy Use (MMBTU): Residential by Type',
attributes=[
'du_detsf_ll_energy_use', 'du_detsf_sl_energy_use',
'du_attsf_energy_use', 'du_mf_energy_use'
],
db_column_lookup=dict(
du_detsf_ll_energy_use='du_detsf_ll_energy_use',
du_detsf_sl_energy_use='du_detsf_sl_energy_use',
du_attsf_energy_use='du_attsf_energy_use',
du_mf_energy_use='du_mf_energy_use'),
labels=[
'SF Large Lot', 'SF Small Lot', 'Attached SF',
'Multifamily'
],
stackable=False,
is_stacked=False,
create_query=lambda result_config:
'SELECT SUM(du_detsf_ll_electricity_use) * 0.0034095106405145 + sum(du_detsf_ll_gas_use) * 0.1 as du_detsf_ll_energy_use__sum, SUM(du_detsf_sl_electricity_use) * 0.0034095106405145 + sum(du_detsf_sl_gas_use) * 0.1 as du_detsf_sl_energy_use__sum, SUM(du_attsf_electricity_use) * 0.0034095106405145 + sum(du_attsf_gas_use) * 0.1 as du_attsf_energy_use__sum, SUM(du_mf_electricity_use) * 0.0034095106405145 + sum(du_mf_gas_use) * 0.1 as du_mf_energy_use__sum from %({0})s'
.format(DbEntityKey.ENERGY),
sort_priority=ResultSort.BASE),
ResultConfiguration(
result_type='bar_graph',
library_keys=[ResultLibraryKey.ENERGY],
result_db_entity_key=ResultKey.ENERGY_COM_USE,
source_db_entity_key=DbEntityKey.ENERGY,
name='Energy Use (MMBTU): Commercial by Type',
attributes=[
'retail_energy_use', 'office_energy_use',
'public_energy_use', 'industrial_energy_use'
],
db_column_lookup=dict(
retail_energy_use='retail_energy_use',
office_energy_use='office_energy_use',
public_energy_use='public_energy_use',
industrial_energy_use='industrial_energy_use'),
labels=['Retail', 'Office', 'Public', '*Industrial'],
stackable=False,
is_stacked=False,
create_query=lambda result_config:
'SELECT SUM(retail_services_electricity_use + restaurant_electricity_use + accommodation_electricity_use + other_services_electricity_use) * 0.0034095106405145 + sum(retail_services_gas_use + restaurant_gas_use + accommodation_gas_use + other_services_gas_use) * 0.1 as retail_energy_use__sum, SUM(office_services_electricity_use + medical_services_electricity_use) * 0.0034095106405145 + sum(office_services_gas_use + medical_services_gas_use) * 0.1 as office_energy_use__sum, SUM(public_admin_electricity_use + education_electricity_use) * 0.0034095106405145 + sum(public_admin_gas_use + education_gas_use) * 0.1 as public_energy_use__sum, SUM(wholesale_electricity_use + transport_warehousing_electricity_use) * 0.0034095106405145 + sum(wholesale_gas_use + transport_warehousing_gas_use) * 0.1 as industrial_energy_use__sum from %({0})s'
.format(DbEntityKey.ENERGY),
sort_priority=ResultSort.BASE),
ResultConfiguration(
result_type='bar_graph',
library_keys=[ResultLibraryKey.ENERGY],
result_db_entity_key=ResultKey.ENERGY_COSTS_TOTAL,
source_db_entity_key=DbEntityKey.ENERGY,
name='Energy Costs ($-2014): Residential and Commercial',
attributes=[
'residential_energy_cost', 'commercial_energy_cost'
],
db_column_lookup=dict(
residential_energy_cost='residential_energy_cost',
commercial_energy_cost='commercial_energy_cost'),
labels=['Residential', 'Commercial'],
stackable=False,
is_stacked=False,
create_query=lambda result_config:
'SELECT SUM(residential_electricity_use) * 0.1802 + sum(residential_gas_use) * 1.203 as residential_energy_cost__sum, SUM(commercial_electricity_use) * 0.1822 + sum(commercial_gas_use) * 0.854 as commercial_energy_cost__sum from %({0})s'
.format(DbEntityKey.ENERGY),
sort_priority=ResultSort.BASE),
ResultConfiguration(
result_type='bar_graph',
library_keys=[ResultLibraryKey.ENERGY],
result_db_entity_key=ResultKey.ENERGY_EMISSIONS_TOTAL,
source_db_entity_key=DbEntityKey.ENERGY,
name='Energy Emissions (CO2e): Residential and Commercial',
attributes=[
'residential_energy_emissions',
'commercial_energy_emissions'
],
db_column_lookup=dict(residential_energy_emissions=
'residential_energy_emissions',
commercial_energy_emissions=
'commercial_energy_emissions'),
labels=['Residential', 'Commercial'],
stackable=False,
is_stacked=False,
create_query=lambda result_config:
'SELECT SUM(residential_electricity_use) * 0.69 + sum(residential_gas_use) * 11.7 as residential_energy_emissions__sum, SUM(commercial_electricity_use) * 0.69 + sum(commercial_gas_use) * 11.7 as commercial_energy_emissions__sum from %({0})s'
.format(DbEntityKey.ENERGY),
sort_priority=ResultSort.BASE),
ResultConfiguration(
result_type='bar_graph',
library_keys=[ResultLibraryKey.FISCAL],
result_db_entity_key=ResultKey.FISCAL_CHART,
source_db_entity_key=DbEntityKey.FISCAL,
name='Fiscal ($-2012): Residential Costs/Revenue',
attributes=[
'residential_capital_costs',
'residential_operations_maintenance_costs',
'residential_revenue'
],
db_column_lookup=dict(
residential_capital_costs='residential_capital_costs',
residential_operations_maintenance_costs=
'residential_operations_maintenance_costs',
residential_revenue='residential_revenue'),
labels=['Capital Costs', 'O&M Costs', 'Revenue'],
stackable=False,
is_stacked=False,
create_query=self.simple_aggregate,
sort_priority=ResultSort.BASE),
ResultConfiguration(
result_type='bar_graph',
library_keys=[ResultLibraryKey.VMT],
result_db_entity_key=ResultKey.VMT_PER_CAPITA,
source_db_entity_key=DbEntityKey.VMT,
name='Annual VMT: Per Capita / Per Employee',
attributes=['vmt_annual_per_capita', 'vmt_annual_per_emp'],
db_column_lookup=dict(
vmt_annual_per_capita='vmt_annual_per_capita',
vmt_annual_per_emp='vmt_annual_per_emp'),
labels=['Per Capita', 'Per Employee'],
stackable=False,
is_stacked=False,
create_query=lambda result_config:
'SELECT Case when SUM(pop) > 0 then SUM(vmt_annual_w_trucks) / sum(pop) else 0 end as vmt_annual_per_capita__sum, Case when SUM(emp) > 0 then SUM(vmt_annual_w_trucks) / sum(emp) else 0 end as vmt_annual_per_emp__sum from %({0})s'
.format(DbEntityKey.VMT),
sort_priority=ResultSort.BASE),
ResultConfiguration(
result_type='bar_graph',
library_keys=[ResultLibraryKey.VMT],
result_db_entity_key=ResultKey.VMT_FUEL,
source_db_entity_key=DbEntityKey.VMT,
name='Annual Fuel Consumption (gal)',
attributes=['annual_gallons'
],
db_column_lookup=dict(annual_gallons='annual_gallons'),
labels=['Gallons'],
stackable=False,
is_stacked=False,
create_query=lambda result_config:
'SELECT SUM(vmt_annual_w_trucks) / 19.4 as annual_gallons__sum from %({0})s'
.format(DbEntityKey.VMT),
sort_priority=ResultSort.BASE),
ResultConfiguration(
result_type='bar_graph',
library_keys=[ResultLibraryKey.VMT],
result_db_entity_key=ResultKey.VMT_COSTS,
source_db_entity_key=DbEntityKey.VMT,
name='Annual Vehicle Costs ($-2014)',
attributes=['cost_per_mile'],
db_column_lookup=dict(cost_per_mile='cost_per_mile'),
labels=['Vehicle Costs'],
stackable=False,
is_stacked=False,
create_query=lambda result_config:
'SELECT SUM(vmt_annual_w_trucks) * 0.35 as cost_per_mile__sum from %({0})s'
.format(DbEntityKey.VMT),
sort_priority=ResultSort.BASE),
ResultConfiguration(
result_type='bar_graph',
library_keys=[ResultLibraryKey.VMT],
result_db_entity_key=ResultKey.VMT_EMISSIONS,
source_db_entity_key=DbEntityKey.VMT,
name='Annual Vehicle Emissions (lbs CO2e)',
attributes=['vehicle_emissions'],
db_column_lookup=dict(
vehicle_emissions='vehicle_emissions'),
labels=['Emissions'],
stackable=False,
is_stacked=False,
create_query=lambda result_config:
'SELECT SUM(vmt_annual_w_trucks) * 0.9061 as vehicle_emissions__sum from %({0})s'
.format(DbEntityKey.VMT),
sort_priority=ResultSort.BASE),
ResultConfiguration(
result_type='bar_graph',
library_keys=[ResultLibraryKey.PUBLIC_HEALTH],
result_db_entity_key=ResultKey.PH_WALKING_MINUTES,
source_db_entity_key=DbEntityKey.PH_BLOCK_GROUP_OUTCOMES,
name='Daily Walking Minutes - Per Capita',
attributes=[
'seniors_all_walk_minutes', 'adult_all_walk_minutes',
'teens_all_walk_minutes', 'children_all_walk_minutes'
],
db_column_lookup=dict(
seniors_all_walk_minutes='seniors_all_walk_minutes',
adult_all_walk_minutes='adult_all_walk_minutes',
teens_all_walk_minutes='teens_all_walk_minutes',
children_all_walk_minutes='children_all_walk_minutes'),
labels=['Seniors', 'Adults', 'Teens', 'Children'],
stackable=False,
is_stacked=False,
create_query=lambda result_config: '''SELECT
CASE WHEN SUM(seniors_all_walk_minutes) > 0 then SUM(pop_senior * seniors_all_walk_minutes) / sum(pop_senior)
else 0 end as seniors_all_walk_minutes__sum,
CASE WHEN SUM(adult_all_walk_minutes) > 0 then SUM(pop_adult * adult_all_walk_minutes) / sum(pop_adult)
else 0 end as adult_all_walk_minutes__sum,
CASE WHEN SUM(teens_all_walk_minutes) > 0 then SUM(pop_teen * teens_all_walk_minutes) / sum(pop_teen)
else 0 end as teens_all_walk_minutes__sum,
CASE WHEN SUM(children_all_walk_minutes) > 0 then SUM(pop_children * children_all_walk_minutes) / sum(pop_children)
else 0 end as children_all_walk_minutes__sum from %({0})s'''
.format(DbEntityKey.PH_BLOCK_GROUP_OUTCOMES),
sort_priority=ResultSort.BASE),
ResultConfiguration(
result_type='bar_graph',
library_keys=[ResultLibraryKey.PUBLIC_HEALTH],
result_db_entity_key=ResultKey.PH_AUTO_MINUTES,
source_db_entity_key=DbEntityKey.PH_BLOCK_GROUP_OUTCOMES,
name='Daily Auto Minutes - Per Capita',
attributes=[
'seniors_all_auto_minutes', 'adult_all_auto_minutes',
'teens_all_auto_minutes', 'children_all_auto_minutes'
],
db_column_lookup=dict(
seniors_all_auto_minutes='seniors_all_auto_minutes',
adult_all_auto_minutes='adult_all_auto_minutes',
teens_all_auto_minutes='teens_all_auto_minutes',
children_all_auto_minutes='children_all_auto_minutes'),
labels=['Seniors', 'Adults', 'Teens', 'Children'],
stackable=False,
is_stacked=False,
create_query=lambda result_config: '''SELECT
CASE WHEN SUM(seniors_all_auto_minutes) > 0 then SUM(pop_senior * seniors_all_auto_minutes) / sum(pop_senior)
else 0 end as seniors_all_auto_minutes__sum,
CASE WHEN SUM(adult_all_auto_minutes) > 0 then SUM(pop_adult * adult_all_auto_minutes) / sum(pop_adult)
else 0 end as adult_all_auto_minutes__sum,
CASE WHEN SUM(teens_all_auto_minutes) > 0 then SUM(pop_teen * teens_all_auto_minutes) / sum(pop_teen)
else 0 end as teens_all_auto_minutes__sum,
CASE WHEN SUM(children_all_auto_minutes) > 0 then SUM(pop_children * children_all_auto_minutes) / sum(pop_children)
else 0 end as children_all_auto_minutes__sum from %({0})s'''
.format(DbEntityKey.PH_BLOCK_GROUP_OUTCOMES),
sort_priority=ResultSort.BASE),
ResultConfiguration(
result_type='bar_graph',
library_keys=[ResultLibraryKey.PUBLIC_HEALTH],
result_db_entity_key=ResultKey.PH_REC_PA_MINUTES,
source_db_entity_key=DbEntityKey.PH_BLOCK_GROUP_OUTCOMES,
name='Daily Physical Activity Minutes - Per Capita',
attributes=[
'seniors_all_rec_pa_minutes',
'adult_all_rec_pa_minutes', 'teens_all_rec_pa_minutes',
'children_all_rec_pa_minutes'
],
db_column_lookup=dict(
seniors_all_rec_pa_minutes='seniors_all_rec_pa_minutes',
adult_all_rec_pa_minutes='adult_all_rec_pa_minutes',
teens_all_rec_pa_minutes='teens_all_rec_pa_minutes',
children_all_rec_pa_minutes=
'children_all_rec_pa_minutes'),
labels=['Seniors', 'Adults', 'Teens', 'Children'],
stackable=False,
is_stacked=False,
create_query=lambda result_config: '''SELECT
CASE WHEN SUM(seniors_all_rec_pa_minutes) > 0 then SUM(pop_senior * seniors_all_rec_pa_minutes) / sum(pop_senior)
else 0 end as seniors_all_rec_pa_minutes__sum,
CASE WHEN SUM(adult_all_rec_pa_minutes) > 0 then SUM(pop_adult * adult_all_rec_pa_minutes) / sum(pop_adult)
else 0 end as adult_all_rec_pa_minutes__sum,
CASE WHEN SUM(teens_all_rec_pa_minutes) > 0 then SUM(pop_teen * teens_all_rec_pa_minutes) / sum(pop_teen)
else 0 end as teens_all_rec_pa_minutes__sum,
CASE WHEN SUM(children_all_rec_pa_minutes) > 0 then SUM(pop_children * children_all_rec_pa_minutes) / sum(pop_children)
else 0 end as children_all_rec_pa_minutes__sum from %({0})s'''
.format(DbEntityKey.PH_BLOCK_GROUP_OUTCOMES),
sort_priority=ResultSort.BASE),
ResultConfiguration(
result_type='summary_table',
library_keys=[ResultLibraryKey.PUBLIC_HEALTH],
result_db_entity_key=ResultKey.PH_OUTCOMES_TABLE,
source_db_entity_key=DbEntityKey.PH_OUTCOMES_SUMMARY,
name='Public Health Outcomes Summary',
attributes=['outcome', 'result'],
db_column_lookup=dict(outcome='outcome', result='result'),
labels=['outcome', 'result'],
stackable=False,
is_stacked=False,
create_query=lambda result_config:
'''SELECT outcome, result from %({0})s'''.format(
DbEntityKey.PH_OUTCOMES_SUMMARY),
sort_priority=ResultSort.BASE),
ResultConfiguration(
result_type='bar_graph',
library_keys=[ResultLibraryKey.AGRICULTURE_ANALYSIS],
result_db_entity_key=ResultKey.AGRICULTURE_ROI,
source_db_entity_key=DbEntityKey.BASE_AGRICULTURE_CANVAS,
name='Agriculture(RUCS): Cost/Gain Comparison',
attributes=['production_cost', 'market_value'],
db_column_lookup=dict(production_cost='production_cost',
market_value='market_value'),
labels=['Total Cost', 'Total Value'],
stackable=False,
is_stacked=False,
create_query=self.simple_aggregate,
sort_priority=ResultSort.BASE),
ResultConfiguration(
result_type='bar_graph',
library_keys=[ResultLibraryKey.AGRICULTURE_ANALYSIS],
result_db_entity_key=ResultKey.AGRICULTURE_ROI,
source_db_entity_key=DbEntityKey.FUTURE_AGRICULTURE_CANVAS,
name='Agriculture(RUCS): Cost/Gain Comparison',
attributes=['production_cost', 'market_value'],
db_column_lookup=dict(production_cost='production_cost',
market_value='market_value'),
labels=['Total Cost', 'Total Value'],
stackable=False,
is_stacked=False,
create_query=self.simple_aggregate,
sort_priority=ResultSort.BASE),
ResultConfiguration(
result_type='analytic_result',
library_keys=[ResultLibraryKey.AGRICULTURE_ANALYSIS],
result_db_entity_key=ResultKey.AGRICULTURE,
source_db_entity_key=DbEntityKey.BASE_AGRICULTURE_CANVAS,
name='Agriculture',
attributes=[
'crop_yield', 'water_consumption', 'labor_force',
'truck_trips', 'production_cost', 'market_value'
],
db_column_lookup=dict(
crop_yield='crop_yield',
water_consumption='water_consumption',
labor_force='labor_force',
truck_trips='truck_trips',
production_cost='production_cost',
market_value='market_value'),
labels=[
'crop_yield', 'water_consumption', 'labor_force',
'truck_trips', 'production_cost', 'market_value'
],
stackable=False,
is_stacked=False,
create_query=self.simple_aggregate,
sort_priority=ResultSort.BASE),
ResultConfiguration(
result_type='analytic_result',
library_keys=[ResultLibraryKey.AGRICULTURE_ANALYSIS],
result_db_entity_key=ResultKey.AGRICULTURE,
source_db_entity_key=DbEntityKey.FUTURE_AGRICULTURE_CANVAS,
name='Agriculture',
attributes=[
'crop_yield', 'water_consumption', 'labor_force',
'truck_trips', 'production_cost', 'market_value'
],
db_column_lookup=dict(
crop_yield='crop_yield',
water_consumption='water_consumption',
labor_force='labor_force',
truck_trips='truck_trips',
production_cost='production_cost',
market_value='market_value'),
labels=[
'crop_yield', 'water_consumption', 'labor_force',
'truck_trips', 'production_cost', 'market_value'
],
stackable=False,
is_stacked=False,
create_query=self.simple_aggregate,
sort_priority=ResultSort.FUTURE)
])
def projects(self,
region=None,
region_keys=None,
project_keys=None,
class_scope=None):
# All SCAG jurisdictions
imperial = [
'Brawley', 'Calexico', 'Calipatria', 'El Centro', 'Holtville',
'Imperial', 'Unincorporated: Imperial', 'Westmorland'
]
los_angeles = [
'Agoura Hills', 'Alhambra', 'Arcadia', 'Artesia', 'Avalon',
'Azusa', 'Baldwin Park', 'Bell', 'Bell Gardens', 'Bellflower',
'Beverly Hills', 'Bradbury', 'Burbank', 'Calabasas', 'Carson',
'Cerritos', 'Claremont', 'Commerce', 'Compton', 'Covina', 'Cudahy',
'Culver City', 'Diamond Bar', 'Downey', 'Duarte', 'El Monte',
'El Segundo', 'Gardena', 'Glendale', 'Glendora',
'Hawaiian Gardens', 'Hawthorne', 'Hermosa Beach', 'Hidden Hills',
'Huntington Park', 'Industry', 'Inglewood', 'Irwindale',
'La Canada Flintridge', 'La Habra Heights', 'La Mirada',
'La Puente', 'La Verne', 'Lakewood', 'Lancaster', 'Lawndale',
'Lomita', 'Long Beach', 'Los Angeles', 'Lynwood', 'Malibu',
'Manhattan Beach', 'Maywood', 'Monrovia', 'Montebello',
'Monterey Park', 'Norwalk', 'Palmdale', 'Palos Verdes Estates',
'Paramount', 'Pasadena', 'Pico Rivera', 'Pomona',
'Rancho Palos Verdes', 'Redondo Beach', 'Rolling Hills',
'Rolling Hills Estates', 'Rosemead', 'San Dimas', 'San Fernando',
'San Gabriel', 'San Marino', 'Santa Clarita', 'Santa Fe Springs',
'Santa Monica', 'Sierra Madre', 'Signal Hill', 'South El Monte',
'South Gate', 'South Pasadena', 'Temple City', 'Torrance',
'Unincorporated: Los Angeles', 'Vernon', 'Walnut', 'West Covina',
'West Hollywood', 'Westlake Village', 'Whittier'
]
orange = [
'Aliso Viejo', 'Anaheim', 'Brea', 'Buena Park', 'Costa Mesa',
'Cypress', 'Dana Point', 'Fountain Valley', 'Fullerton',
'Garden Grove', 'Huntington Beach', 'Irvine', 'La Habra',
'La Palma', 'Laguna Beach', 'Laguna Hills', 'Laguna Niguel',
'Laguna Woods', 'Lake Forest', 'Los Alamitos', 'Mission Viejo',
'Newport Beach', 'Orange', 'Placentia', 'Rancho Santa Margarita',
'San Clemente', 'San Juan Capistrano', 'Santa Ana', 'Seal Beach',
'Stanton', 'Tustin', 'Unincorporated: Orange', 'Villa Park',
'Westminster', 'Yorba Linda'
]
riverside = [
'Banning', 'Beaumont', 'Blythe', 'Calimesa', 'Canyon Lake',
'Cathedral City', 'Coachella', 'Corona', 'Desert Hot Springs',
'Eastvale', 'Hemet', 'Indian Wells', 'Indio', 'Jurupa Valley',
'La Quinta', 'Lake Elsinore', 'Menifee', 'Moreno Valley',
'Murrieta', 'Norco', 'Palm Desert', 'Palm Springs', 'Perris',
'Rancho Mirage', 'Riverside', 'San Jacinto', 'Temecula',
'Unincorporated: Riverside', 'Wildomar'
]
san_bernardino = [
'Adelanto', 'Apple Valley', 'Barstow', 'Big Bear Lake', 'Chino',
'Chino Hills', 'Colton', 'Fontana', 'Grand Terrace', 'Hesperia',
'Highland', 'Loma Linda', 'Montclair', 'Needles', 'Ontario',
'Rancho Cucamonga', 'Redlands', 'Rialto', 'San Bernardino',
'Twentynine Palms', 'Unincorporated: San Bernardino', 'Upland',
'Victorville', 'Yucaipa', 'Yucca Valley'
]
ventura = [
'Camarillo', 'Fillmore', 'Moorpark', 'Ojai', 'Oxnard',
'Port Hueneme', 'San Buenaventura', 'Santa Paula', 'Simi Valley',
'Thousand Oaks', 'Unincorporated: Ventura'
]
#jurisdictions = imperial + los_angeles + orange + riverside + san_bernardino + ventura
#jurisdictions = ['City_%02d' % x for x in xrange(32)]
jurisdictions = imperial
# Create only a small subset of jurisdictions for the dev environments
if settings.USE_SAMPLE_DATA_SETS:
jurisdictions = ["Anaheim", 'Irvine']
configurations = map(
lambda jurisdiction_name: {
'key':
project_key(jurisdiction_name),
'import_key':
jurisdiction_name.lower().replace(' ', '_').replace(':', ''),
'name':
jurisdiction_name,
'description':
"City of %s" % jurisdiction_name,
'base_year':
2014,
'region_key':
'scag',
'media': [
MediumFixture(key=ConfigEntityMediumKey.Fab.ricate(
jurisdiction_name.lower().replace(' ', '_') + '_logo'),
name='%s Logo' % jurisdiction_name,
url='/static/client/{0}/logos/{1}_logo.png'.
format(
settings.CLIENT,
jurisdiction_name.lower().replace(
' ', '_')))
]
}, jurisdictions)
return FixtureList(configurations).matching_keys(
region_keys=region_keys,
key=project_keys).matching_scope(class_scope=class_scope)
def default_db_entities(self):
"""
Region specific db_entity_setups
:param default_dict:
:return:
"""
config_entity = self.config_entity
parent_region_fixture = self.parent_fixture
default_db_entities = parent_region_fixture.default_db_entities()
# The DbEntity keyspace. These keys have no prefix
Key = ScagDmDbEntityKey
# The Behavior keyspace
behavior_key = BehaviorKey.Fab.ricate
# Used to load Behaviors defined elsewhere
get_behavior = lambda key: Behavior.objects.get(key=behavior_key(key))
if isinstance(self.config_entity.parent_config_entity_subclassed,
GlobalConfig):
# Block the client-level region. We just want real regions
return []
return default_db_entities + FixtureList([
update_or_create_db_entity(
config_entity,
DbEntity(
name='2016 SCAG Existing Land Use Parcels',
key=Key.REGION_EXISTING_LAND_USE_PARCELS,
feature_class_configuration=FeatureClassConfiguration(
abstract_class=ExistingLandUseParcel,
primary_geography=True,
primary_key='source_id',
primary_key_type='int',
fields=dict(),
related_fields=dict(land_use_definition=dict(
single=True,
related_class_name=
'footprint.client.configuration.scag_dm.built_form.scag_dm_land_use_definition.ScagDmLandUseDefinition',
related_class_join_field_name='land_use',
source_class_join_field_name='scag_lu16'))),
feature_behavior=FeatureBehavior(
behavior=get_behavior('reference')),
_categories=[
Category(key=DbEntityCategoryKey.KEY_CLASSIFICATION,
value=DbEntityCategoryKey.REFERENCE)
])),
update_or_create_db_entity(
config_entity,
DbEntity(key=Key.FLOOD_ZONES,
feature_class_configuration=FeatureClassConfiguration(
abstract_class=FloodZones),
feature_behavior=FeatureBehavior(
behavior=get_behavior(
'reference_layers_editable_attribute'),
intersection=GeographicIntersection.
polygon_to_polygon),
_categories=[
Category(
key=DbEntityCategoryKey.KEY_CLASSIFICATION,
value=DbEntityCategoryKey.REFERENCE)
])),
update_or_create_db_entity(
config_entity,
DbEntity(key=Key.ENDANGERED_SPECIES,
feature_class_configuration=FeatureClassConfiguration(
abstract_class=EndangeredSpecies),
feature_behavior=FeatureBehavior(
behavior=get_behavior(
'reference_layers_editable_attribute'),
intersection=GeographicIntersection.
polygon_to_polygon),
_categories=[
Category(
key=DbEntityCategoryKey.KEY_CLASSIFICATION,
value=DbEntityCategoryKey.REFERENCE)
])),
update_or_create_db_entity(
config_entity,
DbEntity(key=Key.CPAD_HOLDINGS,
feature_class_configuration=FeatureClassConfiguration(
abstract_class=CpadHoldings),
feature_behavior=FeatureBehavior(
behavior=get_behavior(
'reference_layers_editable_attribute'),
intersection=GeographicIntersection.
polygon_to_polygon),
_categories=[
Category(
key=DbEntityCategoryKey.KEY_CLASSIFICATION,
value=DbEntityCategoryKey.REFERENCE)
])),
update_or_create_db_entity(
config_entity,
DbEntity(key=Key.HABITAT_CONSERVATION_AREA,
feature_class_configuration=FeatureClassConfiguration(
abstract_class=HabitatConservationAreas),
feature_behavior=FeatureBehavior(
behavior=get_behavior(
'reference_layers_editable_attribute'),
intersection=GeographicIntersection.
polygon_to_polygon),
_categories=[
Category(
key=DbEntityCategoryKey.KEY_CLASSIFICATION,
value=DbEntityCategoryKey.REFERENCE)
])),
update_or_create_db_entity(
config_entity,
DbEntity(key=Key.COUNTY_BOUNDARY,
feature_class_configuration=FeatureClassConfiguration(
abstract_class=CountyBoundary),
feature_behavior=FeatureBehavior(
behavior=get_behavior('reference'),
intersection=GeographicIntersection.
polygon_to_polygon),
_categories=[
Category(
key=DbEntityCategoryKey.KEY_CLASSIFICATION,
value=DbEntityCategoryKey.REFERENCE)
])),
update_or_create_db_entity(
config_entity,
DbEntity(name='2040 High Quality Transit Areas',
key=Key.HIGH_QUALITY_TRANSIT_AREAS,
feature_class_configuration=FeatureClassConfiguration(
abstract_class=HighQualityTransitAreas),
feature_behavior=FeatureBehavior(
behavior=get_behavior(
'reference_layers_editable_attribute'),
intersection=GeographicIntersection.
polygon_to_polygon),
_categories=[
Category(
key=DbEntityCategoryKey.KEY_CLASSIFICATION,
value=DbEntityCategoryKey.REFERENCE)
])),
update_or_create_db_entity(
config_entity,
DbEntity(name='2040 High Quality Transit Corridors',
key=Key.HIGH_QUALITY_TRANSIT_CORRIDORS,
feature_class_configuration=FeatureClassConfiguration(
abstract_class=HighQualityTransitCorridors),
feature_behavior=FeatureBehavior(
behavior=get_behavior(
'reference_layers_editable_attribute'),
intersection=GeographicIntersection.
polygon_to_polygon),
_categories=[
Category(
key=DbEntityCategoryKey.KEY_CLASSIFICATION,
value=DbEntityCategoryKey.REFERENCE)
])),
update_or_create_db_entity(
config_entity,
DbEntity(name='2040 Major Transit Stops',
key=Key.MAJOR_TRANSIT_STOPS,
feature_class_configuration=FeatureClassConfiguration(
abstract_class=MajorTransitStops),
feature_behavior=FeatureBehavior(
behavior=get_behavior(
'reference_layers_editable_attribute'),
intersection=GeographicIntersection.
polygon_to_polygon),
_categories=[
Category(
key=DbEntityCategoryKey.KEY_CLASSIFICATION,
value=DbEntityCategoryKey.REFERENCE)
])),
update_or_create_db_entity(
config_entity,
DbEntity(name='2040 Transit Priority Areas',
key=Key.TRANSIT_PRIORITY_AREAS,
feature_class_configuration=FeatureClassConfiguration(
abstract_class=TransitPriorityAreas),
feature_behavior=FeatureBehavior(
behavior=get_behavior(
'reference_layers_editable_attribute'),
intersection=GeographicIntersection.
polygon_to_polygon),
_categories=[
Category(
key=DbEntityCategoryKey.KEY_CLASSIFICATION,
value=DbEntityCategoryKey.REFERENCE)
])),
update_or_create_db_entity(
config_entity,
DbEntity(
key=Key.FARMLAND,
feature_class_configuration=FeatureClassConfiguration(
abstract_class=Farmland,
related_fields=dict(farmland_definition=dict(
single=True,
related_class_name=
'footprint.client.configuration.scag_dm.built_form.scag_dm_farmland_definition.ScagDmFarmlandDefinition',
related_class_join_field_name='farmland_code',
source_class_join_field_name='scag_type'))),
feature_behavior=FeatureBehavior(
behavior=get_behavior(
'reference_layers_editable_attribute'),
intersection=GeographicIntersection.polygon_to_centroid
),
_categories=[
Category(key=DbEntityCategoryKey.KEY_CLASSIFICATION,
value=DbEntityCategoryKey.REFERENCE)
])),
update_or_create_db_entity(
config_entity,
DbEntity(
key=Key.REGION_GENERAL_PLAN_PARCELS,
feature_class_configuration=FeatureClassConfiguration(
abstract_class=GeneralPlanParcels,
primary_key='source_id',
primary_key_type='int',
fields=dict(),
related_fields=dict(land_use_definition=dict(
single=True,
related_class_name=
'footprint.client.configuration.scag_dm.built_form.scag_dm_land_use_definition.ScagDmLandUseDefinition',
# Use this for the resource type, since we don't want a client-specific resource URL
# TODO not wired up yet
resource_model_class_name=
'footprint.main.models.built_form.ClientLandUseDefinition',
related_class_join_field_name='land_use',
source_class_join_field_name='scag_gp_code16'))),
feature_behavior=FeatureBehavior(
behavior=get_behavior('reference'),
intersection=AttributeIntersection()),
_categories=[
Category(key=DbEntityCategoryKey.KEY_CLASSIFICATION,
value=DbEntityCategoryKey.REFERENCE)
])),
update_or_create_db_entity(
config_entity,
DbEntity(
key=Key.REGION_SPECIFIC_PLAN_PARCELS,
feature_class_configuration=FeatureClassConfiguration(
abstract_class=SpecificPlanParcels,
primary_key='source_id',
primary_key_type='int',
fields=dict(),
related_fields=dict(land_use_definition=dict(
single=True,
related_class_name=
'footprint.client.configuration.scag_dm.built_form.scag_dm_land_use_definition.ScagDmLandUseDefinition',
resource_model_class_name=
'footprint.main.models.built_form.ClientLandUseDefinition',
related_class_join_field_name='land_use',
source_class_join_field_name='scag_sp_code16'))),
feature_behavior=FeatureBehavior(
behavior=get_behavior('reference'),
intersection=AttributeIntersection()),
_categories=[
Category(key=DbEntityCategoryKey.KEY_CLASSIFICATION,
value=DbEntityCategoryKey.REFERENCE)
])),
update_or_create_db_entity(
config_entity,
DbEntity(
key=Key.REGION_ZONING_PARCELS,
feature_class_configuration=FeatureClassConfiguration(
abstract_class=ZoningParcels,
primary_key='source_id',
primary_key_type='int',
fields=dict(),
related_fields=dict(land_use_definition=dict(
single=True,
related_class_name=
'footprint.client.configuration.scag_dm.built_form.scag_dm_land_use_definition.ScagDmLandUseDefinition',
resource_model_class_name=
'footprint.main.models.built_form.ClientLandUseDefinition',
related_class_join_field_name='land_use',
source_class_join_field_name='scag_zn_code16'))),
feature_behavior=FeatureBehavior(
behavior=get_behavior('reference'),
intersection=AttributeIntersection()),
_categories=[
Category(key=DbEntityCategoryKey.KEY_CLASSIFICATION,
value=DbEntityCategoryKey.REFERENCE)
])),
update_or_create_db_entity(
config_entity,
DbEntity(key=Key.REGION_ENTITLEMENT_PARCELS_2016,
feature_class_configuration=FeatureClassConfiguration(
abstract_class=EntitlementParcels,
primary_key='source_id',
primary_key_type='int',
fields=dict()),
feature_behavior=FeatureBehavior(
behavior=get_behavior('reference'),
intersection=AttributeIntersection()),
_categories=[
Category(
key=DbEntityCategoryKey.KEY_CLASSIFICATION,
value=DbEntityCategoryKey.REFERENCE)
])),
update_or_create_db_entity(
config_entity,
DbEntity(key=Key.REGION_SCENARIO_PLANNING_ZONES,
feature_class_configuration=FeatureClassConfiguration(
abstract_class=ScenarioPlanningZones, ),
feature_behavior=FeatureBehavior(
behavior=get_behavior('reference'),
intersection=GeographicIntersection.
polygon_to_centroid),
_categories=[
Category(
key=DbEntityCategoryKey.KEY_CLASSIFICATION,
value=DbEntityCategoryKey.REFERENCE)
])),
update_or_create_db_entity(
config_entity,
DbEntity(name='Sphere of Influence',
key=Key.REGION_SPHERE_OF_INFLUENCE,
feature_class_configuration=FeatureClassConfiguration(
abstract_class=SphereOfInfluence, ),
feature_behavior=FeatureBehavior(
behavior=get_behavior(
'reference_layers_editable_attribute'),
intersection=GeographicIntersection.
polygon_to_centroid),
_categories=[
Category(
key=DbEntityCategoryKey.KEY_CLASSIFICATION,
value=DbEntityCategoryKey.REFERENCE)
])),
update_or_create_db_entity(
config_entity,
DbEntity(key=Key.REGION_TIER2_TAZ,
feature_class_configuration=FeatureClassConfiguration(
abstract_class=Tier2Taz, ),
feature_behavior=FeatureBehavior(
behavior=get_behavior('reference'),
intersection=GeographicIntersection.
polygon_to_centroid),
_categories=[
Category(
key=DbEntityCategoryKey.KEY_CLASSIFICATION,
value=DbEntityCategoryKey.REFERENCE)
])),
update_or_create_db_entity(
config_entity,
DbEntity(key=Key.CENSUS_TRACTS,
feature_class_configuration=FeatureClassConfiguration(
abstract_class=CensusTracts, ),
feature_behavior=FeatureBehavior(
behavior=get_behavior(
'reference_layers_editable_attribute'),
intersection=GeographicIntersection.
polygon_to_centroid),
_categories=[
Category(
key=DbEntityCategoryKey.KEY_CLASSIFICATION,
value=DbEntityCategoryKey.REFERENCE)
])),
update_or_create_db_entity(
config_entity,
DbEntity(key=Key.SUB_REGION,
feature_class_configuration=FeatureClassConfiguration(
abstract_class=SubRegion, ),
feature_behavior=FeatureBehavior(
behavior=get_behavior('reference'),
intersection=GeographicIntersection.
polygon_to_centroid),
_categories=[
Category(
key=DbEntityCategoryKey.KEY_CLASSIFICATION,
value=DbEntityCategoryKey.REFERENCE)
])),
update_or_create_db_entity(
config_entity,
DbEntity(key=Key.REGION_CITY_BOUNDARY,
feature_class_configuration=FeatureClassConfiguration(
abstract_class=CityBoundary, ),
feature_behavior=FeatureBehavior(
behavior=get_behavior('editable_feature'),
intersection=GeographicIntersection.
polygon_to_centroid),
_categories=[
Category(
key=DbEntityCategoryKey.KEY_CLASSIFICATION,
value=DbEntityCategoryKey.REFERENCE)
])),
# update_or_create_db_entity(config_entity, DbEntity(
# key=Key.BIKE_LANE,
# feature_class_configuration=FeatureClassConfiguration(
# abstract_class=BikeLane,
# ),
# feature_behavior=FeatureBehavior(
# behavior=get_behavior('reference_layers_editable_attribute'),
# intersection=GeographicIntersection.polygon_to_centroid
# ),
# _categories=[Category(key=DbEntityCategoryKey.KEY_CLASSIFICATION, value=DbEntityCategoryKey.REFERENCE)]
# )),
update_or_create_db_entity(
config_entity,
DbEntity(key=Key.SEA_LEVEL_RISE,
feature_class_configuration=FeatureClassConfiguration(
abstract_class=SeaLevelRise, ),
feature_behavior=FeatureBehavior(
behavior=get_behavior(
'reference_layers_editable_attribute'),
intersection=GeographicIntersection.
polygon_to_centroid),
_categories=[
Category(
key=DbEntityCategoryKey.KEY_CLASSIFICATION,
value=DbEntityCategoryKey.REFERENCE)
]))
])
def layers(self, class_scope=None):
return self.parent_fixture.layers() + FixtureList([
LayerConfiguration(library_keys=[LayerLibraryKey.APPLICATION],
db_entity_key=DbEntityKey.CENSUS_TRACTS,
layer_style=dict(
geometry_type=GeometryTypeKey.POLYGON,
style_attributes=[
dict(style_type=StyleTypeKey.SINGLE,
style_value_contexts=[
StyleValueContext(
value=None,
symbol=None,
style=Style(
line_color='#990000',
line_opacity=0.8,
line_width=3))
])
])),
LayerConfiguration(library_keys=[LayerLibraryKey.APPLICATION],
db_entity_key=DbEntityKey.CENSUS_BLOCKGROUPS,
layer_style=dict(
geometry_type=GeometryTypeKey.POLYGON,
style_attributes=[
dict(style_type=StyleTypeKey.SINGLE,
style_value_contexts=[
StyleValueContext(
value=None,
symbol=None,
style=Style(
line_color='#CD5555',
line_opacity=0.8,
line_width=3))
])
])),
LayerConfiguration(library_keys=[LayerLibraryKey.APPLICATION],
db_entity_key=DbEntityKey.CENSUS_BLOCK,
layer_style=dict(
geometry_type=GeometryTypeKey.POLYGON,
style_attributes=[
dict(style_type=StyleTypeKey.SINGLE,
style_value_contexts=[
StyleValueContext(
value=None,
symbol=None,
style=Style(
line_color='#E60000',
line_opacity=0.8,
line_width=3))
])
])),
LayerConfiguration(
library_keys=[LayerLibraryKey.APPLICATION],
db_entity_key=DbEntityKey.BASE_CANVAS,
column_alias_lookup=dict(built_form__id='built_form_id'),
layer_style=built_form_based_layer_style(),
sort_priority=LayerSort.BASE),
LayerConfiguration(
library_keys=[LayerLibraryKey.APPLICATION],
db_entity_key=DbEntityKey.BASE_AGRICULTURE_CANVAS,
column_alias_lookup=dict(built_form__id='built_form_id'),
layer_style=built_form_based_layer_style(),
sort_priority=LayerSort.BASE),
LayerConfiguration(
library_keys=[LayerLibraryKey.APPLICATION],
db_entity_key=DbEntityKey.ENERGY,
layer_style=dict(
geometry_type=GeometryTypeKey.POLYGON,
style_attributes=[
dict(attribute='annual_million_btus_per_unit',
style_type=StyleTypeKey.QUANTITATIVE,
style_value_contexts=[
StyleValueContext(
value=0,
symbol='=',
style=Style(polygon_fill='#909090')),
StyleValueContext(
value=0,
symbol='>',
style=Style(polygon_fill='#97D704')),
StyleValueContext(
value=5,
symbol='>',
style=Style(polygon_fill='#B2D103')),
StyleValueContext(
value=10,
symbol='>',
style=Style(polygon_fill='#CBCA03')),
StyleValueContext(
value=15,
symbol='>',
style=Style(polygon_fill='#C5A703')),
StyleValueContext(
value=20,
symbol='>',
style=Style(polygon_fill='#BF8603')),
StyleValueContext(
value=30,
symbol='>',
style=Style(polygon_fill='#B96602')),
StyleValueContext(
value=40,
symbol='>',
style=Style(polygon_fill='#B34802')),
StyleValueContext(
value=55,
symbol='>',
style=Style(polygon_fill='#AD2C02')),
StyleValueContext(
value=80,
symbol='>',
style=Style(polygon_fill='#A71102')),
StyleValueContext(
value=120,
symbol='>',
style=Style(polygon_fill='#A1020B')),
])
])),
LayerConfiguration(
library_keys=[LayerLibraryKey.APPLICATION],
db_entity_key=DbEntityKey.WATER,
layer_style=dict(
geometry_type=GeometryTypeKey.POLYGON,
style_attributes=[
dict(attribute='annual_gallons_per_unit',
style_type=StyleTypeKey.QUANTITATIVE,
style_value_contexts=[
StyleValueContext(
value=0,
symbol='=',
style=Style(polygon_fill='#909090')),
StyleValueContext(
value=0,
symbol='>',
style=Style(polygon_fill='#B3D8FF')),
StyleValueContext(
value=40,
symbol='>',
style=Style(polygon_fill='#9FC6F0')),
StyleValueContext(
value=60,
symbol='>',
style=Style(polygon_fill='#8BB5E1')),
StyleValueContext(
value=80,
symbol='>',
style=Style(polygon_fill='#77A4D2')),
StyleValueContext(
value=120,
symbol='>',
style=Style(polygon_fill='#6392C3')),
StyleValueContext(
value=160,
symbol='>',
style=Style(polygon_fill='#6392C3')),
StyleValueContext(
value=200,
symbol='>',
style=Style(polygon_fill='#5081B5')),
StyleValueContext(
value=250,
symbol='>',
style=Style(polygon_fill='#3C70A6')),
StyleValueContext(
value=300,
symbol='>',
style=Style(polygon_fill='#285E97')),
StyleValueContext(
value=350,
symbol='>',
style=Style(polygon_fill='#144D88')),
StyleValueContext(
value=400,
symbol='>',
style=Style(polygon_fill='#013C7A')),
])
])),
LayerConfiguration(
library_keys=[LayerLibraryKey.APPLICATION],
db_entity_key=DbEntityKey.VMT,
layer_style=dict(
geometry_type=GeometryTypeKey.POLYGON,
style_attributes=[
dict(attribute='vmt_daily_per_hh',
style_type=StyleTypeKey.QUANTITATIVE,
style_value_contexts=[
StyleValueContext(value=0,
symbol='=',
style=Style(
polygon_fill='#E8E8E8',
line_color='#909090',
line_width=.3)),
StyleValueContext(value=0,
symbol='>',
style=Style(
polygon_fill='#004d1a',
line_color='#909090',
line_width=.3)),
StyleValueContext(value=20,
symbol='>',
style=Style(
polygon_fill='#009933',
line_color='#909090',
line_width=.3)),
StyleValueContext(value=30,
symbol='>',
style=Style(
polygon_fill='#00CC33',
line_color='#909090',
line_width=.3)),
StyleValueContext(value=40,
symbol='>',
style=Style(
polygon_fill='#FFFF00',
line_color='#909090',
line_width=.3)),
StyleValueContext(value=60,
symbol='>',
style=Style(
polygon_fill='#FF9900',
line_color='#909090',
line_width=.3)),
StyleValueContext(value=80,
symbol='>',
style=Style(
polygon_fill='#cc1500',
line_color='#909090',
line_width=.3))
])
])),
LayerConfiguration(
library_keys=[LayerLibraryKey.APPLICATION],
db_entity_key=DbEntityKey.INCREMENT,
column_alias_lookup=dict(built_form__id='built_form_id'),
layer_style=built_form_based_layer_style(),
sort_priority=LayerSort.FUTURE + 1),
LayerConfiguration(
library_keys=[LayerLibraryKey.APPLICATION],
db_entity_key=DbEntityKey.END_STATE,
visible=True,
column_alias_lookup=dict(built_form__id='built_form_id'),
layer_style=built_form_based_layer_style(),
sort_priority=LayerSort.FUTURE + 2),
LayerConfiguration(
library_keys=[LayerLibraryKey.APPLICATION],
db_entity_key=DbEntityKey.FUTURE_AGRICULTURE_CANVAS,
visible=True,
column_alias_lookup=dict(built_form__id='built_form_id'),
layer_style=built_form_based_layer_style(),
sort_priority=LayerSort.FUTURE + 3),
LayerConfiguration(
library_keys=[LayerLibraryKey.APPLICATION],
db_entity_key=SacogDbEntityKey.EXISTING_LAND_USE_PARCELS,
visible=True,
column_alias_lookup=dict(
land_use_definition__id='land_use_definition_id'),
built_form_set_key='sacog_land_use',
layer_style=primary_base_layer_style(SacogLandUseDefinition)),
LayerConfiguration(library_keys=[LayerLibraryKey.APPLICATION],
db_entity_key=SacogDbEntityKey.STREAM,
layer_style=dict(
geometry_type=GeometryTypeKey.POLYGON,
style_attributes=[
dict(style_type=StyleTypeKey.SINGLE,
style_value_contexts=[
StyleValueContext(
value=None,
symbol=None,
style=Style(
polygon_fill='#00008B',
polygon_opacity=0.75))
])
])),
LayerConfiguration(library_keys=[LayerLibraryKey.APPLICATION],
db_entity_key=SacogDbEntityKey.VERNAL_POOL,
layer_style=dict(
geometry_type=GeometryTypeKey.POLYGON,
style_attributes=[
dict(style_type=StyleTypeKey.SINGLE,
style_value_contexts=[
StyleValueContext(
value=None,
symbol=None,
style=Style(
polygon_fill='#008080',
polygon_opacity=0.75))
])
])),
LayerConfiguration(library_keys=[LayerLibraryKey.APPLICATION],
db_entity_key=SacogDbEntityKey.WETLAND,
layer_style=dict(
geometry_type=GeometryTypeKey.POLYGON,
style_attributes=[
dict(style_type=StyleTypeKey.SINGLE,
style_value_contexts=[
StyleValueContext(
value=None,
symbol=None,
style=Style(
polygon_fill='#00688B',
polygon_opacity=0.75))
])
])),
LayerConfiguration(library_keys=[LayerLibraryKey.APPLICATION],
db_entity_key=SacogDbEntityKey.LIGHT_RAIL,
layer_style=dict(
geometry_type=GeometryTypeKey.LINESTRING,
style_attributes=[
dict(style_type=StyleTypeKey.SINGLE,
style_value_contexts=[
StyleValueContext(
value=None,
symbol=None,
style=Style(
line_color='#660066',
line_width=6))
])
])),
LayerConfiguration(
library_keys=[LayerLibraryKey.APPLICATION],
db_entity_key=SacogDbEntityKey.LIGHT_RAIL_STOPS,
layer_style=dict(
geometry_type=GeometryTypeKey.POINT,
style_attributes=[
dict(style_type=StyleTypeKey.SINGLE,
style_value_contexts=[
StyleValueContext(
value=None,
symbol=None,
style=Style(marker_fill='#000080',
marker_width=10,
marker_line_color='white',
marker_line_width=1))
])
])),
LayerConfiguration(
library_keys=[LayerLibraryKey.APPLICATION],
db_entity_key=SacogDbEntityKey.LIGHT_RAIL_STOPS_ONE_MILE,
layer_style=dict(geometry_type=GeometryTypeKey.POLYGON,
style_attributes=[
dict(style_type=StyleTypeKey.SINGLE,
style_value_contexts=[
StyleValueContext(
value=None,
symbol=None,
style=Style(
line_color='#CC00FF',
line_width=2))
])
])),
LayerConfiguration(
library_keys=[LayerLibraryKey.APPLICATION],
db_entity_key=SacogDbEntityKey.LIGHT_RAIL_STOPS_HALF_MILE,
layer_style=dict(geometry_type=GeometryTypeKey.POLYGON,
style_attributes=[
dict(style_type=StyleTypeKey.SINGLE,
style_value_contexts=[
StyleValueContext(
value=None,
symbol=None,
style=Style(
line_color='#CC00FF',
line_width=2))
])
])),
LayerConfiguration(
library_keys=[LayerLibraryKey.APPLICATION],
db_entity_key=SacogDbEntityKey.LIGHT_RAIL_STOPS_QUARTER_MILE,
layer_style=dict(geometry_type=GeometryTypeKey.POLYGON,
style_attributes=[
dict(style_type=StyleTypeKey.SINGLE,
style_value_contexts=[
StyleValueContext(
value=None,
symbol=None,
style=Style(
line_color='#CC00FF',
line_width=2))
])
])),
LayerConfiguration(
library_keys=[LayerLibraryKey.APPLICATION],
db_entity_key=DbEntityKey.PH_BLOCK_GROUP_OUTCOMES,
layer_style=dict(
geometry_type=GeometryTypeKey.POLYGON,
style_attributes=[
dict(attribute='adult_all_walk_minutes',
style_type=StyleTypeKey.QUANTITATIVE,
style_value_contexts=[
StyleValueContext(value=0,
symbol='=',
style=Style(
polygon_fill='#E8E8E8',
polygon_opacity=0.3)),
StyleValueContext(value=0,
symbol='>',
style=Style(
polygon_fill='#C3523C',
polygon_opacity=0.3)),
StyleValueContext(value=2,
symbol='>',
style=Style(
polygon_fill='#B1782D',
polygon_opacity=0.3)),
StyleValueContext(value=4,
symbol='>',
style=Style(
polygon_fill='#9F9F1E',
polygon_opacity=0.3)),
StyleValueContext(value=6,
symbol='>',
style=Style(
polygon_fill='#8DC60F',
polygon_opacity=0.3)),
StyleValueContext(value=8,
symbol='>',
style=Style(
polygon_fill='#7BED00',
polygon_opacity=0.3)),
StyleValueContext(value=15,
symbol='>',
style=Style(
polygon_fill='#5FBC1E',
polygon_opacity=0.3)),
StyleValueContext(value=20,
symbol='>',
style=Style(
polygon_fill='#438C3D',
polygon_opacity=0.3)),
StyleValueContext(value=25,
symbol='>',
style=Style(
polygon_fill='#275C5B',
polygon_opacity=0.3)),
StyleValueContext(value=30,
symbol='>',
style=Style(
polygon_fill='#0B2C7A',
polygon_opacity=0.3)),
])
]))
])
def layer_libraries(self, class_scope=None):
return self.parent_fixture.layer_libraries(
FixtureList(self.layers()).matching_scope(
class_scope=self.config_entity
and self.config_entity.__class__))
def default_db_entities(self):
"""
Scenarios define DbEntities specific to the Scenario. Creates a list a dictionary of configuration
functionality. These are filtered based on whether the given scenario matches the scope in the
configuration
:return:
"""
scenario = self.config_entity
project = self.config_entity.parent_config_entity
# The Behavior keyspace
behavior_key = BehaviorKey.Fab.ricate
# Used to load Behaviors defined elsewhere
get_behavior = lambda key: Behavior.objects.get(key=behavior_key(key))
return super(SacogScenarioFixture, self).default_db_entities() + map(
lambda db_entity_dict: update_or_create_db_entity(
scenario, db_entity_dict['value']),
FixtureList([
dict(
class_scope=FutureScenario,
value=DbEntity(
key=DbEntityKey.INCREMENT,
feature_class_configuration=FeatureClassConfiguration(
abstract_class=CoreIncrementFeature,
import_from_db_entity_key=DbEntityKey.BASE_CANVAS,
import_ids_only=True,
related_fields=dict(built_form=dict(
single=True,
related_class_name=uf_model(
'built_form.built_form.BuiltForm')))),
feature_behavior=FeatureBehavior(
behavior=get_behavior('scenario_increment'),
intersection=AttributeIntersection(
from_attribute='id', to_attribute='id')),
_categories=[
Category(
key=DbEntityCategoryKey.KEY_CLASSIFICATION,
value=DbEntityCategoryKey.FUTURE_SCENARIO)
]),
),
dict(
class_scope=FutureScenario,
value=DbEntity(
key=DbEntityKey.END_STATE,
feature_class_configuration=FeatureClassConfiguration(
abstract_class=CanvasFeature,
import_from_db_entity_key=DbEntityKey.BASE_CANVAS,
related_fields=dict(built_form=dict(
single=True,
related_class_name=uf_model(
'built_form.built_form.BuiltForm')))),
feature_behavior=FeatureBehavior(
behavior=get_behavior('scenario_end_state'),
intersection=AttributeIntersection(
from_attribute='id', to_attribute='id')),
_categories=[
Category(
key=DbEntityCategoryKey.KEY_CLASSIFICATION,
value=DbEntityCategoryKey.FUTURE_SCENARIO)
]),
),
dict(class_scope=FutureScenario,
value=DbEntity(
key=DbEntityKey.FUTURE_AGRICULTURE_CANVAS,
name='Scenario Agriculture End State',
feature_class_configuration=FeatureClassConfiguration(
abstract_class=AgricultureFeature,
import_from_db_entity_key=DbEntityKey.
BASE_AGRICULTURE_CANVAS,
import_ids_only=False,
related_fields=dict(built_form=dict(
single=True,
related_class_name=uf_model(
'built_form.built_form.BuiltForm'),
related_class_join_field_name='key',
source_class_join_field_name='built_form_key')
)),
feature_behavior=FeatureBehavior(
behavior=get_behavior('agriculture_scenario'),
intersection=AttributeIntersection(
from_attribute='id', to_attribute='id')),
_categories=[
Category(
key=DbEntityCategoryKey.KEY_CLASSIFICATION,
value=DbEntityCategoryKey.FUTURE_SCENARIO)
])),
dict(class_scope=FutureScenario,
value=DbEntity(
key=DbEntityKey.FISCAL,
feature_class_configuration=FeatureClassConfiguration(
abstract_class=FiscalFeature,
import_from_db_entity_key=DbEntityKey.BASE_CANVAS,
empty_table=True),
feature_behavior=FeatureBehavior(
behavior=get_behavior('internal_analysis'),
intersection=AttributeIntersection(
from_attribute='id', to_attribute='id')),
_categories=[
Category(
key=DbEntityCategoryKey.KEY_CLASSIFICATION,
value=DbEntityCategoryKey.ANALYSIS_RESULTS)
])),
dict(class_scope=Scenario,
value=DbEntity(
key=DbEntityKey.VMT_VARIABLES,
feature_class_configuration=FeatureClassConfiguration(
abstract_class=VmtVariablesFeature,
import_from_db_entity_key=DbEntityKey.BASE_CANVAS,
import_ids_only=True,
filter_query=dict(),
),
feature_behavior=FeatureBehavior(
behavior=get_behavior('internal_analysis'),
intersection=AttributeIntersection(
from_attribute='id', to_attribute='id')),
_categories=[
Category(
key=DbEntityCategoryKey.KEY_CLASSIFICATION,
value=DbEntityCategoryKey.REFERENCE)
])),
dict(class_scope=Scenario,
value=DbEntity(
key=DbEntityKey.VMT,
name='Vehicle Miles Traveled Output',
feature_class_configuration=FeatureClassConfiguration(
abstract_class=VmtFeature,
import_from_db_entity_key=DbEntityKey.BASE_CANVAS,
empty_table=True),
feature_behavior=FeatureBehavior(
behavior=get_behavior('internal_analysis'),
intersection=AttributeIntersection(
from_attribute='id', to_attribute='id')),
_categories=[
Category(
key=DbEntityCategoryKey.KEY_CLASSIFICATION,
value=DbEntityCategoryKey.ANALYSIS_RESULTS)
])),
dict(class_scope=Scenario,
value=DbEntity(
key=DbEntityKey.ENERGY,
name='Energy Demand Output',
feature_class_configuration=FeatureClassConfiguration(
abstract_class=EnergyFeature,
import_from_db_entity_key=DbEntityKey.BASE_CANVAS,
empty_table=True),
feature_behavior=FeatureBehavior(
behavior=get_behavior('internal_analysis'),
intersection=AttributeIntersection(
from_attribute='id', to_attribute='id')),
_categories=[
Category(
key=DbEntityCategoryKey.KEY_CLASSIFICATION,
value=DbEntityCategoryKey.ANALYSIS_RESULTS)
])),
dict(class_scope=Scenario,
value=DbEntity(
key=DbEntityKey.WATER,
name='Water Demand Output',
feature_class_configuration=FeatureClassConfiguration(
abstract_class=WaterFeature,
import_from_db_entity_key=DbEntityKey.BASE_CANVAS,
empty_table=True),
feature_behavior=FeatureBehavior(
behavior=get_behavior('internal_analysis'),
intersection=AttributeIntersection(
from_attribute='id', to_attribute='id')),
_categories=[
Category(
key=DbEntityCategoryKey.KEY_CLASSIFICATION,
value=DbEntityCategoryKey.ANALYSIS_RESULTS)
])),
dict(class_scope=Scenario,
value=DbEntity(
key=DbEntityKey.PH_VARIABLES,
feature_class_configuration=FeatureClassConfiguration(
abstract_class=PhVariablesFeature,
import_from_db_entity_key=DbEntityKey.GRID_150M,
import_ids_only=True,
filter_query=dict(),
),
feature_behavior=FeatureBehavior(
behavior=get_behavior('internal_analysis'),
intersection=GeographicIntersection.
polygon_to_polygon),
_categories=[
Category(
key=DbEntityCategoryKey.KEY_CLASSIFICATION,
value=DbEntityCategoryKey.REFERENCE)
])),
dict(class_scope=Scenario,
value=DbEntity(
key=DbEntityKey.PH_GRID_OUTCOMES,
feature_class_configuration=FeatureClassConfiguration(
abstract_class=PhGridOutcomesFeature,
import_from_db_entity_key=DbEntityKey.GRID_150M,
import_ids_only=True,
filter_query=dict(),
),
feature_behavior=FeatureBehavior(
behavior=get_behavior('internal_analysis'),
intersection=GeographicIntersection.
polygon_to_polygon),
_categories=[
Category(
key=DbEntityCategoryKey.KEY_CLASSIFICATION,
value=DbEntityCategoryKey.REFERENCE)
])),
dict(class_scope=Scenario,
value=DbEntity(
key=DbEntityKey.PH_BLOCK_GROUP_OUTCOMES,
name='Public Health Output',
feature_class_configuration=FeatureClassConfiguration(
abstract_class=PhBlockGroupOutcomesFeature,
import_from_db_entity_key=DbEntityKey.GRID_150M,
import_ids_only=True,
filter_query=dict(),
),
feature_behavior=FeatureBehavior(
behavior=get_behavior('internal_analysis'),
intersection=GeographicIntersection.
polygon_to_polygon),
_categories=[
Category(
key=DbEntityCategoryKey.KEY_CLASSIFICATION,
value=DbEntityCategoryKey.ANALYSIS_RESULTS)
])),
dict(class_scope=Scenario,
value=DbEntity(
key=DbEntityKey.PH_OUTCOMES_SUMMARY,
feature_class_configuration=FeatureClassConfiguration(
abstract_class=PhOutcomesSummary,
no_table_associations=True,
empty_table=True,
),
feature_behavior=FeatureBehavior(
behavior=get_behavior('internal_analysis'),
intersection=GeographicIntersection.
polygon_to_polygon),
_categories=[
Category(
key=DbEntityCategoryKey.KEY_CLASSIFICATION,
value=DbEntityCategoryKey.ANALYSIS_RESULTS)
]))
]).matching_scope(class_scope=self.config_entity
and self.config_entity.__class__))
def results(self):
"""
Used to update or create Results per ConfigEntity instance
Returns the result library(ies) scoped for the class of self.config_entity.
The Result will belong to the ResultLibrary specified by result_library_key
:return:
"""
return FixtureList(
# Basic Core result query that summarizes increments
self.parent_fixture.results() + [
# Line Chart Config
ResultConfiguration(
result_type='line_chart',
library_keys=[ResultLibraryKey.APPLICATION],
result_db_entity_key=ResultKey.POPULATION_BY_YEAR,
source_db_entity_key=ScagDmDbEntityKey.CITY_BOUNDARY,
name='Population By Year',
attributes=['pop16', 'pop20', 'pop30', 'pop35', 'pop45'],
db_column_lookup=dict(pop16='pop16',
pop20='pop20',
pop30='pop30',
pop35='pop35',
pop45='pop45'),
labels=['pop16', 'pop20', 'pop30', 'pop35', 'pop45'],
stackable=False,
is_stacked=False,
create_query=lambda result_config:
'SELECT SUM(pop16) as pop16__sum, SUM(pop20) as pop20__sum, SUM(pop30) as pop30__sum, SUM(pop35) as pop35__sum, SUM(pop45) as pop45__sum FROM %({0})s'
.format(ScagDmDbEntityKey.CITY_BOUNDARY),
sort_priority=ResultSort.BASE),
ResultConfiguration(
result_type='line_chart',
library_keys=[ResultLibraryKey.APPLICATION],
result_db_entity_key=ResultKey.HOUSEHOLDS_BY_YEAR,
source_db_entity_key=ScagDmDbEntityKey.CITY_BOUNDARY,
name='Households By Year',
attributes=['hh16', 'hh20', 'hh30', 'hh35', 'hh45'],
db_column_lookup=dict(hh16='hh16',
hh20='hh20',
hh30='hh30',
hh35='hh35',
hh45='hh45'),
labels=['hh16', 'hh20', 'hh30', 'hh35', 'hh45'],
stackable=False,
is_stacked=False,
create_query=lambda result_config:
'SELECT SUM(hh16) as hh16__sum, SUM(hh20) as hh20__sum, SUM(hh30) as hh30__sum, SUM(hh35) as hh35__sum, SUM(hh45) as hh45__sum FROM %({0})s'
.format(ScagDmDbEntityKey.CITY_BOUNDARY),
sort_priority=ResultSort.BASE),
ResultConfiguration(
result_type='line_chart',
library_keys=[ResultLibraryKey.APPLICATION],
result_db_entity_key=ResultKey.EMPLOYMENT_BY_YEAR,
source_db_entity_key=ScagDmDbEntityKey.CITY_BOUNDARY,
name='Employment By Year',
attributes=['emp16', 'emp20', 'emp30', 'emp35', 'emp45'],
db_column_lookup=dict(emp16='emp16',
emp20='emp20',
emp30='emp30',
emp35='emp35',
emp45='emp45'),
labels=['emp16', 'emp20', 'emp30', 'emp35', 'emp45'],
stackable=False,
is_stacked=False,
create_query=lambda result_config:
'SELECT SUM(emp16) as emp16__sum, SUM(emp20) as emp20__sum, SUM(emp30) as emp30__sum, SUM(emp35) as emp35__sum, SUM(emp45) as emp45__sum FROM %({0})s'
.format(ScagDmDbEntityKey.CITY_BOUNDARY),
sort_priority=ResultSort.BASE)
])
def behaviors(self, **kwargs):
key = BehaviorKey.Fab.ricate
# This doesn't fetch from the database, since the Behavior being sought might not exist quite yet
polygon = GeographicKey.POLYGON
# Create a special DbEntity used only by Behavior.feature_template_behavior instances
dummy_user = get_user_model().objects.get(username=UserGroupKey.SUPERADMIN)
DbEntity.objects.update_or_create(key='template_feature_behavior', defaults=dict(
creator=dummy_user,
updater=dummy_user))
return FixtureList([
Behavior(
key=key('environmental_constraint'),
parents=[],
# Environmental constraints always intersect primary features polygon to polygon
intersection=GeographicIntersection.polygon_to_polygon
),
# A behavior attributed to Features representing UrbanFootprint base data
Behavior(
key=key('reference'),
parents=[]
),
Behavior(
key=key('reference_layers_editable_attribute'),
parents=[]
),
Behavior(
key=key('tool'),
parents=[]
),
# A behavior attributed to a Tool that produces a result from one or more inputs
Behavior(
key=key('analysis_tool'),
parents=['tool']
),
# A behavior attributed to a Tool that performs updates
Behavior(
key=key('update_tool'),
parents=['tool']
),
# A behavior attributed to a Tool that edits features or similar
Behavior(
key=key('editor_tool'),
parents=['tool']
),
# A behavior attributed to Features representing UrbanFootprint base data
Behavior(
key=key('editable_feature'),
parents=[]
),
Behavior(
key=key('base_feature'),
parents=[]
),
# The behavior of the Agriculture Builder tool
Behavior(
key=key('agriculture_editor_tool'),
parents=['editor_tool']
),
# The behavior of the Scenario Builder tool
Behavior(
key=key('scenario_editor_tool'),
parents=['editor_tool']
),
Behavior(
key=key('sed_editor_tool'),
parents=['editor_tool']
),
# agriculture_editor_tool is a parent so that this DbEntity with this behavior will run the
# agriculture module when its features are updated
Behavior(
key=key('base_agriculture'),
parents=['agriculture_editor_tool']
),
# agriculture_editor_tool is a parent so that this DbEntity with this behavior will run the
# agriculture module when its features are updated
Behavior(
key=key('scenario_end_state'),
parents=['scenario_editor_tool']
),
Behavior(
key=key('scenario_increment'),
parents=[]
),
# agriculture_editor_tool is a parent so that this DbEntity with this behavior will run the
# agriculture module when its features are updated
Behavior(
key=key('agriculture_scenario'),
parents=['agriculture_editor_tool']
),
Behavior(
key=key('developable'),
parents=[]
),
Behavior(
key=key('internal_analysis'),
parents=[]
),
Behavior(
# Background imagery
key=key('remote_imagery'),
parents=[]
),
Behavior(
# results
key=key('result'),
parents=[]
),
Behavior(
# results
key=key('master'),
abstract=True,
parents=[]
),
Behavior(
# results
key=key('draft'),
abstract=True,
parents=[]
),
Behavior(
# results
key=key('default_config_entity'),
parents=[]
),
Behavior(
# results
key=key('base_scenario'),
parents=['default_config_entity']
),
Behavior(
# results
key=key('future_scenario'),
parents=['default_config_entity']
),
Behavior(
# results
key=key('base_master_scenario'),
parents=['base_scenario', 'master']
),
Behavior(
# results
key=key('base_draft_scenario'),
parents=['base_scenario', 'draft']
),
Behavior(
# results
key=key('future_master_scenario'),
parents=['future_scenario', 'master']
),
Behavior(
# results
key=key('future_draft_scenario'),
parents=['future_scenario', 'draft']
)
])