def __init__(self, source_data, dataset_name, attribute,
years = None, operation = None, name = None,
output_type = 'csv',
storage_location = None):
if output_type == 'sql' and not isinstance(storage_location, DatabaseConfiguration):
raise "If Table output_type is 'sql', a Database object must be passed as storage_location."
elif output_type in ['dbf', 'csv', 'tab', 'esri'] and \
storage_location is not None and \
not isinstance(storage_location,str):
raise "If Table output_type is %s, storage_location must be a path to the output directory"%output_type
elif output_type not in ['dbf', 'csv', 'tab', 'sql', 'esri']:
raise "Table output_type must be either dbf, csv, tab, sql, or esri"
AbstractIndicator.__init__(self, source_data, dataset_name, [attribute],
years, operation, name,
storage_location, can_write_to_db = True)
self.output_type = output_type
kwargs = {}
if self.output_type == 'sql':
kwargs['protocol'] = storage_location.protocol
kwargs['username'] = storage_location.user_name
kwargs['password'] = storage_location.password
kwargs['hostname'] = storage_location.host_name
kwargs['database_name'] = storage_location.database_name
elif self.output_type == 'esri':
kwargs['storage_location'] = storage_location
else:
kwargs['storage_location'] = self.get_storage_location()
self.store = StorageFactory().get_storage(
type = '%s_storage'%(self.output_type),
**kwargs
)
def __init__(self, source_data, dataset_name, attribute,
years = None, operation = None, name = None,
output_type = 'csv',
storage_location = None):
if output_type == 'sql' and not isinstance(storage_location, OpusDatabase):
raise "If Table output_type is 'sql', an OpusDatabase object must be passed as storage_location."
elif output_type in ['dbf', 'csv', 'tab', 'esri'] and \
storage_location is not None and \
not isinstance(storage_location,str):
raise "If Table output_type is %s, storage_location must be a path to the output directory"%output_type
elif output_type not in ['dbf', 'csv', 'tab', 'sql', 'esri']:
raise "Table output_type must be either dbf, csv, tab, sql, or esri"
AbstractIndicator.__init__(self, source_data, dataset_name, [attribute],
years=years, operation=operation, name=name,
storage_location=storage_location, can_write_to_db = True)
self.output_type = output_type
kwargs = {}
if self.output_type == 'esri':
kwargs['storage_location'] = storage_location
else:
kwargs['storage_location'] = self.get_storage_location()
self.store = StorageFactory().get_storage(
type = '%s_storage'%(self.output_type),
**kwargs
)
def __init__(self, source_data, dataset_name,
attribute = None,
years = None, operation = None, name = None,
storage_location = None):
AbstractIndicator.__init__(self, source_data, dataset_name,
[attribute], years, operation, name,
storage_location)
def __init__(self, source_data, dataset_name,
attribute = None,
years = None, operation = None, name = None,
scale = None,
storage_location = None):
if dataset_name == 'parcel':
raise Exception('Cannot create a Matplotlib map for parcel dataset. Please plot at a higher geographic aggregation')
AbstractIndicator.__init__(self, source_data, dataset_name,
[attribute], years, operation, name,
storage_location)
self.scale = scale
def __init__(self, source_data, dataset_name,
attribute = None,
years = None, operation = None, name = None,
scale = None,
storage_location = None):
if dataset_name == 'parcel':
raise Exception('Cannot create a Matplotlib map for parcel dataset. Please plot at a higher geographic aggregation')
AbstractIndicator.__init__(self, source_data, dataset_name,
[attribute], years, operation, name,
storage_location)
self.scale = scale
def __init__(self, source_data, dataset_name,
attribute = None,
years = None, operation = None, name = None,
scale = None,
storage_location = None,
project_name = None, **kwargs):
AbstractIndicator.__init__(self, source_data, dataset_name,
[attribute], years, operation, name,
storage_location)
self.scale = scale
self.project_name = project_name
self.map_args = kwargs
def __init__(
self,
source_data,
dataset_name,
attribute=None,
years=None,
operation=None,
name=None,
scale=None,
storage_location=None,
):
AbstractIndicator.__init__(
self, source_data, dataset_name, [attribute], years, operation, name, storage_location
)
self._values = None
self._ginicoeff = None
def __init__(self,
source_data,
dataset_name,
attribute=None,
years=None,
operation=None,
name=None,
scale=None,
storage_location=None,
project_name=None,
**kwargs):
AbstractIndicator.__init__(self, source_data, dataset_name,
[attribute], years, operation, name,
storage_location)
self.scale = scale
self.project_name = project_name
self.map_args = kwargs
def __init__(self,
source_data,
dataset_name,
attributes,
name,
years=None,
operation=None,
exclude_condition=None,
output_type='tab',
storage_location=None):
if output_type == 'sql' and not isinstance(storage_location,
OpusDatabase):
raise "If DatasetTable output_type is 'sql', a OpusDatabase object must be passed as storage_location."
elif output_type in ['dbf', 'csv', 'tab', 'esri'] and \
storage_location is not None and \
not isinstance(storage_location,str):
raise "If DatasetTable output_type is %s, storage_location must be a path to the output directory" % output_type
elif output_type not in ['dbf', 'csv', 'tab', 'sql', 'esri']:
raise "DatasetTable output_type needs to be either dbf, csv, tab, or sql"
self.output_type = output_type
self.exclude_condition = exclude_condition
self.name = name
AbstractIndicator.__init__(self,
source_data,
dataset_name,
attributes,
years,
operation,
name,
storage_location=storage_location,
can_write_to_db=True)
self.output_type = output_type
kwargs = {}
if self.output_type == 'esri':
kwargs['storage_location'] = storage_location
else:
kwargs['storage_location'] = self.get_storage_location()
self.store = StorageFactory().get_storage(type='%s_storage' %
(self.output_type),
**kwargs)
def __init__(self, source_data, dataset_name, attributes,
name, years = None, operation = None,
exclude_condition = None, output_type = 'tab',
storage_location = None):
if output_type == 'sql' and not isinstance(storage_location, DatabaseConfiguration):
raise "If DatasetTable output_type is 'sql', a Database object must be passed as storage_location."
elif output_type in ['dbf', 'csv', 'tab', 'esri'] and \
storage_location is not None and \
not isinstance(storage_location,str):
raise "If DatasetTable output_type is %s, storage_location must be a path to the output directory"%output_type
elif output_type not in ['dbf', 'csv', 'tab', 'sql', 'esri']:
raise "DatasetTable output_type needs to be either dbf, csv, tab, or sql"
self.output_type = output_type
self.exclude_condition = exclude_condition
self.name = name
AbstractIndicator.__init__(self, source_data, dataset_name,
attributes, years, operation, name,
storage_location=storage_location,
can_write_to_db = True)
self.output_type = output_type
kwargs = {}
if self.output_type == 'sql':
kwargs['protocol'] = storage_location.protocol
kwargs['username'] = storage_location.user_name
kwargs['password'] = storage_location.password
kwargs['hostname'] = storage_location.host_name
kwargs['database_name'] = storage_location.database_name
elif self.output_type == 'esri':
kwargs['storage_location'] = storage_location
else:
kwargs['storage_location'] = self.get_storage_location()
self.store = StorageFactory().get_storage(
type = '%s_storage'%(self.output_type),
**kwargs
)
def __init__(self, source_data, dataset_name,
attribute = None,
years = None,
operation = None,
name = None,
package = None,
prototype_dataset = None,
storage_location = None):
AbstractIndicator.__init__(self, source_data,
dataset_name, [attribute],
years, operation, name,
storage_location)
if prototype_dataset is None:
dir = directory_path_from_opus_path('%s.indicators.geotiff_files'%package)
#todo: check indicator package and find appropriate prototype image
prototype_dataset = os.path.join(dir,'idgrid.tif')
if not os.path.exists(prototype_dataset):
raise 'Error: %s does not exist. Cannot compute GeotiffMap'%prototype_dataset
self.prototype_dataset = prototype_dataset
