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topic.item_identifiers.add(ii)
create_topic_by_item_identifier (self, item_identifier)
item_identifier.to_external_form()
Topic(topic_map=self)
topic.save()
ItemIdentifier(address=reference, containing_topic_map=self)
ii.save()
topic.item_identifiers.add(ii)
create_topic_by_subject_identifier (self, subject_identifier)
subject_identifier.to_external_form()
Topic(topic_map=self)
topic.save()
si.save()
topic.subject_identifiers.add(si)
create_topic_by_subject_locator (self, subject_locator)
subject_locator.to_external_form()
Topic(topic_map=self)
topic.save()
sl.save()
topic.subject_locators.add(sl)
get_associations (self)
self.association_constructs.all()
get_construct_by_id (self, id, proxy=None)
its (system specific)
Identifier.objects.get(pk=int(id)
identifier.get_construct()
proxy.objects.get(pk=construct.id)
get_construct_by_item_identifier (self, item_identifier)
item_identifier.to_external_form()
ii.get_construct()
get_index (self, index_interface)
index_interface(self)
get_locator (self)
Locator(self.iri)
get_parent (self)
get_topics (self)
self.topic_constructs.all()
get_topic_by_subject_identifier (self, subject_identifier)
subject_identifier.to_external_form()
get_topic_by_subject_locator (self, subject_locator)
subject_locator.to_external_form()
get_topic_map (self)
merge_in (self, other)
Model (TMDM)
copy(other, self)
remove (self)
self.delete()
__eq__ (self, other)
isinstance(other, TopicMap)
__ne__ (self, other)
not(self.__eq__(other)
__unicode__ (self)
s (%s)
argparse.ArgumentParser()
parser.parse_args()
Run.get_context()
Dataset.get_by_id(ws, id=test_dataset_id)
test_dataset.drop_columns(columns=[target_column_name])
to_pandas_dataframe()
reset_index(drop=True)
test_dataset.with_timestamp_columns(None)
keep_columns(columns=[target_column_name])
to_pandas_dataframe()
joblib.load("model.pkl")
below(95th percentile)
fitted_model.forecast_quantiles(X_test)
min(quantiles)
max(quantiles)
format(x[0], x[1])
notnull()
all(axis=1)
clean.rename(columns={target_column_name: "actual"}, inplace=True)
clean.to_csv(file_name, header=True, index=False)
run.upload_file(name=file_name, path_or_stream=file_name)
get_best_logger(log_file, verbose)
logging.getLogger(__name__)
logger.setLevel('DEBUG')
logging.FileHandler(log_file)
logging.StreamHandler()
file_handler.setFormatter(formatter)
stream_handler.setFormatter(formatter)
logger.addHandler(file_handler)
logger.addHandler(stream_handler)
compare_addresses(args)
logger.info('Started reading BOSA address file')
pd.read_csv(args.input_file_1)
logger.info('Read the BOSA address file')
logger.fatal(io)
sys.exit(1)
logger.info('Started reading comparison file')
pd.read_csv(args.input_file_2)
logger.info('Read the comparison file')
logger.fatal(io)
sys.exit(1)
args.mapping.items()
comp_keys.append(comp_key)
bosa_ids.append(bosa.columns.get_loc(bosa_key)
mapping (%s -> %s)
sys.exit(1)
logger.info('Building data structure to perform matching')