if first_N:
features = features[:first_N]
write_features_to_disk(features, featureset_id, in_docker_container)
if not in_docker_container:
os.remove(features_path)
return "Featurization of timeseries data complete."
def featurize_data_archive(headerfile_path, zipfile_path, features_to_use=[],
After Change
in_docker_container=False, first_N=None):
targets, metadata = ft.parse_headerfile(features_path)
if first_N:
metadata = metadata[:first_N]
if targets is not None:
targets = targets[:first_N]
featureset = ft.assemble_featureset([], targets, metadata)
write_features_to_disk(featureset, featureset_id, in_docker_container)
// if not in_docker_container:
// os.remove(features_path)
return featureset
