module datasetsforecast.phm2008
class FD001
FD001(seasonality: int = 1, horizon: int = 1, freq: str = ‘None’, train_file: str = ‘train_FD001.txt’, test_file: str = ‘test_FD001.txt’, rul_file: str = ‘RUL_FD001.txt’, n_ts: int = 100, n_test: int = 100)
method __init__
class FD002
FD002(seasonality: int = 1, horizon: int = 1, freq: str = ‘None’, train_file: str = ‘train_FD002.txt’, test_file: str = ‘test_FD002.txt’, rul_file: str = ‘RUL_FD002.txt’, n_ts: int = 260, n_test: int = 259)
method __init__
class FD003
FD003(seasonality: int = 1, horizon: int = 1, freq: str = ‘None’, train_file: str = ‘train_FD003.txt’, test_file: str = ‘test_FD003.txt’, rul_file: str = ‘RUL_FD003.txt’, n_ts: int = 100, n_test: int = 100)
method __init__
class FD004
FD004(seasonality: int = 1, horizon: int = 8, freq: str = ‘None’, train_file: str = ‘train_FD004.txt’, test_file: str = ‘test_FD004.txt’, rul_file: str = ‘RUL_FD004.txt’, n_ts: int = 249, n_test: int = 248)
method __init__
class PHM2008
PHM2008()
method __init__
method download
directory(str): Directory path to download dataset.
method load
directory(str): Directory where data will be downloaded.group(str): Group name.Allowed groups: ‘FD001’, ‘FD002’, ‘FD003’, ‘FD004’.clip_rul(bool): Wether or not upper bound the remaining useful life to 125.
Tuple[pd.DataFrame, pd.DataFrame]: Target time series with columns [‘unique_id’, ‘ds’, ‘y’, ‘exogenous’].
This file was automatically generated via lazydocs.

