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FD004

FD004(seasonality=1, horizon=8, freq='None', train_file='train_FD004.txt', test_file='test_FD004.txt', rul_file='RUL_FD004.txt', n_ts=249, n_test=248)

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FD003

FD003(seasonality=1, horizon=1, freq='None', train_file='train_FD003.txt', test_file='test_FD003.txt', rul_file='RUL_FD003.txt', n_ts=100, n_test=100)

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FD002

FD002(seasonality=1, horizon=1, freq='None', train_file='train_FD002.txt', test_file='test_FD002.txt', rul_file='RUL_FD002.txt', n_ts=260, n_test=259)

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FD001

FD001(seasonality=1, horizon=1, freq='None', train_file='train_FD001.txt', test_file='test_FD001.txt', rul_file='RUL_FD001.txt', n_ts=100, n_test=100)

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PHM2008

PHM2008()

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PHM2008.download

download(directory)
Download PHM2008 Dataset. Parameters:
NameTypeDescriptionDefault
directorystrDirectory path to download dataset.required

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PHM2008.load

load(directory, group, clip_rul=True)
Downloads and loads M3 data. Parameters:
NameTypeDescriptionDefault
directorystrDirectory where data will be downloaded.required
groupstrGroup name. Allowed groups: ‘FD001’, ‘FD002’, ‘FD003’, ‘FD004’.required
clip_rulboolWether or not upper bound the remaining useful life to 125.True
Returns:
TypeDescription
Tuple[DataFrame, DataFrame]Tuple[pd.DataFrame, pd.DataFrame]: Target time series with columns [‘unique_id’, ‘ds’, ‘y’, ‘exogenous’].