pytorch_forecasting.data.timeseries._find_end_indices

pytorch_forecasting.data.timeseries._find_end_indices(diffs: numpy.ndarray, max_lengths: numpy.ndarray, min_length: int) → Tuple[numpy.ndarray, numpy.ndarray]

Identify end indices in series even if some values are missing.

Parameters

• diffs (np.ndarray) – array of differences to next time step. nans should be filled up with ones

• max_lengths (np.ndarray) – maximum length of sequence by position.

• min_length (int) – minimum length of sequence.

Returns

tuple of arrays where first is end indices and second is list of start

and end indices that are currently missing.

Return type

Tuple[np.ndarray, np.ndarray]

timeseries pytorch_forecasting.data.timeseries.check_for_nonfinite