_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][source]¶
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]