reverse_sliding_window

dtaianomaly.windowing.reverse_sliding_window(per_window_anomaly_scores: ndarray, window_size: int, stride: int, length_time_series: int) → ndarray

Reverse the sliding window.

For non-overlapping sliding windows, it is trivial to convert the per-window anomaly scores to per-observation scores, because each observation is linked to only one window. For overlapping windows, certain observations are linked to one or more windows (depending on the window size and stride), obstructing simply copying the corresponding per-window anomaly score to each window. In the case of multiple overlapping windows, the anomaly score of the observation is set to the mean of the corresponding per-window anomaly scores.

Parameters:

per_window_anomaly_scoresarray-like of shape (n_windows)

The anomaly scores computed for the individual windows.

window_sizeint

The window size used for creating windows.

strideint

The stride, i.e., the step size used for creating windows.

length_time_seriesint

The original length of the time series.

Returns:

np.ndarray of shape (length_time_series)

The per-observation anomaly scores.

Examples

>>> from dtaianomaly.windowing import reverse_sliding_window
>>> per_window_anomaly_scores = [0.2, 0.3, 0.5, 0.8, 0.9, 0.6, 0.2, 0.1]
>>> reverse_sliding_window(per_window_anomaly_scores, 3, 1, 10)
array([0.2     , 0.25    , 0.333..., 0.533..., 0.733...,
       0.766..., 0.566..., 0.3     , 0.15    , 0.1     ])