pyts.utils
.windowed_view¶
-
pyts.utils.
windowed_view
(X, window_size, window_step=1)[source]¶ Return a windowed view of a 2D array.
Parameters: - X : array-like, shape = (n_samples, n_timestamps)
Input data.
- window_size : int
The size of the window. It must be between 1 and
n_timestamps
.- window_step : int (default = 1)
The step of the sliding window
Returns: - X_new : array, shape = (n_samples, n_windows, window_size)
Windowed view of the input data.
n_windows
is computed as(n_timestamps - window_size + window_step) // window_step
.
Examples
>>> import numpy as np >>> from pyts.utils import windowed_view >>> windowed_view(np.arange(6).reshape(1, -1), window_size=2) array([[[0, 1], [1, 2], [2, 3], [3, 4], [4, 5]]])
Examples using pyts.utils.windowed_view
¶
Learning Time-Series Shapelets
Learning Time-Series Shapelets