roll_window_size = 6
# rolling means generator
- dataset_size = disk_days_attrs.shape[0] - roll_window_size + 1
- gen = (disk_days_attrs[i: i + roll_window_size, ...].mean(axis=0)
- for i in range(dataset_size))
+ dataset_size = disk_days_attrs.shape[0] - roll_window_size + 1 # type:ignore
+ gen = (disk_days_attrs[i: i + roll_window_size, ...].mean(axis=0) # type:ignore
+ for i in range(dataset_size)) # type:ignore
means = np.vstack(gen) # type: ignore
# rolling stds generator
- gen = (disk_days_attrs[i: i + roll_window_size, ...].std(axis=0, ddof=1)
- for i in range(dataset_size))
+ gen = (disk_days_attrs[i: i + roll_window_size, ...].std(axis=0, ddof=1) # type: ignore
+ for i in range(dataset_size)) # type:ignore
stds = np.vstack(gen) # type: ignore
# coefficient of variation