Sequential

class dpeeg.transforms.Sequential(*transforms: Transforms)

A sequential container.

Transforms will be added to it in the order they are passed.

Parameters:

transforms (sequential of Transforms) – Sequential of transforms to compose.

Examples

If you have multiple transforms that are processed sequentiallt, you can do like:

>>> transforms.Sequential(
...     transforms.Unsqueeze(),
...     transforms.Crop(2, 5),
... )
>>> trans
Sequential(
 (0): Unsqueeze(key=edata, dim=1)
 (1): Crop(tmin=2, tmax=5, include_tmax=False)
)

>>> eegdata = dpeeg.EEGData(edata=np.random.randn(16, 3, 10),
...                         label=np.random.randint(0, 3, 16))
>>> trans(eegdata, verbose=False)
[edata=(16, 1, 3, 3), label=(16,)]