braindecode.augmentation.functional.channels_shuffle¶
- braindecode.augmentation.functional.channels_shuffle(X, y, p_shuffle, random_state=None)¶
Randomly shuffle channels in EEG data matrix.
Part of the CMSAugment policy proposed in [1]
- Parameters
- Xtorch.Tensor
EEG input example or batch.
- ytorch.Tensor
EEG labels for the example or batch.
- p_shuffle: float | None
Float between 0 and 1 setting the probability of including the channel in the set of permutted channels.
- random_state: int | numpy.random.Generator, optional
Seed to be used to instantiate numpy random number generator instance. Used to sample which channels to shuffle and to carry the shuffle. Defaults to None.
- Returns
- torch.Tensor
Transformed inputs.
- torch.Tensor
Transformed labels.
References
- 1
Saeed, A., Grangier, D., Pietquin, O., & Zeghidour, N. (2020). Learning from Heterogeneous EEG Signals with Differentiable Channel Reordering. arXiv preprint arXiv:2010.13694.