braindecode.samplers.RelativePositioningSampler¶
- class braindecode.samplers.RelativePositioningSampler(metadata, tau_pos, tau_neg, n_examples, tau_max=None, same_rec_neg=True, random_state=None)¶
Sample examples for the relative positioning task from [Banville2020].
Sample examples as tuples of two window indices, with a label indicating whether the windows are close or far, as defined by tau_pos and tau_neg.
- Parameters
- metadatapd.DataFrame
See RecordingSampler.
- tau_posint
Size of the positive context, in samples. A positive pair contains two windows x1 and x2 which are separated by at most tau_pos samples.
- tau_negint
Size of the negative context, in samples. A negative pair contains two windows x1 and x2 which are separated by at least tau_neg samples and at most tau_max samples. Ignored if same_rec_neg is False.
- n_examplesint
Number of pairs to extract.
- tau_maxint | None
See tau_neg.
- same_rec_negbool
If True, sample negative pairs from within the same recording. If False, sample negative pairs from two different recordings.
- random_stateNone | np.RandomState | int
Random state.
References
- Banville2020
Banville, H., Chehab, O., Hyvärinen, A., Engemann, D. A., & Gramfort, A. (2020). Uncovering the structure of clinical EEG signals with self-supervised learning. arXiv preprint arXiv:2007.16104.
Methods
- presample()¶
Presample examples.
Once presampled, the examples are the same from one epoch to another.
