Add new dataset class using zarr file storage.
#478
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sylvchev
reviewed
Sep 8, 2023
| self, | ||
| train_indices=None, | ||
| test_indices=None, | ||
| ): |
Co-authored-by: Sylvain Chevallier <sylvain.chevallier@universite-paris-saclay.fr>
Co-authored-by: Sylvain Chevallier <sylvain.chevallier@universite-paris-saclay.fr>
Co-authored-by: Sylvain Chevallier <sylvain.chevallier@universite-paris-saclay.fr>
Co-authored-by: Sylvain Chevallier <sylvain.chevallier@universite-paris-saclay.fr>
Co-authored-by: Sylvain Chevallier <sylvain.chevallier@universite-paris-saclay.fr>
Co-authored-by: Sylvain Chevallier <sylvain.chevallier@universite-paris-saclay.fr>
Co-authored-by: Sylvain Chevallier <sylvain.chevallier@universite-paris-saclay.fr>
Codecov Report
@@ Coverage Diff @@
## master #478 +/- ##
==========================================
- Coverage 84.55% 83.46% -1.10%
==========================================
Files 63 63
Lines 4676 4760 +84
==========================================
+ Hits 3954 3973 +19
- Misses 722 787 +65 |
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As we found current solution to be performant enough, closing this for now. |
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Pull Request Description
This PR introduces a new dataset implementation aimed at improving dataset loading speed. Additionally, it includes a BCI decoding example in a Colab notebook for reference: Link to Colab Example.
Notes
Considered Alternatives: During the development process, we explored potential alternatives like numpy.memmap and lmdb. However, we encountered limitations with numpy.memmap, particularly in terms of lacking compression options. LMDB, while efficient, isn't well-suited for lazy loading, useful for querying windows from recordings.
HDF5 vs. Zarr Debate: There's an ongoing debate between HDF5 and Zarr. Both have their respective advantages, but Zarr appears to have more active development. We might also allow users to choose between both options.