Braindecode and Moabb dataset

[bruAristimunha]

The following datasets are not working with the braindecode loader:

• <class 'moabb.datasets.epfl.EPFLP300'>
• <class 'moabb.datasets.hinss2021.Hinss2021'>
• <class 'moabb.datasets.huebner_llp.Huebner2017'>
• <class 'moabb.datasets.huebner_llp.Huebner2018'>
• <class 'moabb.datasets.schirrmeister2017.Schirrmeister2017'>

[bruAristimunha]

• <class 'moabb.datasets.epfl.EPFLP300'>
• <class 'moabb.datasets.mpi_mi.GrosseWentrup2009'>
• <class 'moabb.datasets.hinss2021.Hinss2021'>
• <class 'moabb.datasets.huebner_llp.Huebner2017'>
• <class 'moabb.datasets.huebner_llp.Huebner2018'>
• <class 'moabb.datasets.liu2024.Liu2024'>
• <class 'moabb.datasets.mpi_mi.MunichMI'>
• <class 'moabb.datasets.upper_limb.Ofner2017'>
• <class 'moabb.datasets.physionet_mi.PhysionetMI'>
• <class 'moabb.datasets.schirrmeister2017.Schirrmeister2017'>
• <class 'moabb.datasets.sosulski2019.Sosulski2019'>
• <class 'moabb.datasets.Zhou2016.Zhou2016'>

[bruAristimunha]

Less that I expected :)

[bruAristimunha]

The issue with EPFLP300 is the irregular size of events in the raw data in the last events. Initially, I thought it was the case where drop_bad would solve it, but no. In some sessions, we have different values.

I tried to solve it on the braindecode side for half an hour, but I couldn't. I'll come back to this later, but on the moabb side.

Same issue with Hinss2021:

assert np.all(this_trial_sizes == window_size_samples), (

AssertionError: All trial sizes should be the same if you do not supply a window size.

[bruAristimunha]

Huebner2017 has an issue too.