Alexandre Gramfort

I lean on the same side here... > Message ID: ***@***.***> >

hi @CurryKaiser, yes can you share a super tiny file eg 5MB so we can use it for testing when integrating this code? thanks

thanks. Can you clarify what are files .cdt.dpo vs .cdt.dpa? I only see issues with the file MEG_A + MEG_B + Oth.cdt as it has a .dpo file (no .dpa)?...

yes we could base our reader on your code. For packaging reasons, we would need to have your code in a released package in pypi and conda (although we can...

here are the rendered doc pages: https://26474-1301584-gh.circle-artifacts.com/0/dev/auto_tutorials/machine-learning/plot_sensors_decoding.html https://26474-1301584-gh.circle-artifacts.com/0/dev/auto_examples/decoding/plot_ssd_spatial_filters.html#sphx-glr-auto-examples-decoding-plot-ssd-spatial-filters-py https://26474-1301584-gh.circle-artifacts.com/0/dev/auto_examples/decoding/plot_decoding_ssd_csp_eeg.html#sphx-glr-auto-examples-decoding-plot-decoding-ssd-csp-eeg-py I don't know why there is no plot in the second one. I also find that the error bars are quite...

sorry I did not look carefully but it is enough to have these 45 trials to make your point here experimentally? I am convinced in theory >

I am not sure I agree with the statements in this tutorial. When I see https://26588-1301584-gh.circle-artifacts.com/0/dev/_images/sphx_glr_plot_decoding_ssd_csp_eeg_001.png I see that SSD improves a bit when you overfit by using the full...

> > I totally understand your concern @agramfort > , which in fact are my concerns too. > Although I personally think that all pre-processing methods should be > considered...

if we run this for more subjects and average can it be even clearer? I find it still not super obvious sorry >

yes exactly like this figure. I see it's obtained by averaging 80 subjects. Let's see if you can replicate this figure without limitation of computation time on your machine and...