are you here?
can you have a look @robintibor @sliwy
https://gist.github.com/gemeinl/1220413cb4418a94c48b71c5014bb390
https://gist.github.com/gemeinl/1220413cb4418a94c48b71c5014bb390
i wonder if you could reverse the order in that tutorial, like first show the last part saying this is how you get a braindecode-dataset from this mne, and then saying ok now let's look into each step in detail
also, if we already had mne epochs, would there also be a clear way atm? is this not intended atm? how is it?
but ya also @sliwy maybe you can say how you find it in terms of understand dataset structure? it seems quite helpful to me!
I also added my current naming preference here: braindecode/braindecode#59
@gemeinl I really like the dataset tutorial, great thing! I agree with @robintibor to start with the last cell - just quickly show how to read mne data. It looks simple and straightforward, you do not have to spend time to figure out where to start and what you need. It may be the first part - basic and usual application. The second part may describe more advanced usage e.g. with splitting (looks really interesting, I didn't know we have this functionality) and any other cool stuff is inside braindecode.
It really helps a lot in understanding the dataset structures!
also, if we already had mne epochs, would there also be a clear way atm? is this not intended atm? how is it?
I will see to this next. It could become a bit more tricky, though. The WindowsDataset gives x, y, ind, where y and ind are read from the metadata pandas.DataFrame from the mne.Epochs objects. If it is not there, you have to manually add it. I have never tried it, will see how it can be done.
like dataset = create_from_X_y(X,y)
with dataset being windows dataset
such a function does not exsist yet, but i think this would be the way to go: https://gist.github.com/gemeinl/1220413cb4418a94c48b71c5014bb390#file-braindecode_xy_data_example-ipynb
Both examples i now sent would benefit from removing pandas import, i believe. We could do this by changing
description argument of BaseDataset from pandas.Series to dict and cast it internally. What do you think abou this?
x y looks great, would be super to make it into single function
did anyone of you touch something to circleci or github config https://app.circleci.com/pipelines/github/braindecode/braindecode/450/workflows/545362fa-2038-4537-b85b-a1548bbec69a/jobs/535 ? @robintibor ?
deploy of docs failed multiple times with some error about read-only SSH key, so I added a User key under https://app.circleci.com/settings/project/github/braindecode/braindecode/ssh?return-to=https%3A%2F%2Fapp.circleci.com%2Fpipelines%2Fgithub%2Fbraindecode%2Fbraindecode @agramfort
here circleci code is indeed read-only, I don't know if that is a problem: https://github.com/braindecode/braindecode/settings/keys
if you asked about touching something before, them I am not aware of it. the screenshot above shows something visible under https://github.com/braindecode/braindecode/settings/keys , which I do not know why it happened
one needs to have read write keys in sync between circle ci and github
I also reran the one you linked above and it succeeded now https://app.circleci.com/pipelines/github/braindecode/braindecode/450/workflows/24366b0c-fee0-4663-bfc1-90023ee4326c/jobs/544
Hi all, we are a team of students in Singapore investigating the relationship between environment, physiological measurement and electroencephalography. Currently, we are using deep learning to connect EEG measurement and other data types. We currently intend to use EEG data as input for our regression model to predict other measurements. As we have never used deep learning on EEG data before we do not know how to start. We are using OpenBCI cyton so the EEG data that we stored are in txt file – which can be made into numpy array. We are intending to use Braindecode, we did manage to store our data as MNE raw arrays and after reading the documentation, we managed to create a BaseConcatDataset (we are not sure if we set the parameters for create_from_X_y correctly, I am still not sure on the meaning of window in the structure). After that we are not what preprocessing method and regression parameters to use. Thank you very much for your help.
Maybe this tutorial can help you a bit? https://colab.research.google.com/drive/1B-5K7dNyfyu-UIVFp3A1BvgQGkZmLWrg#scrollTo=6cpFJHF0CGYS
AttributeError Traceback (most recent call last)
<ipython-input-11-596ca18789b8> in <module>()
112 )
113
--> 114 regressor.fit(train_set, y=None, epochs=n_epochs)
6 frames
/content/notebooks/braindecode/util.py in iter(self)
364 x = x.type(torch.float32)
365 if self.is_regression:
--> 366 y = y.type(torch.float32)
367 else:
368 y = y.type(torch.int64)
AttributeError: 'list' object has no attribute 'type'
Thank you for your help
In the end I really needed the permission in your folk. Thank you!