Open Surya-Teja-Menta opened 2 years ago
Hi @Surya-Teja-Menta, have you managed to figure this out? I have converted my data into numpy arrays to run it through my preprocessing pipeline and would like to create a modelate instance without creating a load_data instance, otherwise I will have to convert the numpy files back into edf files. Thanks!
Hi, @Surya-Teja-Menta if the .eeg file corresponds to a brain vision file then simply provide the .vhdr file. Otherwise, you can convert to .edf and import the data.
@melissafasol importing from numpy could easily be done as data is handled with mne under the hood. Have a look at this tutorial if you are not sure how to do that.
########### Exemplary step by step example (you would need to adjust to your needs!):
Create a mne raw data structure from your numpy
raw = mne.io.RawArray(numpy_data, info)
Initialize a eegraph object:
G = eegraph.Graph()
Hand over the mne object to eegraph:
G.data = raw
Set a montage:
e.g.: G.data.set_montage("standard_1020")
Hand over the channel names to eegraph:
G.ch_names = raw.info['ch_names']
How to load .eeg files in python instead of .edf files. or else any function to convert .eeg to .edf format