i am processing a eeg signal acquired by showing 10 image of each of 40 classes. i want to label the signals converted to epochs to their corresponding class labels.
i extracted events data as:
raw = mne.io.read_raw_bdf(raw_file, preload =True)
events=mne.find_events(raw, stim_channel = None, initial_event = True, consecutive='increasing',
output='step',uint_cast=True, verbose=None)
The events data is as
array([[ 0, 0, 65280],
[ 3085, 65280, 65533],
[ 44751, 65280, 65281],
...,
[4962462, 65280, 65281],
[4974818, 65280, 65281],
[5021696, 65280, 0]], dtype=int64)
The third col of event data is the event code, which is same 65281 for all 400 images, except the first 2 event code[65280, 65533] being the initial 10 second pause.
event_dict = []
for event, class_label in zip(events, class_labels):
event_dict.append((class_label,event[2]))
print(event_dict)
The event_dict contains data
[('initial event', 65280),
('initial event', 65533),
('airliner', 65281),
('watch', 65281),
('folding chair', 65281),
('radio telescope', 65281),
('jack-o-lantern', 65281),
I am plotting the epochs to view the class labelling
epochs.plot(n_channels=10, events=events, event_id=event_dict_as_dict)
The epochs are plotted but the label from the second last last 'Pool table is used only.[1]][1]
[1]: https://i.stack.imgur.com/LyO0k.jpg
the epochs are not correctly labelled