Warning
This project is discontinued in favor of MNE-LSL.
At the moment, MNE-LSL replaces the LSLClient
and does not yet support the FieldTrip buffer.
This is a package for realtime analysis of MEG/EEG data with MNE. The documentation can be found here:
We recommend the Anaconda Python distribution. We require that you use Python 3. You may choose to install mne-realtime via pip.
Besides numpy and scipy (which are included in the standard Anaconda
installation), you will need to install the most recent version of MNE
using the pip tool:
$ pip install -U mne
Then install mne-realtime:
$ pip install https://api.github.com/repos/mne-tools/mne-realtime/zipball/main
These pip commands also work if you want to upgrade if a newer version of
mne-realtime is available. If you do not have administrator privileges on the
computer, use the --user flag with pip.
info = mne.io.read_info(op.join(data_path, 'MEG', 'sample',
'sample_audvis_raw.fif'))
with FieldTripClient(host='localhost', port=1972,
tmax=30, wait_max=5, info=info) as rt_client:
rt_epochs = RtEpochs(rt_client, event_id, tmin, tmax, ...)
rt_epochs.start()
for ev in rt_epochs.iter_evoked():
epoch_data = ev.data
# or alternatively, get last n_samples
rt_epoch = rt_client.get_data_as_epoch(n_samples=500)
continuous_data = rt_epoch.get_data()
The FieldTripClient supports multiple vendors through the FieldTrip buffer.
It can be replaced with other clients such as LSLClient.
See API for a list of clients.
Use the github issue tracker to report bugs.