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%matplotlib inline

Plot real-time epoch data with LSL client

This example demonstrates how to use the LSL client to plot real-time collection of event data from an LSL stream. For the purposes of demo, a mock LSL stream is constructed. You can replace this with the stream of your choice by changing the host id to the desired stream.



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# Author: Teon Brooks <teon.brooks@gmail.com>
#
# License: BSD (3-clause)
import matplotlib.pyplot as plt

from mne.datasets import sample
from mne.io import read_raw_fif

from mne_realtime import LSLClient, MockLSLStream

print(__doc__)

# this is the host id that identifies your stream on LSL
host = 'mne_stream'
# this is the max wait time in seconds until client connection
wait_max = 5


# Load a file to stream raw data
data_path = sample.data_path()
raw_fname = data_path + '/MEG/sample/sample_audvis_filt-0-40_raw.fif'
raw = read_raw_fif(raw_fname).crop(0, 30).load_data().pick('eeg')

# For this example, let's use the mock LSL stream.
_, ax = plt.subplots(1)
n_epochs = 5
with MockLSLStream(host, raw, 'eeg'):
    with LSLClient(info=raw.info, host=host, wait_max=wait_max) as client:
        client_info = client.get_measurement_info()
        sfreq = int(client_info['sfreq'])

        # let's observe ten seconds of data
        for ii in range(n_epochs):
            print('Got epoch %d/%d' % (ii + 1, n_epochs))
            plt.cla()
            epoch = client.get_data_as_epoch(n_samples=sfreq)
            epoch.average().plot(axes=ax)
            plt.pause(1.)
        plt.draw()
print('Streams closed')