[074d3d]: / examples / io / read_xdf.py

Download this file

41 lines (33 with data), 1.2 kB

 1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
"""
.. _ex-read-xdf:
====================
Reading XDF EEG data
====================
Here we read some sample XDF data. Although we do not analyze it here, this
recording is of a short parallel auditory response (pABR) experiment
:footcite:`PolonenkoMaddox2019` and was provided by the `Maddox Lab <Ross Maddox_>`_.
"""
# Authors: Clemens Brunner <clemens.brunner@gmail.com>
# Eric Larson <larson.eric.d@gmail.com>
#
# License: BSD-3-Clause
# Copyright the MNE-Python contributors.
# %%
import pyxdf
import mne
from mne.datasets import misc
fname = misc.data_path() / "xdf" / "sub-P001_ses-S004_task-Default_run-001_eeg_a2.xdf"
streams, header = pyxdf.load_xdf(fname)
data = streams[0]["time_series"].T
assert data.shape[0] == 5 # four raw EEG plus one stim channel
data[:4:2] -= data[1:4:2] # subtract (rereference) to get two bipolar EEG
data = data[::2] # subselect
data[:2] *= 1e-6 / 50 / 2 # uV -> V and preamp gain
sfreq = float(streams[0]["info"]["nominal_srate"][0])
info = mne.create_info(3, sfreq, ["eeg", "eeg", "stim"])
raw = mne.io.RawArray(data, info)
raw.plot(scalings=dict(eeg=100e-6), duration=1, start=14)
# %%
# References
# ----------
# .. footbibliography::