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# -*- coding: utf-8 -*-
"""
.. _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
<https://www.urmc.rochester.edu/labs/maddox.aspx>`__.
"""
# Authors: Clemens Brunner <clemens.brunner@gmail.com>
# Eric Larson <larson.eric.d@gmail.com>
#
# License: BSD-3-Clause
# %%
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::
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