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* upstream/main: Add XDF to "Reading EEG data" tutorial (mne-tools#9289)
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""" | ||
.. _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 <[email protected]> | ||
# Eric Larson <[email protected]> | ||
# | ||
# License: BSD (3-clause) | ||
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import os.path as op | ||
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import pyxdf | ||
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import mne | ||
from mne.datasets import misc | ||
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fname = op.join( | ||
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=12) | ||
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############################################################################### | ||
# References | ||
# ---------- | ||
# .. footbibliography:: |
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seaborn | ||
sphinx_copybutton | ||
https://github.com/mne-tools/mne-bids/archive/main.zip | ||
pyxdf |
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