[074d3d]: / examples / preprocessing / interpolate_bad_channels.py

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"""
.. _ex-interpolate-bad-channels:
=============================================
Interpolate bad channels for MEG/EEG channels
=============================================
This example shows how to interpolate bad MEG/EEG channels
- Using spherical splines from :footcite:`PerrinEtAl1989` for EEG data.
- Using field interpolation for MEG and EEG data.
In this example, the bad channels will still be marked as bad.
Only the data in those channels is replaced.
"""
# Authors: Denis A. Engemann <denis.engemann@gmail.com>
# Mainak Jas <mainak.jas@telecom-paristech.fr>
#
# License: BSD-3-Clause
# Copyright the MNE-Python contributors.
# %%
# sphinx_gallery_thumbnail_number = 2
import mne
from mne.datasets import sample
print(__doc__)
data_path = sample.data_path()
meg_path = data_path / "MEG" / "sample"
fname = meg_path / "sample_audvis-ave.fif"
evoked = mne.read_evokeds(fname, condition="Left Auditory", baseline=(None, 0))
# plot with bads
evoked.plot(exclude=[], picks=("grad", "eeg"))
# %%
# Compute interpolation (also works with Raw and Epochs objects)
evoked_interp = evoked.copy().interpolate_bads(reset_bads=False)
evoked_interp.plot(exclude=[], picks=("grad", "eeg"))
# %%
# You can also use minimum-norm for EEG as well as MEG
evoked_interp_mne = evoked.copy().interpolate_bads(
reset_bads=False, method=dict(eeg="MNE"), verbose=True
)
evoked_interp_mne.plot(exclude=[], picks=("grad", "eeg"))
# %%
# References
# ----------
# .. footbibliography::