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52 lines (38 loc) · 1.29 KB
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# -*- coding: utf-8 -*-
"""
.. _ex-shift-evoked:
==================================
Shifting time-scale in evoked data
==================================
"""
# Author: Mainak Jas <mainak@neuro.hut.fi>
#
# License: BSD-3-Clause
# %%
import matplotlib.pyplot as plt
import mne
from mne.viz import tight_layout
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'
# Reading evoked data
condition = 'Left Auditory'
evoked = mne.read_evokeds(fname, condition=condition, baseline=(None, 0),
proj=True)
ch_names = evoked.info['ch_names']
picks = mne.pick_channels(ch_names=ch_names, include=["MEG 2332"])
# Create subplots
f, (ax1, ax2, ax3) = plt.subplots(3)
evoked.plot(exclude=[], picks=picks, axes=ax1,
titles=dict(grad='Before time shifting'), time_unit='s')
# Apply relative time-shift of 500 ms
evoked.shift_time(0.5, relative=True)
evoked.plot(exclude=[], picks=picks, axes=ax2,
titles=dict(grad='Relative shift: 500 ms'), time_unit='s')
# Apply absolute time-shift of 500 ms
evoked.shift_time(0.5, relative=False)
evoked.plot(exclude=[], picks=picks, axes=ax3,
titles=dict(grad='Absolute shift: 500 ms'), time_unit='s')
tight_layout()