Note
Click here to download the full example code
Reading/Writing a noise covariance matrix¶
How to plot a noise covariance matrix.
# Author: Alexandre Gramfort <alexandre.gramfort@inria.fr>
#
# License: BSD (3-clause)
from os import path as op
import mne
from mne.datasets import sample
data_path = sample.data_path()
fname_cov = op.join(data_path, 'MEG', 'sample', 'sample_audvis-cov.fif')
fname_evo = op.join(data_path, 'MEG', 'sample', 'sample_audvis-ave.fif')
cov = mne.read_cov(fname_cov)
print(cov)
ev_info = mne.io.read_info(fname_evo)
Out:
366 x 366 full covariance (kind = 1) found.
Read a total of 4 projection items:
PCA-v1 (1 x 102) active
PCA-v2 (1 x 102) active
PCA-v3 (1 x 102) active
Average EEG reference (1 x 60) active
<Covariance | size : 366 x 366, n_samples : 15972, data : [[ 2.27235589e-23 4.79818505e-24 7.12852747e-25 ... 4.85348042e-18
2.02846360e-18 8.26727393e-18]
[ 4.79818505e-24 5.33468523e-24 1.80261790e-25 ... 2.33583009e-19
-6.93161055e-19 2.35199238e-18]
[ 7.12852747e-25 1.80261790e-25 5.79073915e-26 ... 1.09498615e-19
6.16924072e-21 2.93873875e-19]
...
[ 4.85348042e-18 2.33583009e-19 1.09498615e-19 ... 1.40677185e-11
1.27444183e-11 1.08634620e-11]
[ 2.02846360e-18 -6.93161055e-19 6.16924072e-21 ... 1.27444183e-11
1.59818134e-11 8.51070563e-12]
[ 8.26727393e-18 2.35199238e-18 2.93873875e-19 ... 1.08634620e-11
8.51070563e-12 1.53708918e-11]]>
Read a total of 4 projection items:
PCA-v1 (1 x 102) active
PCA-v2 (1 x 102) active
PCA-v3 (1 x 102) active
Average EEG reference (1 x 60) active
Plot covariance
Total running time of the script: ( 0 minutes 3.444 seconds)
Estimated memory usage: 8 MB