Reading an inverse operatorΒΆ

The inverse operator’s source space is shown in 3D.

# Author: Alexandre Gramfort <alexandre.gramfort@telecom-paristech.fr>
#
# License: BSD (3-clause)

from mne.datasets import sample
from mne.minimum_norm import read_inverse_operator

print(__doc__)

data_path = sample.data_path()
fname = data_path
fname += '/MEG/sample/sample_audvis-meg-oct-6-meg-inv.fif'

inv = read_inverse_operator(fname)

print("Method: %s" % inv['methods'])
print("fMRI prior: %s" % inv['fmri_prior'])
print("Number of sources: %s" % inv['nsource'])
print("Number of channels: %s" % inv['nchan'])

Out:

Reading inverse operator decomposition from /home/ubuntu/mne_data/MNE-sample-data/MEG/sample/sample_audvis-meg-oct-6-meg-inv.fif...
    Reading inverse operator info...
    [done]
    Reading inverse operator decomposition...
    [done]
    305 x 305 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
    Noise covariance matrix read.
    22494 x 22494 diagonal covariance (kind = 2) found.
    Source covariance matrix read.
    22494 x 22494 diagonal covariance (kind = 6) found.
    Orientation priors read.
    22494 x 22494 diagonal covariance (kind = 5) found.
    Depth priors read.
    Did not find the desired covariance matrix (kind = 3)
    Reading a source space...
    Computing patch statistics...
    Patch information added...
    Distance information added...
    [done]
    Reading a source space...
    Computing patch statistics...
    Patch information added...
    Distance information added...
    [done]
    2 source spaces read
    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
    Source spaces transformed to the inverse solution coordinate frame
Method: 1
fMRI prior: None
Number of sources: 7498
Number of channels: 305

Show result on 3D source space

lh_points = inv['src'][0]['rr']
lh_faces = inv['src'][0]['use_tris']
rh_points = inv['src'][1]['rr']
rh_faces = inv['src'][1]['use_tris']
from mayavi import mlab  # noqa

mlab.figure(size=(600, 600), bgcolor=(0, 0, 0))
mesh = mlab.triangular_mesh(lh_points[:, 0], lh_points[:, 1], lh_points[:, 2],
                            lh_faces, colormap='RdBu')
mesh.module_manager.scalar_lut_manager.reverse_lut = True

mesh = mlab.triangular_mesh(rh_points[:, 0], rh_points[:, 1], rh_points[:, 2],
                            rh_faces, colormap='RdBu')
mesh.module_manager.scalar_lut_manager.reverse_lut = True
../../_images/sphx_glr_plot_read_inverse_001.png

Total running time of the script: ( 0 minutes 1.018 seconds)

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