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"""
==============================================================
Reading a .dip file form xfit and view with source space in 3D
==============================================================
Here the .dip file was generated with the mne_dipole_fit command.
Detailed unix command is :
$mne_dipole_fit --meas sample_audvis-ave.fif --set 1 --meg --tmin 40 --tmax 95 \
--bmin -200 --bmax 0 --noise sample_audvis-cov.fif \
--bem ../../subjects/sample/bem/sample-5120-bem-sol.fif \
--origin 0:0:40 --mri sample_audvis-meg-oct-6-fwd.fif \
--dip sample_audvis_set1.dip
"""
# Author: Alexandre Gramfort <alexandre.gramfort@telecom-paristech.fr>
#
# License: BSD (3-clause)
print(__doc__)
import numpy as np
import mne
from mne.datasets import sample
data_path = sample.data_path()
fwd_fname = data_path + '/MEG/sample/sample_audvis-meg-oct-6-fwd.fif'
dip_fname = data_path + '/MEG/sample/sample_audvis_set1.dip'
bem_fname = data_path + '/subjects/sample/bem/sample-5120-bem-sol.fif'
brain_surface = mne.read_bem_surfaces(bem_fname, add_geom=True)[0]
points = brain_surface['rr']
faces = brain_surface['tris']
fwd = mne.read_forward_solution(fwd_fname)
src = fwd['src']
# read dipoles
time, pos, amplitude, ori, gof = mne.read_dip(dip_fname)
print("Time (ms): %s" % time)
print("Amplitude (nAm): %s" % amplitude)
print("GOF (%%): %s" % gof)
# only plot those for which GOF is above 50%
pos = pos[gof > 50.]
ori = ori[gof > 50.]
time = time[gof > 50.]
###############################################################################
# Show result on 3D source space
try:
from enthought.mayavi import mlab
except:
from mayavi import mlab
lh_points = src[0]['rr']
lh_faces = src[0]['use_tris']
mlab.figure(size=(600, 600), bgcolor=(1, 1, 1), fgcolor=(0, 0, 0))
# show brain surface after proper coordinate system transformation
points = brain_surface['rr']
faces = brain_surface['tris']
coord_trans = fwd['mri_head_t']['trans']
points = np.dot(coord_trans[:3,:3], points.T).T + coord_trans[:3,-1]
mlab.triangular_mesh(points[:, 0], points[:, 1], points[:, 2],
faces, color=(1, 1, 0), opacity=0.3)
# show one cortical surface
mlab.triangular_mesh(lh_points[:, 0], lh_points[:, 1], lh_points[:, 2],
lh_faces, color=(0.7, ) * 3)
# show dipole as small cones
dipoles = mlab.quiver3d(pos[:,0], pos[:,1], pos[:,2],
ori[:,0], ori[:,1], ori[:,2],
opacity=1., scale_factor=4e-4, scalars=time,
mode='cone')
mlab.colorbar(dipoles, title='Dipole fit time (ms)')
# proper 3D orientation
mlab.get_engine().scenes[0].scene.x_plus_view()
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