def _load_om_inverse_head_mat(self, file_name):
"""
Load a previously stored inverse head matrix into an OpenMEEG SymMatrix
object.
"""
inverse_head_martix = om.SymMatrix()
inverse_head_martix.load(file_name)
return inverse_head_martix
v2 = om.Vertex(0., 1., 0., 1) v3 = om.Vertex(0., 0., 1., 2) #print v1.norm() #print (v1 + v2).norm() normal = om.Vect3(1., 0., 0.) t = om.Triangle(v1, v2, v3) hm_file = subject + '.hm' hm.save(hm_file) ssm_file = subject + '.ssm' ssm.save(ssm_file) m1 = om.SymMatrix() m1.load(hm_file) #print m1(0, 0) #print m1.nlin() #print m1.ncol() m2 = om.Matrix() m2.load(ssm_file) #m2.setvalue(2,3,-0.2) # m2(2,3)=-0.2 #print m2(2,3) #print m2(0, 0) #print m2.nlin() #print m2.ncol() ############################################################################### # Numpy interface
###############################################################################
# create a dir for leadfields and tmp
if not op.exists("tmp"):
import os
os.mkdir('tmp')
if not op.exists("leadfields"):
import os
os.mkdir('leadfields')
# Compute Leadfields
gauss_order = 3
use_adaptive_integration = True
dipole_in_cortex = True
if op.exists("tmp/hmi.mat"):
hminv = om.SymMatrix("tmp/hmi.mat")
print("HM inverse loaded from ", "tmp/hmi.mat")
else:
hm = om.HeadMat(geom, gauss_order)
hm.invert()
hm.save("tmp/hmi.mat")
hminv = hm
# hminv = hm.inverse() # to also test the adjoint method: comment the 3
# previous lines, and uncomment this line, and the two others containing
# 'adjoint'
if op.exists("tmp/dsm.mat"):
dsm = om.Matrix("tmp/dsm.mat")
print("DSM loaded from ", "tmp/dsm.mat")
else:
dsm = om.DipSourceMat(geom, dipoles, gauss_order, use_adaptive_integration,