def sphere_el_msh():
fn = os.path.join(os.path.dirname(os.path.realpath(
__file__)), '..', 'testing_files', 'sphere_w_electrodes.msh')
return gmsh.read_msh(fn)
def cube_lr():
fn = os.path.join(os.path.dirname(os.path.realpath(
__file__)), '..', 'testing_files', 'cube.msh')
return gmsh.read_msh(fn)
def sphere3_msh():
return gmsh.read_msh(
os.path.join(os.path.dirname(os.path.realpath(__file__)), '..',
'testing_files', 'sphere3.msh'))
"-ev",
action="store_true",
help="If the NifTI contains a tensor, save only the maximum "
"eigenvector in brain tissue")
parser.add_argument('--version', action='version', version=simnibs_version)
return parser.parse_args(argv)
if __name__ == '__main__':
args = parseArguments(sys.argv[1:])
if not os.path.isfile(args.fn_nifti):
raise IOError('Could not find file: {0}'.format(args.fn_nifti))
if not os.path.isfile(args.fn_mesh):
raise IOError('Could not find file: {0}'.format(args.fn_mesh))
image = nibabel.load(args.fn_nifti)
mesh = gmsh.read_msh(args.fn_mesh)
vol = image.dataobj
affine = image.affine
if args.ev:
logger.info('Creating tensor visualization')
mesh = mesh.crop_mesh([1, 2, 1001, 1002])
cond_list = [c.value for c in cond.standard_cond()]
sigma = cond.cond2elmdata(mesh,
cond_list,
anisotropy_volume=vol,
affine=affine,
aniso_tissues=[1, 2])
views = cond.TensorVisualization(sigma)
mesh.nodedata = []
mesh.elmdata = views
gmsh.write_msh(mesh, args.fn_out)
if len(sys.argv) not in [3, 5]:
print("Incorrect number of arguments")
usage()
sys.exit(1)
# check extension
if os.path.splitext(sys.argv[1])[1] != '.msh':
print('1st argument must have a .msh extension')
sys.exit(1)
if os.path.splitext(sys.argv[2])[1] != '.msh':
print('2nd argument must have a .msh extension')
sys.exit(1)
m = gmsh.read_msh(sys.argv[1])
m.fn = sys.argv[2]
logger.info("Relabeled ventricle regions to CSF and cerebellum regions to WM")
m.elm.tag1[m.elm.tag1 == 6] = 1
m.elm.tag1[m.elm.tag1 == 7] = 3
m.elm.tag2[m.elm.tag2 == 6] = 1
m.elm.tag2[m.elm.tag2 == 7] = 3
logger.info("Fixing surface labeling")
m.fix_surface_labels()
logger.info("Fixing thin tetrahedra")
m.fix_thin_tetrahedra()
logger.info("Fixing tetrahedra node ordering")
m.fix_th_node_ordering()
logger.info("Fixing triangle node ordering")
raise ValueError('.csv-file has to contain all four fiducials')
name = [name[i] for i in p]
coordinates = [list(coordinates[i]) for i in p]
args.Iz = coordinates[name.index('Iz')]
args.Nz = coordinates[name.index('Nz')]
args.LPA = coordinates[name.index('LPA')]
args.RPA = coordinates[name.index('RPA')]
return args
if __name__ == '__main__':
args = parseArguments(sys.argv)
print "Reading Mesh"
mesh = gmsh.read_msh(args.m)
print "Calculating EEG Electrode Positions"
print "Reference points:"
print "Nz:", args.Nz
print "Iz:", args.Iz
print "LPA:", args.LPA
print "RPA:", args.RPA
surface = surface.Surface(mesh, [5, 1005])
eeg = FindPositions(args.Nz, args.Iz, args.LPA, args.RPA, surface,
args.NE_cap)
print "Printing positions to file", args.o + '.csv'
eeg.print2csv(args.o + '.csv')
eeg.print2geo(args.o + '.geo')
# mesh = gmsh.read_msh('almi5-head2-fix.msh')
# surface = surface.Surface(mesh,[5,5000])
# Nz = [8,85.5,-40.5]
parser.add_argument('--out_fill',
help=out_descrip,
type=check_out_fill,
default='nan')
parser.add_argument('--method',
help=type_descrip,
default='linear',
choices=['linear', 'assign'])
parser.add_argument('--version', action='version', version=simnibs_version)
return parser.parse_args(argv)
if __name__ == '__main__':
args = parse_arguments(sys.argv[1:])
msh = gmsh.read_msh(
os.path.abspath(os.path.realpath(os.path.expanduser(args.mesh))))
fn_csv = os.path.expanduser(args.csv)
if args.l is not None:
labels = [int(n) for n in args.l[0].split(',')]
msh = msh.crop_mesh(tags=labels)
points = np.atleast_2d(np.loadtxt(fn_csv, delimiter=',', dtype=float))
if points.shape[1] != 3:
raise IOError('CSV file should have 3 columns')
csv_basename, _ = os.path.splitext(fn_csv)
for ed in msh.elmdata:
c = ed.field_name in ['normJ', 'J']
fn_out = '{0}_{1}.csv'.format(csv_basename, ed.field_name)
logger.info('Interpolating field: {0} and writing to file: {1}'.format(
ed.field_name, fn_out))