def 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 = mesh_io.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)
mesh.nodedata = []
mesh.elmdata = views
mesh_io.write_msh(mesh, args.fn_out)
else:
logger.info('Interpolating data in NifTI file to mesh')
if args.type == 'elements':
ed = mesh_io.ElementData.from_data_grid(mesh, vol, affine,
'from_volume')
mesh.elmdata.append(ed)
if args.type == 'nodes':
nd = mesh_io.NodeData.from_data_grid(mesh, vol, affine,
'from_volume')
mesh.nodedata.append(nd)
mesh_io.write_msh(mesh, args.fn_out)
def test_visualization(self, tensor):
eig_val, eig_vec = np.linalg.eig(tensor)
max_eig = eig_val.argmax()
min_eig = eig_val.argmin()
t = np.tile(tensor, [10, 1, 1])
factor = np.arange(1, 11)
t *= factor[:, None, None]
t = gmsh.ElementData(t.reshape(-1, 9))
fields = cond.TensorVisualization(t, all_compoents=True)
assert np.allclose(fields[0].value / factor[:, None],
eig_val[max_eig] * eig_vec[:, max_eig])
assert np.allclose(fields[2].value / factor[:, None],
eig_val[min_eig] * eig_vec[:, min_eig])
assert np.allclose(fields[3].value / factor,
np.prod(eig_val)**(1.0 / 3.0))
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)
else:
logger.info('Interpolating data in NifTI file to mesh')
ed = gmsh.ElementData.from_data_grid(mesh,
vol,
affine,
'from_volume',
bounds_error=False,
fill_value=0)
mesh.nodedata = []
mesh.elmdata = [ed]
gmsh.write_msh(mesh, args.fn_out)