def __init__(self,
filename=None,
grid=None,
displacement=None,
shape=None):
if filename is not None:
t = nib.load(filename)
self.ndim = t.shape[-1]
self.shape = t.shape[:-1]
data = np.copy(t.get_data(), order='C').astype(np.float)
transpose_axis = (self.ndim, )
for i in xrange(self.ndim):
transpose_axis = transpose_axis + (i, )
data = np.transpose(data, transpose_axis)
self.grid = data + identity_mapping(self.shape)
elif grid is not None:
self.shape = grid.shape[1:]
self.ndim = grid.shape[0]
self.grid = np.copy(grid).astype(np.float)
elif displacement is not None:
self.shape = displacement.shape[1:]
self.ndim = displacement.shape[0]
self.grid = displacement + identity_mapping(self.shape)
elif shape is not None:
self.ndim = len(shape)
self.shape = shape
self.grid = identity_mapping(self.shape)
def init_mappings(self):
self.initial_grid = identity_mapping(self.shape)
self.forward_mappings = np.ones((self.n_step + 1, self.ndim) +
self.shape) * self.initial_grid
self.backward_mappings = np.copy(self.forward_mappings)
# jacobian determinants of forward mappings
self.forward_dets = np.ones((self.n_step + 1, ) + self.shape)
# jacobian determinants of backward mappings
self.backward_dets = np.ones((self.n_step + 1, ) + self.shape)
def init_mappings(self):
self.initial_grid = identity_mapping(self.shape)
self.forward_mappings = np.ones(
(self.n_step + 1, self.ndim) + self.shape) * self.initial_grid
self.backward_mappings = np.copy(self.forward_mappings)
# jacobian determinants of forward mappings
self.forward_dets = np.ones(
(self.n_step + 1,) + self.shape)
# jacobian determinants of backward mappings
self.backward_dets = np.ones(
(self.n_step + 1,) + self.shape)
def save(self, filename, affine=np.identity(4)):
displacement = self.grid - identity_mapping(self.shape)
transpose_axis = ()
for i in xrange(1, self.ndim + 1):
transpose_axis = transpose_axis + (i, )
transpose_axis += (0, )
displacement = np.transpose(displacement, transpose_axis)
nib.save(nib.Nifti1Image(displacement, affine), filename)
print "saved transformation: %s" % filename
def save(self, filename, affine=np.identity(4)):
displacement = self.grid - identity_mapping(self.shape)
transpose_axis = ()
for i in xrange(1, self.ndim + 1):
transpose_axis = transpose_axis + (i,)
transpose_axis += (0,)
displacement = np.transpose(displacement, transpose_axis)
nib.save(nib.Nifti1Image(displacement, affine), filename)
print "saved transformation: %s" % filename
def __init__(self, filename=None, grid=None, displacement=None, shape=None):
if filename is not None:
t = nib.load(filename)
self.ndim = t.shape[-1]
self.shape = t.shape[:-1]
data = np.copy(t.get_data(), order="C").astype(np.float)
transpose_axis = (self.ndim,)
for i in xrange(self.ndim):
transpose_axis = transpose_axis + (i,)
data = np.transpose(data, transpose_axis)
self.grid = data + identity_mapping(self.shape)
elif grid is not None:
self.shape = grid.shape[1:]
self.ndim = grid.shape[0]
self.grid = np.copy(grid).astype(np.float)
elif displacement is not None:
self.shape = displacement.shape[1:]
self.ndim = displacement.shape[0]
self.grid = displacement + identity_mapping(self.shape)
elif shape is not None:
self.ndim = len(shape)
self.shape = shape
self.grid = identity_mapping(self.shape)
