def filename2vertices_faces_metadata(fn):
'''Attempts to get meta data based on the filename
Parameters
----------
fn: str
Filename
Returns
-------
meta: tuple
Tuple with two gifti.GiftiMetaData objects for vertices
and faces. If the filename contains exactly one of 'lh', 'rh', or
'mh' then it is assumed to be of left, right or merged hemispheres.
If the filename contains exactly one of 'pial,'smoothwm',
'intermediate',''inflated','sphere','flat', then the geometric
type is set
'''
_, fn = os.path.split(fn)
vertex_map = dict(AnatomicalStructurePrimary=dict(
lh='CortexLeft',
rh='CortexRight',
mh='CortexRightLeft'),
AnatomicalStructureSecondary=dict(
pial='Pial',
smoothwm='GrayWhite',
intermediate='MidThickness'),
GeometricType=dict(
pial='Anatomical',
smoothwm='Anatomical',
intermediate='Anatomical',
inflated='Inflated',
sphere='Spherical',
flat='Flat'))
def just_one(dict_, fn=fn):
vs = [v for k, v in dict_.iteritems() if k in fn]
return vs[0] if len(vs) == 1 else None
v_meta = [gifti.GiftiNVPairs('Name', fn)]
for key, dict_ in vertex_map.iteritems():
v = just_one(dict_)
if not v is None:
v_meta.append(gifti.GiftiNVPairs(key, v))
f_meta = [gifti.GiftiNVPairs('Name', fn)]
# XXX maybe also closed or open topology? that's a bit tricky though
v = gifti.GiftiMetaData()
v.data.extend(v_meta)
f = gifti.GiftiMetaData()
f.data.extend(f_meta)
return v, f
def to_gifti_image(s, add_indices=False, swap_LPI_RAI=False):
'''
Converts a surface to nibabel's gifti format.
Parameters
----------
s: surf
Input surface
add_indices: True or False (default: False)
if True then indices of the nodes are added.
Note: caret may not be able to read these
swap_LPI_RAI: True or False (default: False)
If True then the diagonal elements of the xform matrix
are set to [-1,-1,1,1], otherwise to [1,1,1,1].
Returns
-------
img: gifti.GiftiImage
Surface representated as GiftiImage
'''
vertices = gifti.GiftiDataArray(np.asarray(s.vertices, np.float32))
vertices.intent = gifti.intent_codes.field1['pointset']
vertices.datatype = 16 # this is what gifti likes
if add_indices:
nvertices = s.nvertices
indices = gifti.GiftiDataArray(
np.asarray(np.arange(nvertices), np.int32))
indices.datatype = 8 # this is what gifti likes
indices.coordsys = None # otherwise SUMA might complain
indices.intent = gifti.intent_codes.field1['node index']
faces = gifti.GiftiDataArray(np.asarray(s.faces, np.int32))
faces.intent = gifti.intent_codes.field1['triangle']
faces.datatype = 8 # this is what gifti likes
faces.coordsys = None # otherwise SUMA might complain
# set some fields common to faces and vertices
for arr in (vertices, faces) + ((indices, ) if add_indices else ()):
arr.ind_ord = 1
arr.encoding = 3
arr.endian = 'LittleEndian' # XXX this does not work (see below)
arr.dims = list(arr.data.shape)
if externals.versions['nibabel'] < '2.1':
# in later versions it is a computed property
arr.num_dim = len(arr.dims)
# make the image
meta = gifti.GiftiMetaData()
labeltable = gifti.GiftiLabelTable()
img = gifti.GiftiImage(meta=meta, labeltable=labeltable)
if swap_LPI_RAI:
xform = np.asarray(vertices.coordsys.xform)
xform[0, 0] = -1
xform[1, 1] = -1
vertices.coordsys.xform = xform
if add_indices:
img.add_gifti_data_array(indices)
img.add_gifti_data_array(vertices)
img.add_gifti_data_array(faces)
return img
