def map2gifti(ds, filename=None, encoding='GIFTI_ENCODING_B64GZ'):
"""Maps data(sets) into a GiftiImage, and optionally saves it to disc.
Parameters
----------
ds : AttrDataset or numpy.ndarray
The data to be mapepd
filename : basestring or None, optional
Filename to which the GiftiImage is stored
encoding : "ASCII" or "Base64Binary" or "GZipBase64Binary", optional
Encoding format of data
Returns
-------
img : GiftiImage
dataset contents represented in GiftiImage
"""
darrays = []
if isinstance(ds, np.ndarray):
samples = ds
elif isinstance(ds, AttrDataset):
samples = ds.samples
_warn_if_fmri_dataset(ds)
else:
raise TypeError('first argument must be AttrDataset or numpy.ndarray')
[nsamples, nfeatures] = samples.shape
def _get_attribute_value(ds, attr_name, keys_):
if isinstance(ds, np.ndarray):
# no attributes
return None
attr_collection = ds.__dict__.get(attr_name)
if isinstance(keys_, basestring):
keys_ = (keys_, )
for key in keys_:
if key in attr_collection:
return attr_collection[key].value
return None
def _build_array(data, intent, encoding=encoding):
return gifti.GiftiDataArray.from_array(data, intent, encoding=encoding)
node_indices_labels = ('node_indices', 'center_ids', 'ids', 'roi_ids')
node_indices = _get_attribute_value(ds, 'fa', node_indices_labels)
if node_indices is not None:
darray = _build_array(node_indices, 'NIFTI_INTENT_NODE_INDEX')
darrays.append(darray)
intents = _get_attribute_value(ds, 'sa', 'intents')
for i, sample in enumerate(samples):
intent = 'NIFTI_INTENT_NONE' if intents is None else intents[i]
darray = _build_array(sample, intent)
darrays.append(darray)
image = gifti.GiftiImage(darrays=darrays)
if filename is not None:
giftiio.write(image, filename)
return image
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
def map2gifti2(ds,
filename=None,
encoding='GIFTI_ENCODING_B64GZ',
surface=None,
vertices=None):
"""Maps data(sets) into a GiftiImage, and optionally saves it to disc.
Parameters
----------
ds : AttrDataset or numpy.ndarray
The data to be mapepd
filename : basestring or None, optional
Filename to which the GiftiImage is stored
encoding : "ASCII" or "Base64Binary" or "GZipBase64Binary", optional
Encoding format of data
surface : mvpa2.surf.nibabel.surf.Surface or str, optional
Optional anatomical Surface object, or filename of anatomical surface
file, to be stored together with the data. This should allow
FreeSurfer's mris_convert to read files written by this function
Returns
-------
img : GiftiImage
dataset contents represented in GiftiImage
"""
darrays = []
if isinstance(ds, np.ndarray):
samples = ds
elif isinstance(ds, AttrDataset):
samples = ds.samples
_warn_if_fmri_dataset(ds)
else:
raise TypeError('first argument must be AttrDataset or numpy.ndarray')
[nsamples, nfeatures] = samples.shape
def _get_attribute_value(ds, attr_name, keys_):
if isinstance(ds, np.ndarray):
# no attributes
return None
attr_collection = ds.__dict__.get(attr_name)
if isinstance(keys_, basestring):
keys_ = (keys_, )
for key in keys_:
if key in attr_collection:
return attr_collection[key].value
return None
def _build_array(data, intent, encoding=encoding):
is_integer = intent == 'NIFTI_INTENT_NODE_INDEX'
dtype = np.int32 if is_integer else np.float32
arr = gifti.GiftiDataArray(data.astype(dtype),
intent,
encoding=encoding)
# Setting the coordsys argument the constructor would set the matrix
# to the 4x4 identity matrix, which is not desired. Instead the
# coordsys is explicitly set to None afterwards
arr.coordsys = None
return arr
node_indices_labels = ('node_indices', 'center_ids', 'ids', 'roi_ids')
node_indices = _get_attribute_value(ds, 'fa', node_indices_labels)
if vertices is not None:
values = np.zeros((samples.shape[0], vertices))
for i, sample in enumerate(samples):
values[i, node_indices] = sample
#darray = _build_array(np.arange(vertices), 'NIFTI_INTENT_NODE_INDEX')
#darrays.append(darray)
samples = values
else:
if node_indices is not None:
darray = _build_array(node_indices, 'NIFTI_INTENT_NODE_INDEX')
darrays.append(darray)
intents = _get_attribute_value(ds, 'sa', 'intents')
for i, sample in enumerate(samples):
intent = 'NIFTI_INTENT_NONE' if intents is None else intents[i]
darray = _build_array(sample, intent)
darrays.append(darray)
# if there is a surface, add it
if surface is not None:
surface_object = surf_from_any(surface, )
anat_image = anat_surf_to_gifti_image(surface_object,
add_indices=False)
for darray in anat_image.darrays:
darrays.append(darray)
image = gifti.GiftiImage(darrays=darrays)
if filename is not None:
nb.save(image, filename)
return (image)