Support for surface-based GIFTI data IO.

This module offers functions to import into PyMVPA surface-based GIFTI data using NiBabel, and export PyMVPA surface-based datasets back into GIFTI.

The current implementation supports data associated with nodes, and node indices for such data. There is no support for meta-data, or non-identity affine transformations.

This module supports node data, i.e. each node on the surface has N values associated with it (with N>=1). Typical examples include time series data and statistical maps.

Optionally, anatomical information (vertices and faces) can be stored, so that FreeSurfer’s mris_convert can read data written by map2gifti.


anat_surf_to_gifti_image(s[, add_indices, ...]) Converts a surface to nibabel’s gifti format.
gifti_dataset(samples[, targets, chunks])
map2gifti(ds[, filename, encoding, surface]) Maps data(sets) into a GiftiImage, and optionally saves it to disc.


AttrDataset(samples[, sa, fa, a]) Generic storage class for datasets with multiple attributes.
Dataset(samples[, sa, fa, a]) Generic storage class for datasets with multiple attributes.
FeatureAttributesCollection([items, length]) Container for attributes of features
SampleAttributesCollection([items, length]) Container for attributes of samples (i.e.