mvpa2.datasets.giftiΒΆ
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.
Functions
anat_surf_to_gifti_image(s[, add_indices, ...]) |
Converts a surface to nibabel’s gifti format. | ||
gifti_dataset(samples[, targets, chunks]) |
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map2gifti(ds[, filename, encoding, surface]) |
Maps data(sets) into a GiftiImage, and optionally saves it to disc. | ||
surf_from_any(s) |
Classes
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. |
