nilearn.experimental: Experimental Modules

The nilearn.experimental module provides importable modules that enable the use of experimental features.

The features and estimators that are experimental aren’t subject to deprecation cycles. Use them at your own risks!

nilearn.experimental.surface

Classes:

FileMesh(file_path)	A surface mesh stored in a Gifti or Freesurfer file.
InMemoryMesh(coordinates, faces)	A surface mesh stored as in-memory numpy arrays.
Mesh()	A surface mesh, having vertex coordinates and faces(triangles).
PolyMesh
SurfaceImage(mesh, data)	Surface image, usually containing meshes & data for both hemispheres.
SurfaceLabelsMasker(labels_img[, label_names])	Extract data from a SurfaceImage, averaging over atlas regions.
SurfaceMasker([mask_img])	Extract data from a SurfaceImage.

Functions:

fetch_destrieux()	Load Destrieux surface atlas into a surface object.
fetch_nki([n_subjects])	Load NKI enhanced surface data into a surface object.
load_fsaverage([mesh_name])	Load several fsaverage mesh types for both hemispheres.