eelbrain.VolumeSourceSpace

class eelbrain.VolumeSourceSpace(vertices, subject=None, src=None, subjects_dir=None, parc=None, adjacency='custom', name='source', filename='{subject}-{src}-src.fif')

MNE volume source space

Parameters:

  • vertices (ArrayLike) – Integer array with vertex identities of the source space.

  • subject (str) – The mri-subject name.

  • src (str) – The description of the source space (e.g. vol-7).

  • subjects_dir (PathArg) – The path to the FreeSurfer subjects-directory (needed to locate the source space file).

  • parc (str) – Add a parcellation to the source space to identify vertex location.

  • adjacency ('grid' | 'none' | array of int, (n_edges, 2)) – Adjacency between elements. Set to "none" for no connections or "grid" to use adjacency in the sequence of elements as connection. Set to numpy.ndarray to specify custom adjacency. The array should be of shape (n_edges, 2), and each row should specify one connection [i, j] with i < j, with rows sorted in ascending order. If the array’s dtype is uint32, property checks are disabled to improve efficiency.

  • name (str) – Dimension name (default "source").

  • filename (str) – Filename template for the MNE source space file.

See also

SourceSpace

surface-based source space

Methods

adjacency([disconnect_parc])

Create source space adjacency

circular_index(seeds[, extent, name])

Return an index into all vertices closer than extent of a seed

dimindex(arg)

Convert a dimension index to an array index

from_file(subjects_dir, subject, src[, ...])

SourceSpace dimension from MNE source space file

from_mne_source_spaces(source_spaces, src, ...)

SourceSpace dimension from mne.SourceSpaces object

get_source_space([subjects_dir])

Read the corresponding MNE source space

index_for_label(label)

Return the index for a label

index_into_dim(dim)

Index into a subset dimension

intersect(dim[, check_dims])

Create a Source dimension that is the intersection with dim