mvpa2.misc.surfing.queryengine.SurfaceVoxelsQueryEngine

Inheritance diagram of SurfaceVoxelsQueryEngine

class mvpa2.misc.surfing.queryengine.SurfaceVoxelsQueryEngine(voxsel, space='voxel_indices', add_fa=None, fallback_euclidean_distance=True)

Query-engine that maps center voxels (indexed by feature ids) to indices of features (voxels) that are near each center voxel.

In a typical use case such an instance is generated using the function ‘disc_surface_queryengine’ with the output_space=’voxels’ argument

Methods

feature_id2linear_voxel_ids(feature_id)
feature_id2nearest_vertex_id(feature_id[, ...]) Computes the index of the vertex nearest to a given voxel.
get_masked_nifti_image() Returns a nifti image indicating which voxels are included in one or more searchlights.
linear_voxel_id2feature_id(linear_voxel_id)
query(**kwargs)
query_byid(feature_id)
train(ds)
untrain()
vertex_id2nearest_feature_id(vertex_id) Computes the index of the voxel nearest to a given vertex.

Makes a new SurfaceVoxelsQueryEngine

Parameters:

voxsel: volume_mask_dict.VolumeMaskDictionary :

mapping from center node indices to indices of voxels in a searchlight

space: str (default: ‘voxel_indices’) :

defines by which space voxels are indexed.

add_fa: list of str :

additional feature attributes that should be returned when this instance is called with a center node id.

fallback_euclidean_distance: bool (default: True) :

If True then every feature id will have voxels associated with it. That means that the number of self.ids is then equal to the number of features as the input dataset. If False, only feature ids that are selected by at least one searchlight are used. The number of self.ids is then equal to the number of voxels that are selected by at least one searchlight.

Methods

feature_id2linear_voxel_ids(feature_id)
feature_id2nearest_vertex_id(feature_id[, ...]) Computes the index of the vertex nearest to a given voxel.
get_masked_nifti_image() Returns a nifti image indicating which voxels are included in one or more searchlights.
linear_voxel_id2feature_id(linear_voxel_id)
query(**kwargs)
query_byid(feature_id)
train(ds)
untrain()
vertex_id2nearest_feature_id(vertex_id) Computes the index of the voxel nearest to a given vertex.
ids
query_byid(feature_id)
train(ds)
untrain()

NeuroDebian

NITRC-listed