mvpa2.misc.surfing.volsurf.VolSurf

class mvpa2.misc.surfing.volsurf.VolSurf(vg, white, pial, intermediate=None)

Associates a volume geometry with two surfaces (pial and white).

Methods

coordinates_to_grey_distance_mm(nodes, xyz)	Computes the grey position of coordinates in metric units
surf_project_nodewise(xyz)	Projects coordinates on lines connecting pial and white matter.
surf_project_weights(nodes, xyz)	Computes relative position of xyz on lines from pial to white matter.
surf_project_weights_nodewise(xyz)	Computes relative position of xyz on lines from pial to white matter.
surf_unproject_weights_nodewise(weights)	Maps relative positions in grey matter to coordinates

Parameters:

volgeom: volgeom.VolGeom :

Volume geometry

white: surf.Surface :

Surface representing white-grey matter boundary

pial: surf.Surface :

Surface representing pial-grey matter boundary

intermediate: surf.Surface (default: None). :

Surface representing intermediate surface. If omitted it is the node-wise average of white and pial. This parameter is usually ignored, except when used in a VolSurfMinimalLowresMapping.

Notes

‘pial’ and ‘white’ should have the same topology.

Methods

coordinates_to_grey_distance_mm(nodes, xyz)	Computes the grey position of coordinates in metric units
surf_project_nodewise(xyz)	Projects coordinates on lines connecting pial and white matter.
surf_project_weights(nodes, xyz)	Computes relative position of xyz on lines from pial to white matter.
surf_project_weights_nodewise(xyz)	Computes relative position of xyz on lines from pial to white matter.
surf_unproject_weights_nodewise(weights)	Maps relative positions in grey matter to coordinates

coordinates_to_grey_distance_mm(nodes, xyz)

Computes the grey position of coordinates in metric units

Parameters:

nodes: int or np.ndarray :

Single index, or Q indices of nodes relative to which the coordinates are computed. If True then grey distances are computed node-wise.

xyz: Px3 array with coordinates, assuming ‘white’ and ‘pial’ surfaces :

have P nodes each.

Returns:

grey_position_mm: np.ndarray :

Vector with P elements (if type(nodes) is int) or PxQ array (with type(nodes) is np.ndarray) containing the signed ‘distance’ to the grey matter. Values of zero indicate a node is within the grey matter. Negative values indicate that a node is ‘below’ the white matter (i.e. farther from the pial surface than the white surface), whereas Positive values indicate that a node is ‘above’ the pial matter.

intermediate_surface

Returns the node-wise average of the pial and white surface

Returns:intermediate: surf.Surface :

pial_surface

Returns the pial surface

Returns:pial: surf.Surface :

surf_project_nodewise(xyz)

Projects coordinates on lines connecting pial and white matter.

Parameters:

xyz: numpy.ndarray (float) :

Px3 array with coordinates, assuming ‘white’ and ‘pial’ surfaces have P nodes each

Returns:

xyz_proj: numpy.ndarray (float) :

Px3 array with coordinates the constraints that xyz_proj[i,:] lies on the line connecting node ‘i’ on the white and pial surface, and that xyz_proj[i,:] is closest to xyz[i,:] of all points on this line.

surf_project_weights(nodes, xyz)

Computes relative position of xyz on lines from pial to white matter.

Parameters:

nodes: True or np.ndarray or int :

Q node indices for each the weights are computed. If True, then weights are computed node-wise, otherwise separately for each node.

xyz: numpy.ndarray (float) :

Px3 array with coordinates. IF nodes is True then the ‘white’ and ‘pial’ surfaces must have P nodes each.

Returns:

weights: numpy.ndarray (float) :

If nodes is True, P values of relative grey matter positions (0=white surface and 1=pial surface), where the i-th element are the projection weights for xyz[i] relative to the i-th node in the pial and white surface. Otherwise it returns an PxQ array with the projected weights for each node. If nodes is an int, then a P-vector is returned

surf_project_weights_nodewise(xyz)

Computes relative position of xyz on lines from pial to white matter.

Parameters:

xyz: numpy.ndarray (float) :

Px3 array with coordinates, assuming ‘white’ and ‘pial’ surfaces have P nodes each.

Returns:

weights: numpy.ndarray (float) :

If nodes is True, P values of relative grey matter positions (0=white surface and 1=pial surface), where the i-th element are the projection weights for xyz[i] relative to the i-th node in the pial and white surface. Otherwise it returns an PxQ array with the projected weights for each node. If nodes is an int, then a P-vector is returned

surf_unproject_weights_nodewise(weights)

Maps relative positions in grey matter to coordinates

Parameters:

weights: numpy.ndarray (float) :

P values of relative grey matter positions, where 0=white surface and 1=pial surface.

Returns:

xyz: numpy.ndarray (float) :

Px3 array with coordinates, assuming ‘white’ and ‘pial’ surfaces have P nodes each.

volgeom

Returns the volume geometry

Returns:vg: volgeom.VolGeom :

white_surface

Returns the white surface

Returns:white: surf.Surface :