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algorithms.registration.grid_transform

Module: algorithms.registration.grid_transform

Inheritance diagram for nipy.algorithms.registration.grid_transform:

Classes

GridTransform

class nipy.algorithms.registration.grid_transform.GridTransform(image, data, affine=None)

Bases: object

__init__(image, data, affine=None)

image : a nipy-like image

data : a 5d array representing the deformation modes, first three dimensions should represent space, next dimension should be the mode index, last dimension should be 3.

IJK()

Returns an array of grid coordinates that is aligned with the image data array in the sense that:

arr[i,j,k] corresponds to self.IJK()[i,j,k,:]

affine
as_displacements()

Return the displacements sampled on the grid. Displacements are matched with the array output by IJK.

param
shape

SplineTransform

class nipy.algorithms.registration.grid_transform.SplineTransform(image, control_points, sigma, grid_coords=False, affine=None)

Bases: nipy.algorithms.registration.grid_transform.GridTransform

__init__(image, control_points, sigma, grid_coords=False, affine=None)

control_points: a Nx3 array of world coordinates

if grid_coords is True, both control_points and sigma are interpreted in voxel coordinates.

IJK()

Returns an array of grid coordinates that is aligned with the image data array in the sense that:

arr[i,j,k] corresponds to self.IJK()[i,j,k,:]

affine
as_displacements()
param
shape