Mapping Neurons

Fragment Generation

class brainlit.map_neurons.DiffeomorphismAction

Interface for differentiable mappings e.g. transformations that register a brain image to an atlas.

class brainlit.map_neurons.Diffeomorphism_Transform(points, values)

Object that takes a discrete vector field and creates a continuous one which can also give derivative (Jacobian) information. Implements DiffeomorphismAction which is an interface to transform points and tangent vectors.

class brainlit.map_neurons.CloudReg_Transform(vpath: str, Apath: str, direction: str = 'atlas')

Object that can read mat files from CloudReg, and compute transformations on points and Jacobians. Implements DiffeomorphismAction which is an interface to transform points and tangent vectors.

brainlit.map_neurons.diffeo_gen_ara(sigma)

Return random diffeomorphism generated by sampling Gaussian noise then passing through Riemannian exponential.

Parameters

sigma (float) -- standard deviation of noise in microns.

Returns

list of sampled points in spatial domain. np.array: range of diffeomorphism at sampled points.

Return type

List