Deep learning for NeuroImaging in Python.

Note

This page is a reference documentation. It only explains the function signature, and not how to use it. Please refer to the gallery for the big picture.

surfify.utils.sampling.find_rotation_interpol_coefs(vertices, triangles, angles, interpolation='barycentric')[source]¶

Function to compute interpolation coefficient asssociated to a rotation of the provided icosahedron. Used by the ‘rotate_data’ function.

Parameters:

vertices : array (N, 3)

vertices of the icosahedron to reduce.

triangles : array (N, 3)

triangles of the icosahedron to reduce.

angles : 3-uplet

the rotation angles in degrees for each axis (Euler representation).

interpolation : str, default ‘barycentric’

type of interpolation to use: ‘euclidian’ or ‘barycentric’.

Returns:

dict:

neighs: array (N, 3)
indices of the three closest neighbors on the rotated icosahedron for each vertice

weights: array (N, 3)
weights associated to each of these neighbors