Fast interpolation of regularly sampled 3D data with different intervals in x,y, and z

Question

I have some volumetric imaging data consisting of values sampled on a regular grid in x,y,z, but with a non-cubic voxel shape (the space between adjacent points in z is grea

Answer 1

I created the regulargrid package (https://pypi.python.org/pypi/regulargrid/, source at https://github.com/JohannesBuchner/regulargrid)

It provides support for n-dimensional Cartesian grids (as needed here) via the very fast scipy.ndimage.map_coordinates for arbitrary coordinate scales.

Also see this answer: Fast interpolation of grid data