Numpy meshgrid in 3D

Question

Numpy\'s meshgrid is very useful for converting two vectors to a coordinate grid. What is the easiest way to extend this to three dimensions? So given three vectors x, y, an

Answer 1

Numpy (as of 1.8 I think) now supports higher that 2D generation of position grids with meshgrid. One important addition which really helped me is the ability to chose the indexing order (either xy or ij for Cartesian or matrix indexing respectively), which I verified with the following example:

import numpy as np

x_ = np.linspace(0., 1., 10)
y_ = np.linspace(1., 2., 20)
z_ = np.linspace(3., 4., 30)

x, y, z = np.meshgrid(x_, y_, z_, indexing='ij')

assert np.all(x[:,0,0] == x_)
assert np.all(y[0,:,0] == y_)
assert np.all(z[0,0,:] == z_)