[Numpy-discussion] Create a n-D grid; meshgrid alternative

Hey,

quite often I want to evaluate a function on a grid in a n-D space. What I end up doing (and what I really dislike) looks something like this:

x = np.linspace(0, 5, 20) M1, M2 = np.meshgrid(x, x) X = np.column_stack([M1.flatten(), M2.flatten()]) X.shape # (400, 2)

fancy_function(X)

I don't think I ever used `meshgrid` in any other way. Is there a better way to create such a grid space?

I wrote myself a little helper function:

def gridspace(linspaces): return np.column_stack([space.flatten() for space in np.meshgrid(*linspaces)])

But maybe something like this should be part of numpy?

Best, Stefan