Create Numpy Grid in correct order - arrays

Question

I have several arrays with points along my x-, y-,...-axes and want to create a grid with all points in it like this:
x = [1, 2, 3]
y = [20, 40, 60, 80]
result = []
for xi in x:
for yi in y:
result.append([xi, yi])
np.array(result)
which gives me
array([[ 1, 20],
[ 1, 40],
[ 1, 60],
[ 1, 80],
[ 2, 20],
[ 2, 40],
[ 2, 60],
[ 2, 80],
[ 3, 20],
[ 3, 40],
[ 3, 60],
[ 3, 80]])
To do this with numpy I found the following code in this question:
np.vstack(np.meshgrid(x, y)).reshape(2, -1).T
But this gives the result in the wrong order:
array([[ 1, 20],
[ 2, 20],
[ 3, 20],
[ 1, 40],
[ 2, 40],
[ 3, 40],
[ 1, 60],
[ 2, 60],
[ 3, 60],
[ 1, 80],
[ 2, 80],
[ 3, 80]])
It goes through the x-values first, then y-values.
I can get around this by using
np.vstack(reversed(np.meshgrid(y, x))).reshape(2, -1).T
but this does not work any more in 3D, where
np.vstack(np.meshgrid(x, y, z)).reshape(3, -1).T
goes through z-values first, then x-values, then y-values.
How can I get the correct order in all dimensions with numpy?

Answer 1

You can specify the matrix indexing ij in np.meshgrid as the indexing parameter to get the reversed order, by default it's the cartesian indexing order xy:
x = [1, 2, 3]
y = [20, 40, 60, 80]
np.stack(np.meshgrid(x, y, indexing='ij'), axis=-1).reshape(-1, 2)
#array([[ 1, 20],
# [ 1, 40],
# [ 1, 60],
# [ 1, 80],
# [ 2, 20],
# [ 2, 40],
# [ 2, 60],
# [ 2, 80],
# [ 3, 20],
# [ 3, 40],
# [ 3, 60],
# [ 3, 80]])
In 3d this could be:
np.stack(np.meshgrid(x, y, z, indexing='ij'), axis=-1).reshape(-1, 3)