Numpy turn hierarchy of matrices into concatenation

I have the following 4 matrices:

>>> a
array([[0., 0.],
       [0., 0.]])
>>> b
array([[1., 1.],
       [1., 1.]])
>>> c
array([[2., 2.],
       [2., 2.]])
>>> d
array([[3., 3.],
       [3., 3.]])

I’m creating another matrix that will contain them:

>>> e = np.array([[a,b], [c,d]])
>>> e.shape
(2, 2, 2, 2)

I want to "cancel the hierarchy" and reshape e into a 4×4 matrix that will look like this:

0 0 1 1
0 0 1 1
2 2 3 3
2 2 3 3

However, when I run e.reshape((4,4)), I get the following matrix:

>>> e.reshape((4,4))
array([[0., 0., 0., 0.],
       [1., 1., 1., 1.],
       [2., 2., 2., 2.],
       [3., 3., 3., 3.]])

Is there a way to reshape my (2,2,2,2) matrix into a (4,4) matrix by cancelling the hierarchy, rather than the the by the indexing I’m currently getting?

>Solution :

Yes you can do it with the .concatenate function of numpy:

np.concatenate(np.concatenate(e, axis=1), axis=1)

There you get the following matrix as result:

array([[0., 0., 1., 1.],
       [0., 0., 1., 1.],
       [2., 2., 3., 3.],
       [2., 2., 3., 3.]])