Combine or join numpy arrays

Question

How can I join two numpy ndarrays to accomplish the following in a fast way, using optimized numpy, without any looping?

>>> a = np.random.rand(2,2)
>>> a
array([[ 0.09028802,  0.2274419 ],
       [ 0.35402772,  0.87834376]])

>>> b = np.random.rand(2,2)
>>> b
array([[ 0.4776325 ,  0.73690098],
       [ 0.69181444,  0.672248  ]])

>>> c = ???
>>> c
array([[ 0.09028802,  0.2274419, 0.4776325 ,  0.73690098],
       [ 0.09028802,  0.2274419, 0.69181444,  0.672248  ],
       [ 0.35402772,  0.87834376, 0.4776325 ,  0.73690098],
       [ 0.35402772,  0.87834376, 0.69181444,  0.672248  ]])

Answer 1

Not the prettiest, but you could combine hstack, repeat, and tile:

>>> a = np.arange(4).reshape(2,2)
>>> b = a+10
>>> a
array([[0, 1],
       [2, 3]])
>>> b
array([[10, 11],
       [12, 13]])
>>> np.hstack([np.repeat(a,len(a),0),np.tile(b,(len(b),1))])
array([[ 0,  1, 10, 11],
       [ 0,  1, 12, 13],
       [ 2,  3, 10, 11],
       [ 2,  3, 12, 13]])

Or for a 3x3 case:

>>> a = np.arange(9).reshape(3,3)
>>> b = a+10
>>> np.hstack([np.repeat(a,len(a),0),np.tile(b,(len(b),1))])
array([[ 0,  1,  2, 10, 11, 12],
       [ 0,  1,  2, 13, 14, 15],
       [ 0,  1,  2, 16, 17, 18],
       [ 3,  4,  5, 10, 11, 12],
       [ 3,  4,  5, 13, 14, 15],
       [ 3,  4,  5, 16, 17, 18],
       [ 6,  7,  8, 10, 11, 12],
       [ 6,  7,  8, 13, 14, 15],
       [ 6,  7,  8, 16, 17, 18]])