Resizing and stretching a NumPy array

>>> a = numpy.array([[1,5,9],[2,7,3],[8,4,6]])
>>> numpy.kron(a, [[1,1],[1,1]])
array([[1, 1, 5, 5, 9, 9],
       [1, 1, 5, 5, 9, 9],
       [2, 2, 7, 7, 3, 3],
       [2, 2, 7, 7, 3, 3],
       [8, 8, 4, 4, 6, 6],
       [8, 8, 4, 4, 6, 6]])

@KennyTM's answer is very slick, and really works for your case but as an alternative that might offer a bit more flexibility for expanding arrays try np.repeat:

>>> a = np.array([[1, 5, 9],
              [2, 7, 3],
              [8, 4, 6]])

>>> np.repeat(a,2, axis=1)
array([[1, 1, 5, 5, 9, 9],
       [2, 2, 7, 7, 3, 3],
       [8, 8, 4, 4, 6, 6]])

So, this accomplishes repeating along one axis, to get it along multiple axes (as you might want), simply nest the np.repeat calls:

>>> np.repeat(np.repeat(a,2, axis=0), 2, axis=1)
array([[1, 1, 5, 5, 9, 9],
       [1, 1, 5, 5, 9, 9],
       [2, 2, 7, 7, 3, 3],
       [2, 2, 7, 7, 3, 3],
       [8, 8, 4, 4, 6, 6],
       [8, 8, 4, 4, 6, 6]])

You can also vary the number of repeats for any initial row or column. For example, if you wanted two repeats of each row aside from the last row:

>>> np.repeat(a, [2,2,1], axis=0)
array([[1, 5, 9],
       [1, 5, 9],
       [2, 7, 3],
       [2, 7, 3],
       [8, 4, 6]])

Here when the second argument is a list it specifies a row-wise (rows in this case because axis=0) repeats for each row.