numpy.tile(A, reps)
Construct an array by repeating A the number of times given by reps.
If reps has length d, the result will have dimension of max(d,A.ndim).
If A.ndim<d, A is promoted to be d-dimensional by prepending new axes. So a shape (3,) array is promoted to (1, 3) for 2-D replication, or shape (1, 1, 3) for 3-D replication. If this is not the desired behavior, promote A to d-dimensions manually before calling this function.
If A.ndim>d, reps is promoted to A.ndim by prepending 1’s to it. Thus for an A of shape (2, 3, 4, 5), a reps of (2, 2) is treated as (1, 1, 2, 2).
Note : Although tile may be used for broadcasting, it is strongly recommended to use numpy’s broadcasting operations and functions.
Parameters:Aarray_likeThe input array.
repsarray_likeThe number of repetitions of A along each axis.
Returns:cndarrayThe tiled output array.
Examples
>>> importnumpyasnp>>> a=np.array([0,1,2])>>> np.tile(a,2)array([0, 1, 2, 0, 1, 2])>>> np.tile(a,(2,2))array([[0, 1, 2, 0, 1, 2], [0, 1, 2, 0, 1, 2]])>>> np.tile(a,(2,1,2))array([[[0, 1, 2, 0, 1, 2]], [[0, 1, 2, 0, 1, 2]]])>>> b=np.array([[1,2],[3,4]])>>> np.tile(b,2)array([[1, 2, 1, 2], [3, 4, 3, 4]])>>> np.tile(b,(2,1))array([[1, 2], [3, 4], [1, 2], [3, 4]])>>> c=np.array([1,2,3,4])>>> np.tile(c,(4,1))array([[1, 2, 3, 4], [1, 2, 3, 4], [1, 2, 3, 4], [1, 2, 3, 4]])