numpy.tile(A, reps)
[source]
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 ddimensional by prepending new axes. So a shape (3,) array is promoted to (1, 3) for 2D replication, or shape (1, 1, 3) for 3D replication. If this is not the desired behavior, promote A
to ddimensions 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: 


Returns: 

See also
repeat
broadcast_to
>>> 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]])
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https://docs.scipy.org/doc/numpy1.17.0/reference/generated/numpy.tile.html