Python--numpy中的tile()函数

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 pre-pending 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

A : array_like

reps : array_like

Returns

c : ndarray

See Also

repeat : Repeat elements of an array. broadcast_to : Broadcast an array to a new shape

Examples

a = np.array([0, 1, 2])

np.tile(a, 2)     /*列（水平方向）重复2次 */

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

这里的列可以理解为a向右复制，同理，行理解为a向下复制。复制次数包括本身（即2为复制1次，加上原来的为2个）。

当参数仅1个时候（如上），默认水平方向复制。

当参数为2个时候（如下），则第一个表示行（垂直方向）复制，第二个表示会列（水平方向）复制。

np.tile(a, (3, 2))    /*行（垂直方向）重复3次，列（水平方向）重复2次*/

array([[0, 1, 2, 0, 1, 2],

          [0, 1, 2, 0, 1, 2],

np.tile(a, (2, 1, 2))  /*这个目前也不太理解，应该是超平面，大于三维时候*/

array([[[0, 1, 2, 0, 1, 2]],

b = np.array([[1, 2], [3, 4]])

np.tile(b, 2)

array([[1, 2, 1, 2],

np.tile(b, (2, 1))

array([[1, 2],

c = np.array([1,2,3,4])

np.tile(c,(4,1))

array([[1, 2, 3, 4],