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numpy.tile()

谈琦
2023-12-01

numpy.tile()是个什么函数呢,说白了,就是把数组沿各个方向复制

比如 a = np.array([0,1,2]),    np.tile(a,(2,1))就是把a先沿x轴(就这样称呼吧)复制1倍,即没有复制,仍然是 [0,1,2]。 再把结果沿y方向复制2倍,即最终得到

 array([[0,1,2],

             [0,1,2]])

同理:

>>> b = np.array([[1, 2], [3, 4]])
>>> np.tile(b, 2) #沿X轴复制2倍
array([[1, 2, 1, 2],
       [3, 4, 3, 4]])
>>> np.tile(b, (2, 1))#沿X轴复制1倍(相当于没有复制),再沿Y轴复制2倍
array([[1, 2],
       [3, 4],
       [1, 2],
       [3, 4]])

numpy.tile()具体细节,如下:


numpy. tile ( Areps )

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 < dA 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 > dreps is promoted to A.ndim by pre-pending 1’s to it. Thus for an A of shape (2, 3, 4, 5), a repsof (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

The input array.

reps : array_like

The number of repetitions of A along each axis.

Returns:

c : ndarray

The tiled output array.

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)
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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