0

如果在 2D 中,p(x,y),我想要一个 3*3 的相邻矩阵:

(x-1,y-1), (x,y-1), (x+1,y-1),
...
(x-1,y+1), (x,y+1), (x+1,y+1),

如果在 3D(3*3*3)、4D(3*3*3*3)、...中怎么办?

有更好的功能吗?

4

2 回答 2

2

您也可以使用itertools.product,具体取决于您喜欢的输出格式。它会比一种numpy方法慢,但我发现它更容易理解:

from itertools import product

def adjacent_grid(centre):
    steps = product([-1, 0, 1], repeat=len(centre))
    return (tuple(c+d for c,d in zip(centre, delta)) for delta in steps)

这使

>>> list(adjacent_grid((3,)))
[(2,), (3,), (4,)]
>>> list(adjacent_grid((3,3)))
[(2, 2), (2, 3), (2, 4), (3, 2), (3, 3), (3, 4), (4, 2), (4, 3), (4, 4)]
>>> list(adjacent_grid((3,3,3)))
[(2, 2, 2), (2, 2, 3), (2, 2, 4), (2, 3, 2), (2, 3, 3), (2, 3, 4), (2, 4, 2), (2, 4, 3), (2, 4, 4), (3, 2, 2), (3, 2, 3), (3, 2, 4), (3, 3, 2), (3, 3, 3), (3, 3, 4), (3, 4, 2), (3, 4, 3), (3, 4, 4), (4, 2, 2), (4, 2, 3), (4, 2, 4), (4, 3, 2), (4, 3, 3), (4, 3, 4), (4, 4, 2), (4, 4, 3), (4, 4, 4)]
于 2013-02-06T05:27:07.190 回答
1

您可以通过在 numpy 中使用广播来获得结果:

import numpy as np
def p(*args):
    args = np.array(args)
    idx = np.array([-1, 0, 1])
    a = np.broadcast_arrays(*np.ix_(*(args[:,None] + idx)))
    return np.concatenate([x[..., None] for x in a], axis=-1)

结果形状是 2D 中的 (3,3,2),3D 中的 (3,3,3,3),4D 中的 (3,3,3,3,4):

>>> p(3, 8)
array([[[2, 7],
        [2, 8],
        [2, 9]],

       [[3, 7],
        [3, 8],
        [3, 9]],

       [[4, 7],
        [4, 8],
        [4, 9]]])
于 2013-02-06T04:49:12.060 回答