我正在尝试系统地访问 numpy 数组的轴。例如,假设我有一个数组
a = np.random.random((10, 10, 10, 10, 10, 10, 10))
# choosing 7:9 from axis 2
b = a[:, :, 7:9, ...]
# choosing 7:9 from axis 3
c = a[:, :, :, 7:9, ...]
如果我有一个高维数组,输入冒号会变得非常重复。现在,我想要一些函数 choose_from_axis
这样
# choosing 7:9 from axis 2
b = choose_from_axis(a, 2, 7, 9)
# choosing 7:9 from axis 3
c = choose_from_axis(a, 3, 7, 9)
所以,基本上,我想访问一个带有数字的轴。我知道如何做到这一点的唯一方法是来回使用 rollaxis
,但我正在寻找一种更直接的方法来做到这一点。
最佳答案
听起来您可能正在寻找 take :
>>> a = np.random.randint(0,100, (3,4,5))
>>> a[:,1:3,:]
array([[[61, 4, 89, 24, 86],
[48, 75, 4, 27, 65]],
[[57, 55, 55, 6, 95],
[19, 16, 4, 61, 42]],
[[24, 89, 41, 74, 85],
[27, 84, 23, 70, 29]]])
>>> a.take(np.arange(1,3), axis=1)
array([[[61, 4, 89, 24, 86],
[48, 75, 4, 27, 65]],
[[57, 55, 55, 6, 95],
[19, 16, 4, 61, 42]],
[[24, 89, 41, 74, 85],
[27, 84, 23, 70, 29]]])
这也将为您提供对元组索引的支持。示例:
>>> a = np.arange(2*3*4).reshape(2,3,4)
>>> a
array([[[ 0, 1, 2, 3],
[ 4, 5, 6, 7],
[ 8, 9, 10, 11]],
[[12, 13, 14, 15],
[16, 17, 18, 19],
[20, 21, 22, 23]]])
>>> a[:,:,(0,1,3)]
array([[[ 0, 1, 3],
[ 4, 5, 7],
[ 8, 9, 11]],
[[12, 13, 15],
[16, 17, 19],
[20, 21, 23]]])
>>> a.take((0,1,3), axis=2)
array([[[ 0, 1, 3],
[ 4, 5, 7],
[ 8, 9, 11]],
[[12, 13, 15],
[16, 17, 19],
[20, 21, 23]]])
关于python - 通过 int 选择 numpy 数组轴,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/30067183/