[英]Tricky numpy argmax on last dimension of 3-dimensional ndarray
if have an array of shape (9,1,3). 如果具有形状数组(9,1,3)。
array([[[ 6, 12, 108]],
[[122, 112, 38]],
[[ 57, 101, 62]],
[[119, 76, 177]],
[[ 46, 62, 2]],
[[127, 61, 155]],
[[ 5, 6, 151]],
[[ 5, 8, 185]],
[[109, 167, 33]]])
I want to find the argmax index of the third dimension, in this case it would be 185, so index 7. 我想找到第三维的argmax索引,在这种情况下,它将是185,因此索引为7。
I guess the solution is linked to reshaping but I can't wrap my head around it. 我猜该解决方案与重塑有关,但是我无法解决这个问题。 Thanks for any help!
谢谢你的帮助!
You may have to do it like this: 您可能需要这样做:
data = np.array([[[ 6, 12, 108]],
[[122, 112, 38]],
[[ 57, 101, 62]],
[[119, 76, 177]],
[[ 46, 62, 2]],
[[127, 61, 155]],
[[ 5, 6, 151]],
[[ 5, 8, 185]],
[[109, 167, 33]]])
np.argmax(data[:,0][:,2])
7
I'm not sure what's tricky about it. 我不确定这有什么棘手的问题。 But, one way to get the index of the greatest element along the last axis would be by using
np.max
and np.argmax
like: 但是,获取沿最后一个轴的最大元素的索引的一种方法是使用
np.max
和np.argmax
例如:
# find `max` element along last axis
# and get the index using `argmax` where `arr` is your array
In [53]: np.argmax(np.max(arr, axis=2))
Out[53]: 7
Alternatively, as @PaulPanzer suggested in his comments , you could use: 或者,如@PaulPanzer在其评论中建议的那样 ,您可以使用:
In [63]: np.unravel_index(np.argmax(arr), arr.shape)
Out[63]: (7, 0, 2)
In [64]: arr[(7, 0, 2)]
Out[64]: 185
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