问题描述
使用 numpy 的优秀广播规则,您可以使用
Using the excellent broadcasting rules of numpy you can subtract a shape (3,) array v
from a shape (5,3) array X
with
X - v
结果是一个形状为 (5,3) 的数组,其中每一行 i
是差值 X[i] - v
.
The result is a shape (5,3) array in which each row i
is the difference X[i] - v
.
有没有办法从 X
中减去一个形状 (n,3) 数组 w
以便 w
的每一行都减去形式整个数组 X
没有显式使用循环?
Is there a way to subtract a shape (n,3) array w
from X
so that each row of w
is subtracted form the whole array X
without explicitly using a loop?
推荐答案
您需要使用 组成一个3D数组,然后用w做减法代码>.这会将
broadcasting
引入播放此 3D
操作并产生形状为 (5,n,3)
的输出.实现看起来像这样 -
You need to extend the dimensions of X
with None/np.newaxis
to form a 3D array and then do subtraction by w
. This would bring in broadcasting
into play for this 3D
operation and result in an output with a shape of (5,n,3)
. The implementation would look like this -
X[:,None] - w # or X[:,np.newaxis] - w
相反,如果所需的排序是 (n,5,3)
,那么您需要扩展 w
的维度,就像这样 -
Instead, if the desired ordering is (n,5,3)
, then you need to extend the dimensions of w
instead, like so -
X - w[:,None] # or X - w[:,np.newaxis]
样品运行 -
In [39]: X
Out[39]:
array([[5, 5, 4],
[8, 1, 8],
[0, 1, 5],
[0, 3, 1],
[6, 2, 5]])
In [40]: w
Out[40]:
array([[8, 5, 1],
[7, 8, 6]])
In [41]: (X[:,None] - w).shape
Out[41]: (5, 2, 3)
In [42]: (X - w[:,None]).shape
Out[42]: (2, 5, 3)
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