[英]How do you sequentially flip each dimension in a NumPy array?
I have encountered the following function in MATLAB that sequentially flips all of the dimensions in a matrix: 我在MATLAB中遇到了以下函数,它顺序翻转矩阵中的所有维度:
function X=flipall(X)
for i=1:ndims(X)
X = flipdim(X,i);
end
end
Where X
has dimensions (M,N,P) = (24,24,100)
. 其中
X
尺寸(M,N,P) = (24,24,100)
。 How can I do this in Python, given that X
is a NumPy array? 考虑到
X
是NumPy数组,我怎样才能在Python中执行此操作?
The equivalent to flipdim
in MATLAB is flip
in numpy
. 等效
flipdim
在MATLAB是flip
的numpy
。 Be advised that this is only available in version 1.12.0. 请注意,这仅适用于1.12.0版。
Therefore, it's simply: 因此,它很简单:
import numpy as np
def flipall(X):
Xcopy = X.copy()
for i in range(X.ndim):
Xcopy = np.flip(Xcopy, i)
return Xcopy
As such, you'd simply call it like so: 因此,您只需将其称为:
Xflip = flipall(X)
However, if you know a priori that you have only three dimensions, you can hard code the operation by simply doing: 但是,如果您事先知道只有三个维度,则只需执行以下操作即可对操作进行硬编码:
def flipall(X):
return X[::-1,::-1,::-1]
This flips each dimension one right after the other. 这会使每个尺寸一个接一个地翻转。
If you don't have version 1.12.0 (thanks to user hpaulj), you can use slice
to do the same operation: 如果您没有版本1.12.0(感谢用户hpaulj),您可以使用
slice
执行相同的操作:
import numpy as np
def flipall(X):
return X[[slice(None,None,-1) for _ in X.shape]]
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