如何在保留顺序的同时重塑数组? [英] How to reshape an array while preserving order?

问题描述

我正在尝试将数组从形状(a，b，c)整形为(b，c，a)，以便如果我的表是B而我的表新表为B1，然后 B [n，::] = B1 [:，:，n] 表示介于0和a之间的某个n.例如，我尝试了类似的方法，

I am trying to reshape an array from shape (a,b,c) to (b,c,a) such that if my table is B and my new table is B1 then B[n,:,:]=B1[:,:,n] for some n between 0 and a. For example I tried something like,

B=np.array([[[1],[2],[23]],[[2],[4],[21]],[[6],[45],[61]],[[1],[34],[231]]])
B1=np.reshape(B,(3,1,4))

但是

B [1，:，:] = array([[2]，[4]，[21]])和

B1 [:，:，1] = array([[2]，[21]，[1]])这不是我想要的，我期望他们是平等的.任何建议将不胜感激.

B1[:,:,1]=array([[ 2],[21],[ 1]]) which is not what I want I would've expected them to be equal. Any suggestions would be greatly appreciated.

推荐答案

In [207]: B=np.array([[[1],[2],[23]],[[2],[4],[21]],[[6],[45],[61]],[[1],[34],[231]]])         
In [208]: B                                                                                    
Out[208]: 
array([[[  1],
        [  2],
        [ 23]],

       [[  2],
        [  4],
        [ 21]],

       [[  6],
        [ 45],
        [ 61]],

       [[  1],
        [ 34],
        [231]]])
In [209]: B.shape                                                                              
Out[209]: (4, 3, 1)

reshape 保持顺序，只是重新排列尺寸的大小:

reshape keeps the order, just rearranging the size of the dimensions:

In [210]: B.reshape(3,1,4)                                                                     
Out[210]: 
array([[[  1,   2,  23,   2]],

       [[  4,  21,   6,  45]],

       [[ 61,   1,  34, 231]]])

请注意，您可以按照创建 B 时所使用的顺序读取 1,2,23,2，... .

notice that you can read the 1,2,23,2,... in the same order that you used when creating B.

转置是不同的操作:

In [211]: B.transpose(1,2,0)                                                                   
Out[211]: 
array([[[  1,   2,   6,   1]],

       [[  2,   4,  45,  34]],

       [[ 23,  21,  61, 231]]])
In [212]: _.shape                                                                              
Out[212]: (3, 1, 4)
In [213]: __.ravel()                                                                           
Out[213]: array([  1,   2,   6,   1,   2,   4,  45,  34,  23,  21,  61, 231])

1,2,23，... 顺序仍然存在-如果您读取这些行.但是混乱的秩序已经改变.

The 1,2,23,... order is still there - if you read down the rows. But the raveled order has changed.

In [216]: B.transpose(1,2,0).ravel(order='F')                                                  
Out[216]: array([  1,   2,  23,   2,   4,  21,   6,  45,  61,   1,  34, 231])

In [217]: B[1,:,:]                                                                             
Out[217]: 
array([[ 2],
       [ 4],
       [21]])
In [218]: B.transpose(1,2,0)[:,:,1]                                                            
Out[218]: 
array([[ 2],
       [ 4],
       [21]])

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