重新排序3D数组的行

use*_*415 2 python arrays numpy reshape

我有一个像这样的3D数组:

[[[ 0  0  1  0 -1  1  1  0  0]
  [ 0  0 -1  0  1 -1 -1  0  0]
  [ 0  0  1 -2 -1  1  0  0  0]
  [ 0  0 -1  2  1 -1  0  0  0]]

 [[ 0  0  0  2  0  0  1  0  0]
  [ 0  0  0  0  0  0  0  0  0]
  [ 0  0  0 -2  0  0 -1  0  0]
  [ 0  0  0  0  0  0  0  0  0]]

 [[ 0  0  1  0 -1  1  1  0  0]
  [ 0  0 -1  2  1 -1  0  0  0]
  [ 0  0  1 -2 -1  1  0  0  0]
  [ 0  0 -1  0  1 -1 -1  0  0]]

 [[ 0  0  0  0  0  0  0  0  0]
  [ 0  0  0  0  0  0  0  0  0]
  [ 0  0  0  0  0  0  0  0  0]
  [ 0  0  0  0  0  0  0  0  0]]]
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我需要重新整形它,以便每个矩阵中的所有第一行在矩阵中组合在一起,然后是所有第二行,等等.

所以结果如下:

[[[ 0  0  1  0 -1  1  1  0  0]
  [ 0  0  0  2  0  0  1  0  0]
  [ 0  0  1  0 -1  1  1  0  0]
  [ 0  0  0  0  0  0  0  0  0]]

 [[ 0  0 -1  0  1 -1 -1  0  0]
  [ 0  0  0  0  0  0  0  0  0]
  [ 0  0 -1  2  1 -1  0  0  0]
  [ 0  0  0  0  0  0  0  0  0]]

 [[ 0  0  1 -2 -1  1  0  0  0]
  [ 0  0  0 -2  0  0 -1  0  0]
  [ 0  0  1 -2 -1  1  0  0  0]
  [ 0  0  0  0  0  0  0  0  0]]

 [[ 0  0 -1  2  1 -1  0  0  0]
  [ 0  0  0  0  0  0  0  0  0]
  [ 0  0 -1  0  1 -1 -1  0  0]
  [ 0  0  0  0  0  0  0  0  0]]]
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Ale*_*ley 5

您只需要交换阵列的前两个轴x.如果数组是ndarray(就像你的那样),则返回一个视图,不会复制任何数据:

>>> x.swapaxes(0,1)
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例如:

>>> x = np.arange(27).reshape(3,3,3)
>>> x
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],
        [24, 25, 26]]])

>>> x.swapaxes(0,1)
array([[[ 0,  1,  2],
        [ 9, 10, 11],
        [18, 19, 20]],

       [[ 3,  4,  5],
        [12, 13, 14],
        [21, 22, 23]],

       [[ 6,  7,  8],
        [15, 16, 17],
        [24, 25, 26]]])
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