Transpose and axis swap of ndarray arrays

Transpose and axis swap of ndarray arrays

Transpose resets the array, returning a view of the source data (without any copying).
There are three ways to transpose, transposemethod, Tproperty and swapaxesmethod.

1 .T

import numpy as np
arr = np.arange(9).reshape((3,3))#生成一个3行3列的数组
print arr
[[0 1 2]
 [3 4 5]
 [6 7 8]]
print arr.T
[[0 3 6]
 [1 4 7]
 [2 5 8]]

2. transpose

For high-dimensional arrays, transpose requires a tuple of axis numbers to transpose.

For example, for a three-dimensional array, number the dimensions, that is, 0, 1, 2. Here 0,1,2 can be understood as the index of the returned tuple for shape.
for example

arr1 = np.arange(24).reshape(2,3,4)#生成一个2*3*4的数组
print arr1
[[[ 0  1  2  3]
  [ 4  5  6  7]
  [ 8  9 10 11]]
 [[12 13 14 15]
  [16 17 18 19]
  [20 21 22 23]]]
print arr1.shape #看形状
(2, 3, 4)        #说明这是一个2*3*4的数组（矩阵），返回的是一个元组，可以对元组进行索引，也就是0,1,2

transpose((1,0,2))The meaning of is to (2, 3, 4)convert into (3, 2, 4), for example, the index starting with the value 12 is [1,0,0], after the transformation, it becomes [0,1,0], as shown below:

print arr1.transpose((1,0,2))
[[[ 0  1  2  3]
  [12 13 14 15]]
 [[ 4  5  6  7]
  [16 17 18 19]]
 [[ 8  9 10 11]
  [20 21 22 23]]]

3.swapages

swapaxes, which accept a pair of axis numbers. Swap shafts.

arr1 = np.arange(24).reshape(2,3,4)
print arr1
[[[ 0  1  2  3]
  [ 4  5  6  7]
  [ 8  9 10 11]]
 [[12 13 14 15]
  [16 17 18 19]
  [20 21 22 23]]]
print arr1.swapaxes(1,0) #将第一个轴和第二个轴交换，对比transpose（1,0,2）
[[[ 0  1  2  3]
  [12 13 14 15]]
 [[ 4  5  6  7]
  [16 17 18 19]]
 [[ 8  9 10 11]
  [20 21 22 23]]]