【1.3】Numpy学习-数组转置和形状（.T/reshape()/resize()）

Numpy学习-数组转置和形状

import numpy as np

ar1 = np.arange(10)
ar2 = np.ones((5,2))
print(ar1,'\n',ar1.T)
print(ar2,'\n',ar2.T)
# .T方法：转置，一维数组转置后结果不变

print('--------------------------------------------------')

ar3 = ar1.reshape(2,5) # 用法一：直接将已有数组改变形状
ar4 = np.zeros((4,6)).reshape(3,8) # 用法二：生成数组后直接改变形状
ar5 = np.reshape(np.arange(12),(3,4)) # 用法三：参数内添加数组，目标形状

print(ar1,'\n',ar3)
print(ar4)
print(ar5)

print('---------------------------------------')
ar6 = np.resize(np.arange(5),(3,4))
print(ar6)

# numpy.resize(a,new_shape):返回具有指定形状的新数组，如有必要可重复填充所需要的元素

结果如下：

[0 1 2 3 4 5 6 7 8 9] 
 [0 1 2 3 4 5 6 7 8 9]
[[1. 1.]
 [1. 1.]
 [1. 1.]
 [1. 1.]
 [1. 1.]] 
 [[1. 1. 1. 1. 1.]
 [1. 1. 1. 1. 1.]]
--------------------------------------------------
[0 1 2 3 4 5 6 7 8 9] 
 [[0 1 2 3 4]
 [5 6 7 8 9]]
[[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  1  2  3]
 [ 4  5  6  7]
 [ 8  9 10 11]]
---------------------------------------
[[0 1 2 3]
 [4 0 1 2]
 [3 4 0 1]]