18. numpy.reshape()使用示例

对随机生成的两种数组randint， asfortranarray(r)分别进行测试：

import numpy as np
from numpy import random as nr

r = nr.randint(0, 10, size = (4, 3))
r1 = r.reshape((3, 4), order = 'A') # randint A与C相同 行优先 用原始数组的行排现有的行
r2 = r.reshape((3, 4), order = 'C') # 行优先
r3 = r.reshape((3, 4), order = 'F') # 列优先 用原始数组的列排现有的列
r4 = r.reshape((3, 4)) # 默认行优先
print('r : ', r)
print('r1 : ', r1)
print('r2 : ', r2)
print('r3 : ', r3)  
print('r4 : ', r4)


r = np.asfortranarray(r)

r1 = r.reshape((3, 4), order = 'A') # asfortranarray 此时A与F相同
r2 = r.reshape((3, 4), order = 'C') # 行优先
r3 = r.reshape((3, 4), order = 'F') # 列优先
r4 = r.reshape((3, 4))  # 默认行优先
print('r : ', r) # r 不变
print('r1 : ', r1)
print('r2 : ', r2)
print('r3 : ', r3)  
print('r4 : ', r4)

结果如下：

r :  [[1 2 7]
 [0 2 2]
 [3 9 8]
 [1 5 0]]
r1 :  [[1 2 7 0]
 [2 2 3 9]
 [8 1 5 0]]
r2 :  [[1 2 7 0]
 [2 2 3 9]
 [8 1 5 0]]
r3 :  [[1 1 9 2]
 [0 2 5 8]
 [3 2 7 0]]
r4 :  [[1 2 7 0]
 [2 2 3 9]
 [8 1 5 0]]
r :  [[1 2 7]
 [0 2 2]
 [3 9 8]
 [1 5 0]]
r1 :  [[1 1 9 2]
 [0 2 5 8]
 [3 2 7 0]]
r2 :  [[1 2 7 0]
 [2 2 3 9]
 [8 1 5 0]]
r3 :  [[1 1 9 2]
 [0 2 5 8]
 [3 2 7 0]]
r4 :  [[1 2 7 0]
 [2 2 3 9]
 [8 1 5 0]]
1
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