numpy 数组形状

import numpy as np

# t1 一维数组
t1 = np.arange(12)
print(t1,t1.shape)

# 查看数组的形状
print(t1.shape)

# t1 二维数组
t2 = np.array([[1,2,3],[4,5,6]])
print(t2,t2.shape)

# t3 三维数组
t3 = np.array([[[1,2,3],[4,5,6]],[[7,8,9],[10,11,12]]])
print(t3,t3.shape)

# 结果
[ 0  1  2  3  4  5  6  7  8  9 10 11] (12,)
(12,)
[[1 2 3]
 [4 5 6]] (2, 3)
[[[ 1  2  3]
  [ 4  5  6]]
 [[ 7  8  9]
  [10 11 12]]] (2, 2, 3)


t4 = np.arange(12)
  ...: print(t4,t4.shape)
[ 0  1  2  3  4  5  6  7  8  9 10 11] (12,)
t4.reshape((3,4))
Out[4]: 
array([[ 0,  1,  2,  3],
       [ 4,  5,  6,  7],
       [ 8,  9, 10, 11]])
t5 = np.arange(24).reshape((2,3,4))
  ...: print(t5)
[[[ 0  1  2  3]
  [ 4  5  6  7]
  [ 8  9 10 11]]
 [[12 13 14 15]
  [16 17 18 19]
  [20 21 22 23]]]

#  一维数组转化为三维数组
t5 = np.arange(24).reshape((2,3,4))
print(t5)

[[[ 0  1  2  3]
  [ 4  5  6  7]
  [ 8  9 10 11]]
 [[12 13 14 15]
  [16 17 18 19]
  [20 21 22 23]]]


#  t5 三维数组转化为一维数组
t5.reshape((24,))

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])


#  t5 三维数组转化为二维数组
t5.reshape((24,1))

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]])


#  t5 三维数组转化为二维数组
t5.reshape((1,24))

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]])

# 当数组t5的维数未知时，可采用shape属性的数组结果下标来计算t5的元素个数转化为一维数组
t6 = t5.reshape((t5.shape[0]*t5.shape[1]*t5.shape[2],))
print(t6)

[ 0  1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 16 17 18 19 20 21 22 23]

#  当数组t5的维数未知时，可采用flatten()转化为一维数组
t5.flatten()

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])