处理数组形状

>>> import numpy as np
>>> m = np.arange(24)
>>> m
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])
>>> m.shape
(24,)
>>> n = m.reshape(3,8)
>>> n
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]])
>>> o = m.reshape(3,2,4)
>>> o
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]]])
>>> m.shape #直接改变形状
(24,)
>>> m
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])
>>> m.resize(3,8) #直接改变形状
>>> m
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]])
>>> m.transpose() #转置，视图
array([[ 0,  8, 16],
       [ 1,  9, 17],
       [ 2, 10, 18],
       [ 3, 11, 19],
       [ 4, 12, 20],
       [ 5, 13, 21],
       [ 6, 14, 22],
       [ 7, 15, 23]])

 

>>> #多维转一维
>>> e
array([[[10, 11, 12, 13, 14],
        [ 0,  1,  2,  3,  4]],

       [[20, 22, 24, 26, 28],
        [ 0,  2,  4,  6,  8]]])
>>> e.ravel()
array([10, 11, 12, 13, 14,  0,  1,  2,  3,  4, 20, 22, 24, 26, 28,  0,  2,
        4,  6,  8])
>>> n.flatten() #重新分配内在
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])
>>> n.shape(24,)
Traceback (most recent call last):
  File "<pyshell#62>", line 1, in <module>
    n.shape(24,)
TypeError: 'tuple' object is not callable
>>> n
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]])
>>> n.resize(24,)
>>> n
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])