Python中reshape的用法?

原文地址为： Python中reshape的用法?

使用数组的reshape方法，可以创建一个改变了尺寸的新数组，原数组的shape保持不变；

 1 >>> a = np.array([1, 2, 3, 4]);b = np.array((5, 6, 7, 8));c = np.array([[1, 2, 3, 4],[4, 5, 6, 7], [7, 8, 9, 10]])
 2 >>> b
 3 array([5, 6, 7, 8])
 4 >>> c
 5 array([[ 1,  2,  3,  4],
 6        [ 4,  5,  6,  7],
 7        [ 7,  8,  9, 10]])
 8 >>> c.dtype
 9 dtype('int32')
10 >>> d = a.reshape((2,2))
11 >>> d
12 array([[1, 2],
13        [3, 4]])
14 >>> d = a.reshape((1,2))
15 Traceback (most recent call last):
16   File "<pyshell#27>", line 1, in <module>
17     d = a.reshape((1,2))
18 ValueError: total size of new array must be unchanged
19 >>> d = a.reshape((1,-1))
20 >>> d
21 array([[1, 2, 3, 4]])

>>> d = a.reshape((-1,1))
>>> d
array([[1],
[2],
[3],
[4]])

注意:a.reshape((1,-1))和a.reshape((1,2))和a.reshape((-1,1))

转载请注明本文地址： Python中reshape的用法?