numpy库对多维数组有非常灵巧的处理方式，主要的处理方法有：
.reshape(shape) ： 不改变数组元素，返回一个shape形状的数组，原数组不变
.resize(shape) ： 与.reshape()功能一致，但修改原数组
In [22]: a = np.arange(20)
#原数组不变
In [23]: a.reshape([4,5])
Out[23]:
array([[ 0, 1, 2, 3, 4],
[ 5, 6, 7, 8, 9],
[10, 11, 12, 13, 14],
[15, 16, 17, 18, 19]])
In [24]: a
Out[24]:
array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16,
17, 18, 19])
#修改原数组
In [25]: a.resize([4,5])
In [26]: a
Out[26]:
array([[ 0, 1, 2, 3, 4],
[ 5, 6, 7, 8, 9],
[10, 11, 12, 13, 14],
[15, 16, 17, 18, 19]])
.swapaxes(ax1,ax2) ： 将数组n个维度中两个维度进行调换，不改变原数组
In [27]: a.swapaxes(1,0)
Out[27]:
array([[ 0, 5, 10, 15],
[ 1, 6, 11, 16],
[ 2, 7, 12, 17],
[ 3, 8, 13, 18],
[ 4, 9, 14, 19]])
.flatten() ： 对数组进行降维，返回折叠后的一维数组，原数组不变
In [29]: a.flatten()
Out[29]:
array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16,
17, 18, 19])
