np.newaxis和np.power

1.np.power

numpy.power(x1, x2)

数组的元素分别求n次方。x2可以是数字，也可以是数组，但是x1和x2的列数要相同。

x1 = range(6)
>>> x1
[0, 1, 2, 3, 4, 5]
>>> np.power(x1, 3)
array([  0,   1,   8,  27,  64, 125])

>>> x2 = [1.0, 2.0, 3.0, 3.0, 2.0, 1.0]
>>> np.power(x1, x2)
array([  0.,   1.,   8.,  27.,  16.,   5.])

>>> x2 = np.array([[1, 2, 3, 3, 2, 1], [1, 2, 3, 3, 2, 1]])
>>> x2
array([[1, 2, 3, 3, 2, 1],
       [1, 2, 3, 3, 2, 1]])
>>> np.power(x1, x2)
array([[ 0,  1,  8, 27, 16,  5],
       [ 0,  1,  8, 27, 16,  5]])

2.np.newaxis()

np.newaxis,增加维度

np.linspace(1, 10, 10)
  array([ 1., 2., 3., 4., 5., 6., 7., 8., 9., 10.])

np.linspace(1, 10, 10)[np.newaxis,:]
 array([[ 1., 2., 3., 4., 5., 6., 7., 8., 9., 10.]])

 np.linspace(1, 10, 10)[:,np.newaxis]
  array
 ([[ 1.],
  [ 2.],
  [ 3.],
  [ 4.],
  [ 5.],
  [ 6.],
  [ 7.],
  [ 8.],
  [ 9.],
  [ 10.]])

In [4]: np.linspace(1, 10, 10).shape
Out[4]: (10,)%数组

In [5]: np.linspace(1, 10, 10)[np.newaxis,:].shape
Out[5]: (1, 10)%矩阵

In [6]: np.linspace(1, 10, 10)[:,np.newaxis].shape
Out[6]: (10, 1)