np.newaxis的作用:插入新维度
首先先来看以下这些例子:
example 1:
# In:
arr = np.array([1,2,3,4,5])
print(arr.shape)
print(arr)
# Out:
(5,)
[1,2,3,4,5]
example 2:
# In:
arr = np.array([1,2,3,4,5])
arr1 = arr[:, np.newaxis]
print(arr1.shape)
print(arr1)
# Out:
(5,1)
[[1],
[2],
[3],
[4],
[5]]
example 3:
# In:
arr = np.array([1,2,3,4,5])
arr2 = arr[np.newaxis, :]
print(arr2.shape)
print(arr2)
#Out:
(1,5)
[[1,2,3,4,5]]
如以上例子所示,np.newaxis的作用是增加一个维度
对应[: ,np.newaxis] 和 [np.newaxis, :]来说:
是在np.newaxis所在位置增加1维。
如果还感觉不太清楚,请看以下例子:
example 4:
# In:
arr = np.array([1,2,3,4,5])
print(arr.shape)
print(arr)
# Out:
(5,)
[1,2,3,4,5]
# In:
arr1 = arr[np.newaxis, :]
print(arr1.shape)
print(arr1)
#Out:
(1,5)
[[1,2,3,4,5]]
# In:
arr2 = arr1[np.newaxis, :]
print(arr2.shape)
print(arr2)
#Out:
(1,5)
[[[1,2,3,4,5]]]
# In:
arr3 = arr2[:, :, :, np.newaxis]
print(arr3.shape)
print(arr3)
#Out:
(1,5)
[[[[1],
[2],
[3],
[4],
[5]]]]