np.newaxis作用

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]]]]

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转载自blog.csdn.net/qq_42546127/article/details/112885874