NumPy squeeze()

import numpy as np

# create a 3-D array
array1 = np.array([[[0, 1]]])

# squeeze the array 
squeezedArray = np.squeeze(array1)

print(squeezedArray)

# Output : [0 1]

squeeze() 语法

squeeze() 的语法是

numpy.squeeze(array, axis = None)

squeeze() 参数

squeeze() 方法接受两个参数

• array - 要压缩的数组
• axis(可选) - 沿其压缩数组的轴（None、int 或 tuple）

squeeze() 返回值

squeeze() 方法返回压缩后的数组。

示例 1：压缩具有单维条目的数组

import numpy as np

array1 = np.array([[[1, 2, 3]]])

# squeeze the array
squeezedArray = np.squeeze(array1)  

print(squeezedArray)

输出

[1 2 3]

示例 2：压缩具有多个单维条目的数组

import numpy as np

array1 = np.array([[1], [2], [3]]) 

# squeeze the array
squeezedArray = np.squeeze(array1)  

print(squeezedArray)

输出

[1 2 3]

示例 3：沿特定轴进行压缩

如果不传递 axis 参数，则默认为 None，所有长度为 1 的维度都会被移除。

但是，我们可以指定要压缩的特定轴。

import numpy as np
array1 = np.array([[[1], [2], [3]]])

print('Original Array: \n', array1, "\nShape: ",array1.shape, '\n')

# squeeze array1
array2 = np.squeeze(array1)  

print('Squeezed Array: \n', array2, "\nShape: ",array2.shape, '\n')

# squeeze array1 along axis 0
array3 = np.squeeze(array1, axis = 0)  

print('Squeezed Array along axis 0: \n', array3, "\nShape: ",array3.shape, '\n')

# squeeze array1 along the last axis
array4 = np.squeeze(array1, axis = -1)  

print('Squeezed Array along last axis: \n', array4, "\nShape: ",array4.shape, '\n')

# squeeze array1 along axis 9 and 2
array5 = np.squeeze(array1, axis = (0, 2))  

print('Squeezed Array along axis (0, 2): \n', array5, "\nShape: ",array5.shape, '\n')

输出

Original Array: 
[[[1]
  [2]
  [3]]] 
Shape:  (1, 3, 1) 

Squeezed Array: 
 [1 2 3] 
Shape:  (3,) 

Squeezed Array along axis 0: 
 [[1]
 [2]
 [3]] 
Shape:  (3, 1) 

Squeezed Array along last axis: 
 [[1 2 3]] 
Shape:  (1, 3) 

Squeezed Array along axis (0, 2): 
 [1 2 3] 
Shape:  (3,) 

示例 4：所有维度长度都为 1 的情况下的压缩

如果所有维度长度都为 1，则返回一个标量值。

import numpy as np

array1 = np.array([[[123]]])

# squeeze array1
array2 = np.squeeze(array1)  

print('Squeezed Array: \n', array2)

输出

123