np.linalg.norm() 求范数

linalg = linear(线性) + algebra(代数)
norm 表示范数

使用语法:

import numpy as np
x_norm = np.linalg.norm(x, ord=None, axis=None, Keepdims=False)

x:为输入的数据

ord:范数类型

axis:处理类型

keepdims:是否要保持矩阵的二维特性,True 表示保持,False(默认)反之。

代码示例:

import numpy as np

x = np.array([[0, 3, 4], [2, 4, 4]])
print(x)
>>>
[[0 3 4]
 [2 4 4]]

x_norm = np.linalg.norm(x)
print(x_norm)
>>>
7.81024967591

x_norm = np.linalg.norm(x, ord=1, axis=1, keepdims=True)
print(x_norm)
>>>
[[  7.]
 [ 10.]]

x_norm = np.linalg.norm(x, axis=1, keepdims=True)
print(x_norm)
>>>
[[ 5.]
 [ 6.]]

来自

https://blog.csdn.net/qq_31347869/article/details/89090817

感谢!!!

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转载自blog.csdn.net/qq_40297851/article/details/105146306