如何在NumPy中标准化数组? [英] How to normalize an array in NumPy?

问题描述

我想要一个NumPy数组的范数.更具体地说，我正在寻找此功能的等效版本

I would like to have the norm of one NumPy array. More specifically, I am looking for an equivalent version of this function

def normalize(v):
    norm = np.linalg.norm(v)
    if norm == 0: 
       return v
    return v / norm

在skearn或numpy中是否存在类似的内容?

Is there something like that in skearn or numpy?

此功能在v是0向量的情况下起作用.

This function works in a situation where v is the 0 vector.

推荐答案

如果您使用的是scikit-learn，则可以使用

If you're using scikit-learn you can use sklearn.preprocessing.normalize:

import numpy as np
from sklearn.preprocessing import normalize

x = np.random.rand(1000)*10
norm1 = x / np.linalg.norm(x)
norm2 = normalize(x[:,np.newaxis], axis=0).ravel()
print np.all(norm1 == norm2)
# True

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