如何将 NumPy 数组归一化为单位向量? [英] How to normalize a NumPy array to a unit vector?

问题描述

我想将 NumPy 数组转换为单位向量.更具体地说，我正在寻找此规范化函数的等效版本:

I would like to convert a NumPy array to a unit vector. More specifically, I am looking for an equivalent version of this normalisation function:

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

该函数处理向量v的范数为0的情况.

This function handles the situation where vector v has the norm value of 0.

sklearn 或 numpy 中是否提供了类似的功能?

Is there any similar functions provided in sklearn or numpy?

推荐答案

如果你使用 scikit-learn 你可以使用 sklearn.preprocessing.normalize:

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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