如何生成正态分布和均匀分布的随机数

function generateNormalDistribution(mean, standardDeviation) {
  let u = 0, v = 0;
  while (u === 0) u = Math.random(); // 避免u为0，因为log(0)是无穷大
  while (v === 0) v = Math.random();
  let z = Math.sqrt(-2.0 * Math.log(u)) * Math.cos(2.0 * Math.PI * v);
  return z * standardDeviation + mean;
}

let mean = 0; // 正态分布的均值
let standardDeviation = 1; // 正态分布的标准差
let randomValue = generateNormalDistribution(mean, standardDeviation);
console.log(randomValue);

import numpy as np

mean = 0  # 正态分布的均值
standard_deviation = 1  # 正态分布的标准差
random_value = np.random.normal(mean, standard_deviation)
print(random_value)

function generateUniformDistribution(min, max) {
  return Math.random() * (max - min) + min;
}

let min = 0; // 均匀分布的最小值
let max = 10; // 均匀分布的最大值
let randomValue = generateUniformDistribution(min, max);
console.log(randomValue);

import random

min_value = 0  # 均匀分布的最小值
max_value = 10  # 均匀分布的最大值
random_value = random.uniform(min_value, max_value)
print(random_value)