/******************************************************
 * File: random_engine.h
 * Description: 隨機數(shù)生成器接口
 ******************************************************/
#ifndef RANDOM_ENGINE_H
#define RANDOM_ENGINE_H
#include <cstdint>
class RandomEngine
{
public:
    explicit RandomEngine(uint64_t seed = 88172645463325252ull);
    uint64_t nextUint64();
    double uniform01();
    double uniform(double a, double b);
    double normal(double mean = 0.0, double stddev = 1.0);
    double exponential(double lambda);
private:
    uint64_t state;
    bool hasSpare;
    double spare;
};
#endif
/******************************************************
 * File: random_engine.cpp
 * Description: Xorshift 隨機數(shù)生成器實現(xiàn)
 ******************************************************/
#include "random_engine.h"
#include <cmath>
#include <stdexcept>
/* 構(gòu)造函數(shù)：初始化種子 */
RandomEngine::RandomEngine(uint64_t seed)
    : state(seed), hasSpare(false)
{
    if (state == 0)
        state = 88172645463325252ull;
}
/* 核心 Xorshift64 算法 */
uint64_t RandomEngine::nextUint64()
{
    uint64_t x = state;
    x ^= x << 13;
    x ^= x >> 7;
    x ^= x << 17;
    state = x;
    return x;
}
/* 生成 [0,1) 上均勻分布 */
double RandomEngine::uniform01()
{
    return (nextUint64() >> 11) * (1.0 / 9007199254740992.0);
}
/* 生成 [a,b) 上均勻分布 */
double RandomEngine::uniform(double a, double b)
{
    if (a >= b)
        throw std::invalid_argument("uniform: a must be < b");
    return a + (b - a) * uniform01();
}
/* 正態(tài)分布：Box–Muller 變換 */
double RandomEngine::normal(double mean, double stddev)
{
    if (stddev <= 0.0)
        throw std::invalid_argument("normal: stddev must be positive");
    if (hasSpare)
    {
        hasSpare = false;
        return mean + stddev * spare;
    }
    double u, v, s;
    do
    {
        u = uniform(-1.0, 1.0);
        v = uniform(-1.0, 1.0);
        s = u * u + v * v;
    } while (s >= 1.0 || s == 0.0);
    s = std::sqrt(-2.0 * std::log(s) / s);
    spare = v * s;
    hasSpare = true;
    return mean + stddev * (u * s);
}
/* 指數(shù)分布 */
double RandomEngine::exponential(double lambda)
{
    if (lambda <= 0.0)
        throw std::invalid_argument("exponential: lambda must be positive");
    return -std::log(1.0 - uniform01()) / lambda;
}
/******************************************************
 * File: main.cpp
 * Description: 示例與測試
 ******************************************************/
#include <iostream>
#include "random_engine.h"
int main()
{
    RandomEngine rng(12345);
    std::cout << "Uniform [0,1):\n";
    for (int i = 0; i < 5; ++i)
        std::cout << rng.uniform01() << std::endl;
    std::cout << "\nNormal(0,1):\n";
    for (int i = 0; i < 5; ++i)
        std::cout << rng.normal() << std::endl;
    std::cout << "\nExponential(lambda=2):\n";
    for (int i = 0; i < 5; ++i)
        std::cout << rng.exponential(2.0) << std::endl;
    return 0;
}