c – 具有Beta分布的随机数发生器

我需要像betarand(a,b)这样的函数的c或c源代码,它产生带有beta分布的随机数.我知道我可以使用boost库但是我要将它移植到CUDA架构中,所以我需要代码.有人能帮助我吗？
同时我有betapdf(Beta概率密度函数).但我不知道如何使用它来创建随机数:).

解决方法

C 11随机数库不提供beta分布.但是,beta分布可以根据库提供的两个gamma分布来建模.我已经为你实现了一个 beta_distribution的std :: gamma_distribution.据我所知,它完全符合随机数分布的要求.

#include <iostream>
#include <sstream>
#include <string>
#include <random>
 
namespace sftrabbit {
 
  template <typename RealType = double>
  class beta_distribution
  {
    public:
      typedef RealType result_type;
 
      class param_type
      {
        public:
          typedef beta_distribution distribution_type;
 
          explicit param_type(RealType a = 2.0,RealType b = 2.0)
            : a_param(a),b_param(b) { }
 
          RealType a() const { return a_param; }
          RealType b() const { return b_param; }
 
          bool operator==(const param_type& other) const
          {
            return (a_param == other.a_param &&
                    b_param == other.b_param);
          }
 
          bool operator!=(const param_type& other) const
          {
            return !(*this == other);
          }
 
        private:
          RealType a_param,b_param;
      };
 
      explicit beta_distribution(RealType a = 2.0,RealType b = 2.0)
        : a_gamma(a),b_gamma(b) { }
      explicit beta_distribution(const param_type& param)
        : a_gamma(param.a()),b_gamma(param.b()) { }
 
      void reset() { }
 
      param_type param() const
      {
        return param_type(a(),b());
      }
 
      void param(const param_type& param)
      {
        a_gamma = gamma_dist_type(param.a());
        b_gamma = gamma_dist_type(param.b());
      }
 
      template <typename URNG>
      result_type operator()(URNG& engine)
      {
        return generate(engine,a_gamma,b_gamma);
      }
 
      template <typename URNG>
      result_type operator()(URNG& engine,const param_type& param)
      {
        gamma_dist_type a_param_gamma(param.a()),b_param_gamma(param.b());
        return generate(engine,a_param_gamma,b_param_gamma); 
      }
 
      result_type min() const { return 0.0; }
      result_type max() const { return 1.0; }
 
      result_type a() const { return a_gamma.alpha(); }
      result_type b() const { return b_gamma.alpha(); }
 
      bool operator==(const beta_distribution<result_type>& other) const
      {
        return (param() == other.param() &&
                a_gamma == other.a_gamma &&
                b_gamma == other.b_gamma);
      }
 
      bool operator!=(const beta_distribution<result_type>& other) const
      {
        return !(*this == other);
      }
 
    private:
      typedef std::gamma_distribution<result_type> gamma_dist_type;
 
      gamma_dist_type a_gamma,b_gamma;
 
      template <typename URNG>
      result_type generate(URNG& engine,gamma_dist_type& x_gamma,gamma_dist_type& y_gamma)
      {
        result_type x = x_gamma(engine);
        return x / (x + y_gamma(engine));
      }
  };
 
  template <typename CharT,typename RealType>
  std::basic_ostream<CharT>& operator<<(std::basic_ostream<CharT>& os,const beta_distribution<RealType>& beta)
  {
    os << "~Beta(" << beta.a() << "," << beta.b() << ")";
    return os;
  }
 
  template <typename CharT,typename RealType>
  std::basic_istream<CharT>& operator>>(std::basic_istream<CharT>& is,beta_distribution<RealType>& beta)
  {
    std::string str;
    RealType a,b;
    if (std::getline(is,str,'(') && str == "~Beta" &&
        is >> a && is.get() == ',' && is >> b && is.get() == ')') {
      beta = beta_distribution<RealType>(a,b);
    } else {
      is.setstate(std::ios::failbit);
    }
    return is;
  }
 
}

像这样使用它：

std::random_device rd;
std::mt19937 gen(rd());
sftrabbit::beta_distribution<> beta(2,2);
for (int i = 0; i < 10000; i++) {
  std::cout << beta(gen) << std::endl;
}

c – 具有Beta分布的随机数发生器

解决方法

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