binomial_distribution 类

生成二项式分布。

template<class IntType = int> class binomial_distribution { public:     // types     typedef IntType result_type;     struct param_type;     // constructors and reset functions     explicit binomial_distribution(IntType t = 1, double p = 0.5);     explicit binomial_distribution(const param_type& parm);     void reset();     // generating functions     template<class URNG>     result_type operator()(URNG& gen);     template<class URNG>     result_type operator()(URNG& gen, const param_type& parm);     // property functions     IntType t() const;     double p() const;     param_type param() const;     void param(const param_type& parm);     result_type min() const;     result_type max() const; };

参数

• IntType
  整数结果类型，默认为 int。 有关可能的类型，请参阅 <random>。

备注

如果未根据二项式分布离散型概率函数提供和分布任何类型，则模板类将描述产生用户指定的整型值或 int 型值的分布。 下表链接到有关各个成员的文章。

binomial_distribution::binomial_distribution	binomial_distribution::t	binomial_distribution::param
binomial_distribution::operator()	binomial_distribution::p	binomial_distribution::param_type

属性成员 t() 和 p() 将分别返回当前存储的分布参数值 t 和 p。

有关分布类及其成员的详细信息，请参阅 <random>。

有关二项式分布离散型概率函数的详细信息，请参阅 Wolfram MathWorld 文章二项式分布。

示例

 

 // compile with: /EHsc /W4
#include <random> 
#include <iostream>
#include <iomanip>
#include <string>
#include <map>

void test(const int t, const double p, const int& s) {

    // uncomment to use a non-deterministic seed
    //    std::random_device rd;
    //    std::mt19937 gen(rd());
    std::mt19937 gen(1729);

    std::binomial_distribution<> distr(t, p);

    std::cout << std::endl;
    std::cout << "p == " << distr.p() << std::endl;
    std::cout << "t == " << distr.t() << std::endl;

    // generate the distribution as a histogram
    std::map<int, int> histogram;
    for (int i = 0; i < s; ++i) {
        ++histogram[distr(gen)];
    }

    // print results
    std::cout << "Histogram for " << s << " samples:" << std::endl;
    for (const auto& elem : histogram) {
        std::cout << std::setw(5) << elem.first << ' ' << std::string(elem.second, ':') << std::endl;
    }
    std::cout << std::endl;
}

int main()
{
    int    t_dist = 1;
    double p_dist = 0.5;
    int    samples = 100;

    std::cout << "Use CTRL-Z to bypass data entry and run using default values." << std::endl;
    std::cout << "Enter an integer value for t distribution (where 0 <= t): ";
    std::cin >> t_dist;
    std::cout << "Enter a double value for p distribution (where 0.0 <= p <= 1.0): ";
    std::cin >> p_dist;
    std::cout << "Enter an integer value for a sample count: ";
    std::cin >> samples;

    test(t_dist, p_dist, samples);
}

输出

首次运行：

Use CTRL-Z to bypass data entry and run using default values.
Enter an integer value for t distribution (where 0 <= t): 22
Enter a double value for p distribution (where 0.0 <= p <= 1.0): .25
Enter an integer value for a sample count: 100

p == 0.25
t == 22
Histogram for 100 samples:
    1 :
    2 ::
    3 :::::::::::::
    4 ::::::::::::::
    5 :::::::::::::::::::::::::
    6 ::::::::::::::::::
    7 :::::::::::::
    8 ::::::
    9 ::::::
   11 :
   12 :

第二次运行：

Use CTRL-Z to bypass data entry and run using default values.
Enter an integer value for t distribution (where 0 <= t): 22
Enter a double value for p distribution (where 0.0 <= p <= 1.0): .5
Enter an integer value for a sample count: 100

p == 0.5
t == 22
Histogram for 100 samples:
    6 :
    7 ::
    8 :::::::::
    9 ::::::::::
   10 ::::::::::::::::
   11 :::::::::::::::::::
   12 :::::::::::
   13 :::::::::::::
   14 :::::::::::::::
   15 ::
   16 ::

第三次运行：

Use CTRL-Z to bypass data entry and run using default values.
Enter an integer value for t distribution (where 0 <= t): 22
Enter a double value for p distribution (where 0.0 <= p <= 1.0): .75
Enter an integer value for a sample count: 100

p == 0.75
t == 22
Histogram for 100 samples:
   13 ::::
   14 :::::::::::
   15 :::::::::::::::
   16 :::::::::::::::::::::
   17 ::::::::::::::
   18 :::::::::::::::::
   19 :::::::::::
   20 ::::::
   21 :

要求

标头：<random>

命名空间: std

请参见

参考

<random>