extreme_value_distribution 類別

產生極值分佈。

template<class RealType = double> class extreme_value_distribution { public:     // types     typedef RealType result_type;     struct param_type;     // constructor and reset functions     explicit extreme_value_distribution(RealType a = 0.0, RealType b = 1.0);     explicit extreme_value_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     RealType a() const;     RealType b() const;     param_type param() const;     void param(const param_type& parm);     result_type min() const;     result_type max() const; };

參數

• RealType
  浮點結果類型，預設值為 double。 如需可能的類型，請參閱 <random>。

備註

此範本類別描述產生使用者指定之整數類型的值的分佈 (若無提供則為 double 類型)，而這是根據極值分佈進行分佈。 下表提供各個成員的文章連結。

extreme_value_distribution::extreme_value_distribution	extreme_value_distribution::a	extreme_value_distribution::param
extreme_value_distribution::operator()	extreme_value_distribution::b	extreme_value_distribution::param_type

屬性函式 a() 和 b() 會針對儲存的分佈參數 a 和 b 分別傳回各自的值。

如需分佈類別及其成員的詳細資訊，請參閱 <random>。

如需極值的詳細資訊，請參閱 Wolfram MathWorld 文章：極值分佈 (英文)。

範例

 

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

void test(const double a, const double b, const int s) {

    // uncomment to use a non-deterministic generator
    //    std::random_device gen;

    std::mt19937 gen(1701);

    std::extreme_value_distribution<> distr(a, b);

    std::cout << std::endl;
    std::cout << "min() == " << distr.min() << std::endl;
    std::cout << "max() == " << distr.max() << std::endl;
    std::cout << "a() == " << std::fixed << std::setw(11) << std::setprecision(10) << distr.a() << std::endl;
    std::cout << "b() == " << std::fixed << std::setw(11) << std::setprecision(10) << distr.b() << std::endl;

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

    // print results
    std::cout << "Distribution for " << s << " samples:" << std::endl;
    int counter = 0;
    for (const auto& elem : histogram) {
        std::cout << std::fixed << std::setw(11) << ++counter << ": "
            << std::setw(14) << std::setprecision(10) << elem.first << std::endl;
    }
    std::cout << std::endl;
}

int main()
{
    double a_dist = 0.0;
    double b_dist = 1;

    int samples = 10;

    std::cout << "Use CTRL-Z to bypass data entry and run using default values." << std::endl;
    std::cout << "Enter a floating point value for the \'a\' distribution parameter: ";
    std::cin >> a_dist;
    std::cout << "Enter a floating point value for the \'b\' distribution parameter (must be greater than zero): ";
    std::cin >> b_dist;
    std::cout << "Enter an integer value for the sample count: ";
    std::cin >> samples;

    test(a_dist, b_dist, samples);
}

輸出

Use CTRL-Z to bypass data entry and run using default values.
Enter a floating point value for the 'a' distribution parameter: 0
Enter a floating point value for the 'b' distribution parameter (must be greater than zero): 1
Enter an integer value for the sample count: 10

min() == -1.79769e+308
max() == 1.79769e+308
a() == 0.0000000000
b() == 1.0000000000
Distribution for 10 samples:
          1:  -0.8813940331
          2:  -0.7698972281
          3:   0.2951258007
          4:   0.3110450734
          5:   0.4210546820
          6:   0.4210688771
          7:   0.4598857960
          8:   1.3155194200
          9:   1.5379170046
         10:   2.0568757061

需求

標頭：<random>

命名空間: std

請參閱

參考

<random>