bernoulli_distribution 类
生成伯努利分布。
class bernoulli_distribution { public: // types typedef bool result_type; struct param_type; // constructors and reset functions explicit bernoulli_distribution(double p = 0.5); explicit bernoulli_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 double p() const; param_type param() const; void param(const param_type& parm); result_type min() const; result_type max() const; };
备注
该类描述了产生 bool 类型的值的分布,根据伯努利分布离散型概率函数进行分布。 下表链接到有关各个成员的文章。
bernoulli_distribution::p |
bernoulli_distribution::param |
|
bernoulli_distribution::operator() |
属性函数 p() 将返回当前存储的分布参数值 p。
有关分布类及其成员的详细信息,请参阅 <random>。
有关伯努利分布离散型概率函数的详细信息,请参阅 Wolfram MathWorld 文章伯努利分布。
示例
// compile with: /EHsc /W4
#include <random>
#include <iostream>
#include <iomanip>
#include <string>
#include <map>
void test(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::bernoulli_distribution distr(p);
std::cout << "p == " << distr.p() << std::endl;
// generate the distribution as a histogram
std::map<bool, 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::boolalpha << std::setw(5) << elem.first << ' ' << std::string(elem.second, ':') << std::endl;
}
std::cout << std::endl;
}
int main()
{
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 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(p_dist, samples);
}
输出
Use CTRL-Z to bypass data entry and run using default values.
Enter a double value for p distribution (where 0.0 <= p <= 1.0): .45
Enter an integer value for a sample count: 100
p == 0.45
Histogram for 100 samples:
false :::::::::::::::::::::::::::::::::::::::::::::::::::::
true :::::::::::::::::::::::::::::::::::::::::::::::
要求
标头:<random>
命名空间: std