bernoulli_distribution Class

The latest version of this topic can be found at bernoulli_distribution Class.

Generates a Bernoulli distribution.

Syntax

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;
   };  

Remarks

The class describes a distribution that produces values of type bool, distributed according to the Bernoulli distribution discrete probability function. The following table links to articles about individual members.

The property member p() returns the currently stored distribution parameter value p.

For more information about distribution classes and their members, see <random>.

For detailed information about the Bernoulli distribution discrete probability function, see the Wolfram MathWorld article Bernoulli Distribution.

Example

// 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);  
}  
  

Output

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 :::::::::::::::::::::::::::::::::::::::::::::::  

Requirements

Header: <random>

Namespace: std

bernoulli_distribution::bernoulli_distribution

Constructs the distribution.

explicit bernoulli_distribution(double p = 0.5);

 
explicit bernoulli_distribution(const param_type& parm);

Parameters

p
The stored p distribution parameter.

parm
The parameter structure used to construct the distribution.

Remarks

Precondition: 0.0 ≤ p ≤ 1.0

The first constructor constructs an object whose stored p value holds the value p.

The second constructor constructs an object whose stored parameters are initialized from parm. You can obtain and set the current parameters of an existing distribution by calling the param() member function.

For more information and a code example, see binomial_distribution Class.

bernoulli_distribution::param_type

Contains the parameters of the distribution.

struct param_type {
typedef bernoulli_distribution distribution_type;
param_type(double p = 0.5); double p() const; .....
bool operator==(const param_type& right) const; bool operator!=(const param_type& right) const; };

Parameters

See parent topic bernoulli_distribution Class.

Remarks

Precondition: 0.0 ≤ p ≤ 1.0

This structure can be passed to the distribution's class constructor at instantiation, to the param() member function to set the stored parameters of an existing distribution, and to operator() to be used in place of the stored parameters.

See Also

<random>