poisson_distribution Class

 

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

Generates a Poisson distribution.

Syntax

class poisson_distribution  
   {  
   public:  // types  
   typedef IntType result_type;  
   struct param_type;  // constructors and reset functions  
   explicit poisson_distribution(double mean = 1.0);
   explicit poisson_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 mean() const;
   param_type param() const;
   void param(const param_type& parm);
   result_type min() const;
   result_type max() const;
   };  

Parameters

IntType
The integer result type, defaults to int. For possible types, see <random>.

Remarks

The template class describes a distribution that produces values of a user-specified integral type with a Poisson distribution. The following table links to articles about individual members.

poisson_distribution::poisson_distribution	poisson_distribution::mean	poisson_distribution::param
poisson_distribution::operator()		poisson_distribution::param_type

The property function mean() returns the value for stored distribution parameter mean.

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

For detailed information about the Poisson distribution, see the Wolfram MathWorld article Poisson 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 generator  
    //    std::random_device gen;  
    std::mt19937 gen(1701);  
  
    std::poisson_distribution<> distr(p);  
  
    std::cout << std::endl;  
    std::cout << "min() == " << distr.min() << std::endl;  
    std::cout << "max() == " << distr.max() << std::endl;  
    std::cout << "p() == " << std::fixed << std::setw(11) << std::setprecision(10) << distr.mean() << 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 << "Distribution 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()  
{  
    double p_dist = 1.0;  
  
    int samples = 100;  
  
    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 'mean' distribution parameter (must be greater than zero): ";  
    std::cin >> p_dist;  
    std::cout << "Enter an integer value for the sample count: ";  
    std::cin >> samples;  
  
    test(p_dist, samples);  
}  
  

Output

First test:

Use CTRL-Z to bypass data entry and run using default values.Enter a floating point value for the 'mean' distribution parameter (must be greater than zero): 1Enter an integer value for the sample count: 100min() == 0max() == 2147483647p() == 1.0000000000Distribution for 100 samples:    0 ::::::::::::::::::::::::::::::    1 ::::::::::::::::::::::::::::::::::::::    2 :::::::::::::::::::::::    3 ::::::::    5 :  

Second test:

Use CTRL-Z to bypass data entry and run using default values.Enter a floating point value for the 'mean' distribution parameter (must be greater than zero): 10Enter an integer value for the sample count: 100min() == 0max() == 2147483647p() == 10.0000000000Distribution for 100 samples:    3 :    4 ::    5 ::    6 ::::::::    7 ::::    8 ::::::::    9 ::::::::::::::   10 ::::::::::::   11 ::::::::::::::::   12 :::::::::::::::   13 ::::::::   14 ::::::   15 :   16 ::   17 :  

Requirements

Header: <random>

Namespace: std

poisson_distribution::poisson_distribution

Constructs the distribution.

explicit poisson_distribution(RealType mean = 1.0);

 
explicit binomial_distribution(const param_type& parm);

Parameters

mean
The mean distribution parameter.

parm
The parameter structure used to construct the distribution.

Remarks

Precondition: 0.0 < mean

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.

poisson_distribution::param_type

Stores the parameters of the distribution.

struct param_type {  
   typedef poisson_distribution<IntType> distribution_type;  
   param_type(double mean = 1.0);
   RealType mean() const;
   ....  
   bool operator==(const param_type& right) const;
   bool operator!=(const param_type& right) const;
   };  

Parameters

See parent topic poisson_distribution Class.

Remarks

Precondition: 0.0 < mean

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>