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std::poisson_distribution

Defined in header <random> 
template< class IntType = int >
class poisson_distribution;
 (since C++11)

Produces random non-negative integer values i, distributed according to discrete probability function: \(P(i | \mu) = \frac{e^{-\mu}\mu^i}{i!}\)P(i|μ) =

e-μ·μi/i!

The value obtained is the probability of exactly i occurrences of a random event if the expected, mean number of its occurrence under the same conditions (on the same time/space interval) is μ.

std::poisson_distribution satisfies RandomNumberDistribution.

Template parameters

IntType - The result type generated by the generator. The effect is undefined if this is not one of short, int, long, long long, unsigned short, unsigned int, unsigned long, or unsigned long long.

Member types

Member type Definition
result_type (C++11) IntType
param_type (C++11) the type of the parameter set, see RandomNumberDistribution.

Member functions

(C++11)
constructs new distribution
(public member function)
(C++11)
resets the internal state of the distribution
(public member function)
Generation
(C++11)
generates the next random number in the distribution
(public member function)
Characteristics
(C++11)
returns the mean distribution parameter (mean number of occurrences of the event)
(public member function)
(C++11)
gets or sets the distribution parameter object
(public member function)
(C++11)
returns the minimum potentially generated value
(public member function)
(C++11)
returns the maximum potentially generated value
(public member function)

Non-member functions

(C++11)(C++11)(removed in C++20)
compares two distribution objects
(function)
(C++11)
performs stream input and output on pseudo-random number distribution
(function template)

Example

#include <iomanip>
#include <iostream>
#include <map>
#include <random>
#include <string>
 
int main()
{
    std::random_device rd;
    std::mt19937 gen(rd());
 
    // If an event occurs 4 times a minute on average, how
    // often is it that it occurs n times in one minute?
    std::poisson_distribution<> d(4);
 
    std::map<int, int> hist;
    for (int n = 0; n != 10000; ++n)
        ++hist[d(gen)];
 
    for (auto [x, y] : hist)
        std::cout << std::hex << x << ' '
                  << std::string(y / 100, '*') << '\n';
}

Possible output:

0 *
1 *******
2 **************
3 *******************
4 *******************
5 ***************
6 **********
7 *****
8 **
9 *
a
b
c
d
Weisstein, Eric W. "Poisson Distribution." From MathWorld — A Wolfram Web Resource.

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