Defined in header <random> | ||
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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.
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 type | Definition |
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result_type | IntType |
param_type | the type of the parameter set, see RandomNumberDistribution. |
constructs new distribution (public member function) |
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resets the internal state of the distribution (public member function) |
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Generation |
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generates the next random number in the distribution (public member function) |
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Characteristics |
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returns the mean distribution parameter (mean number of occurrences of the event) (public member function) |
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gets or sets the distribution parameter object (public member function) |
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returns the minimum potentially generated value (public member function) |
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returns the maximum potentially generated value (public member function) |
compares two distribution objects (function) |
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performs stream input and output on pseudo-random number distribution (function template) |
#include <iostream> #include <iomanip> #include <string> #include <map> #include <random> 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 p : hist) { std::cout << p.first << ' ' << std::string(p.second/100, '*') << '\n'; } }
Output:
0 * 1 ******* 2 ************** 3 ******************* 4 ******************* 5 *************** 6 ********** 7 ***** 8 ** 9 * 10 11 12 13
Weisstein, Eric W. "Poisson Distribution." From MathWorld--A Wolfram Web Resource.
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