geometric_distribution Class

Generates a geometric distribution.

Syntax

template<class IntType = int>
class geometric_distribution {
public:
    // types
    typedef IntType result_type;
    struct param_type;

    // constructors and reset functions
    explicit geometric_distribution(double p = 0.5);
    explicit geometric_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;
};

Parameters

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

URNG
The uniform random number generator engine. For possible types, see <random>.

Remarks

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

geometric_distribution geometric_distribution::p geometric_distribution::param
geometric_distribution::operator() param_type

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

The property member param() sets or returns the param_type stored distribution parameter package.

The min() and max() member functions return the smallest possible result and largest possible result, respectively.

The reset() member function discards any cached values, so that the result of the next call to operator() does not depend on any values obtained from the engine before the call.

The operator() member functions return the next generated value based on the URNG engine, either from the current parameter package, or the specified parameter package.

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

For detailed information about the chi-squared distribution, see the Wolfram MathWorld article Geometric 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::geometric_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.p() << 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 = 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 floating point value for the \'p\' distribution parameter: ";
    std::cin >> p_dist;
    std::cout << "Enter an integer value for the sample count: ";
    std::cin >> samples;

    test(p_dist, samples);
}

First test:

Use CTRL-Z to bypass data entry and run using default values.
Enter a floating point value for the 'p' distribution parameter: .5
Enter an integer value for the sample count: 100

min() == 0
max() == 2147483647
p() == 0.5000000000
Distribution for 100 samples:
    0 :::::::::::::::::::::::::::::::::::::::::::::::::::::
    1 ::::::::::::::::::::::::::
    2 ::::::::::::
    3 ::::::
    4 ::
    5 :

Second test:

Use CTRL-Z to bypass data entry and run using default values.
Enter a floating point value for the 'p' distribution parameter: .1
Enter an integer value for the sample count: 100

min() == 0
max() == 2147483647
p() == 0.1000000000
Distribution for 100 samples:
    0 :::::::::
    1 :::::::::::
    2 ::::::::::
    3 :::::::
    4 :::::
    5 ::::::::
    6 :::
    7 ::::::
    8 :::::::
    9 :::::
   10 :::
   11 :::
   12 ::
   13 :
   14 :::
   15 ::
   16 :::
   17 :::
   20 :::::
   21 :
   29 :
   32 :
   35 :

Requirements

Header: <random>

Namespace: std

geometric_distribution::geometric_distribution

Constructs the distribution.

explicit geometric_distribution(double p = 0.5);
explicit geometric_distribution(const param_type& parm);

Parameters

p
The p distribution parameter.

parm
The parameter structure used to construct the distribution.

Remarks

Precondition: 0.0 < p && 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.

geometric_distribution::param_type

Stores the parameters of the distribution.

struct param_type {
   typedef geometric_distribution<result_type> 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

p
The p distribution parameter.

right
The param_type instance to compare this to.

Remarks

Precondition: 0.0 < p && 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>