exponential_distribution Class

Generates an exponential distribution.

Syntax

template<class RealType = double>
class exponential_distribution
   {
public:
   // types
   typedef RealType result_type;
   struct param_type;

   // constructors and reset functions
   explicit exponential_distribution(result_type lambda = 1.0);
   explicit exponential_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
   result_type lambda() const;
   param_type param() const;
   void param(const param_type& parm);
   result_type min() const;
   result_type max() const;
   };

Parameters

RealType
The floating-point result type, defaults to double. For possible types, see <random>.

URNG
The 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, or type double if none is provided, distributed according to the Exponential Distribution. The following table links to articles about individual members.

exponential_distribution exponential_distribution::lambda exponential_distribution::param
exponential_distribution::operator() param_type

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

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

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

For detailed information about the exponential distribution, see the Wolfram MathWorld article Exponential Distribution.

Example

// compile with: /EHsc /W4
#include <random>
#include <iostream>
#include <iomanip>
#include <string>
#include <map>

void test(const double l, const int s) {

    // uncomment to use a non-deterministic generator
    //    std::random_device gen;
    std::mt19937 gen(1701);

    std::exponential_distribution<> distr(l);

    std::cout << std::endl;
    std::cout << "min() == " << distr.min() << std::endl;
    std::cout << "max() == " << distr.max() << std::endl;
    std::cout << "lambda() == " << std::fixed << std::setw(11) << std::setprecision(10) << distr.lambda() << std::endl;

    // generate the distribution as a histogram
    std::map<double, int> histogram;
    for (int i = 0; i < s; ++i) {
        ++histogram[distr(gen)];
    }

    // print results
    std::cout << "Distribution for " << s << " samples:" << std::endl;
    int counter = 0;
    for (const auto& elem : histogram) {
        std::cout << std::fixed << std::setw(11) << ++counter << ": "
            << std::setw(14) << std::setprecision(10) << elem.first << std::endl;
    }
    std::cout << std::endl;
}

int main()
{
    double l_dist = 0.5;
    int samples = 10;

    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 'lambda' distribution parameter (must be greater than zero): ";
    std::cin >> l_dist;
    std::cout << "Enter an integer value for the sample count: ";
    std::cin >> samples;

    test(l_dist, samples);
}
Use CTRL-Z to bypass data entry and run using default values.
Enter a floating point value for the 'lambda' distribution parameter (must be greater than zero): 1
Enter an integer value for the sample count: 10

min() == 0
max() == 1.79769e+308
lambda() == 1.0000000000
Distribution for 10 samples:
    1: 0.0936880533
    2: 0.1225944894
    3: 0.6443593183
    4: 0.6551171649
    5: 0.7313457551
    6: 0.7313557977
    7: 0.7590097389
    8: 1.4466885214
    9: 1.6434088411
    10: 2.1201210996

Requirements

Header: <random>

Namespace: std

exponential_distribution::exponential_distribution

Constructs the distribution.

explicit exponential_distribution(result_type lambda = 1.0);
explicit exponential_distribution(const param_type& parm);

Parameters

lambda
The lambda distribution parameter.

parm
The parameter package used to construct the distribution.

Remarks

Precondition: 0.0 < lambda

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

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.

exponential_distribution::param_type

Stores the parameters of the distribution.

struct param_type {
   typedef exponential_distribution<result_type> distribution_type;
   param_type(result_type lambda = 1.0);
   result_type lambda() const;

   bool operator==(const param_type& right) const;
   bool operator!=(const param_type& right) const;
   };

Parameters

lambda
The lambda distribution parameter.

right
The param_type object to compare to this.

Remarks

Precondition: 0.0 < lambda

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>