exponential_distribution Class

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

Generates an exponential distribution.

Syntax

class exponential_distribution  
   {  
   public:  // types  
   typedef RealType result_type;  
   struct param_type;  // constructors and reset functions  
   explicit exponential_distribution(RealType 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  
   RealType 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>.

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.

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

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);  
}  
  

Output

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(RealType 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<RealType> distribution_type;
param_type(RealType lambda = 1.0); RealType lambda() const; .....
bool operator==(const param_type& right) const; bool operator!=(const param_type& right) const; };

Parameters

See parent topic exponential_distribution Class.

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>