# exponential_distribution Class

Visual Studio 2013

Generates an exponential distribution.

```template<class RealType = double>
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.

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

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

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
```