# extreme_value_distribution Class

Visual Studio 2015

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Generates an extreme value distribution.

## Syntax

```class extreme_value_distribution
{
public:  // types
typedef RealType result_type;
struct param_type;  // constructor and reset functions
explicit extreme_value_distribution(RealType a = 0.0, RealType b = 1.0);
explicit extreme_value_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 a() const;
RealType b() 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 Extreme Value Distribution. The following table links to articles about individual members.

extreme_value_distribution::extreme_value_distribution`extreme_value_distribution::a``extreme_value_distribution::param`
`extreme_value_distribution::operator()``extreme_value_distribution::b`extreme_value_distribution::param_type

The property functions `a()` and `b()` return their respective values for stored distribution parameters `a` and `b`.

For detailed information about the extreme value distribution, see the Wolfram MathWorld article Extreme Value Distribution.

## Example

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

void test(const double a, const double b, const int s) {

// uncomment to use a non-deterministic generator
//    std::random_device gen;

std::mt19937 gen(1701);

std::extreme_value_distribution<> distr(a, b);

std::cout << std::endl;
std::cout << "min() == " << distr.min() << std::endl;
std::cout << "max() == " << distr.max() << std::endl;
std::cout << "a() == " << std::fixed << std::setw(11) << std::setprecision(10) << distr.a() << std::endl;
std::cout << "b() == " << std::fixed << std::setw(11) << std::setprecision(10) << distr.b() << 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 a_dist = 0.0;
double b_dist = 1;

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 \'a\' distribution parameter: ";
std::cin >> a_dist;
std::cout << "Enter a floating point value for the \'b\' distribution parameter (must be greater than zero): ";
std::cin >> b_dist;
std::cout << "Enter an integer value for the sample count: ";
std::cin >> samples;

test(a_dist, b_dist, samples);
}

```

## Output

```Use CTRL-Z to bypass data entry and run using default values.
Enter a floating point value for the 'a' distribution parameter: 0
Enter a floating point value for the 'b' distribution parameter (must be greater than zero): 1
Enter an integer value for the sample count: 10

min() == -1.79769e+308
max() == 1.79769e+308
a() == 0.0000000000
b() == 1.0000000000
Distribution for 10 samples:
1: -0.8813940331
2: -0.7698972281
3: 0.2951258007
4: 0.3110450734
5: 0.4210546820
6: 0.4210688771
7: 0.4598857960
8: 1.3155194200
9: 1.5379170046
10: 2.0568757061

```

Namespace: std

## extreme_value_distribution::extreme_value_distribution

Constructs the distribution.

```explicit extreme_value_distribution(RealType a = 0.0, RealType b = 1.0);

explicit extreme_value_distribution(const param_type& parm);

```

### Parameters

`a`
The `a` distribution parameter.

`b`
The `b` distribution parameter.

`parm`
The parameter structure used to construct the distribution.

### Remarks

Precondition: `0.0 < b`

The first constructor constructs an object whose stored `a` value holds the value `a` and whose stored `b` value holds the value `b`.

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.

## extreme_value_distribution::param_type

Stores the parameters of the distribution.

```struct param_type {
typedef extreme_value_distribution<RealType> distribution_type;
param_type(RealType a = 0.0, RealType b = 1.0);
RealType a() const;
RealType b() const;
.....
bool operator==(const param_type& right) const;
bool operator!=(const param_type& right) const;
};

```

### Parameters

See parent topic extreme_value_distribution Class.

### Remarks

Precondition: `0.0 < b`

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.