extreme_value_distribution Class
The latest version of this topic can be found at extreme_value_distribution Class.
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 more information about distribution classes and their members, see <random>.
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
Requirements
Header: <random>
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.