std::extreme_value_distribution
Defined in header <random> |
||
|---|---|---|
template< class RealType = double > class extreme_value_distribution; |
(since C++11) |
Produces random numbers according to the extreme value distribution (it is also known as Gumbel Type I, log-Weibull, Fisher-Tippett Type I): \({\small p(x;a,b) = \frac{1}{b} \exp{(\frac{a-x}{b}-\exp{(\frac{a-x}{b})})} }\)p(x;a,b) =
1/b exp ⎛⎜
⎝a-x/b - exp⎛
⎜
⎝a-x/b⎞
⎟
⎠⎞
⎟
⎠
std::extreme_value_distribution satisfies all requirements of RandomNumberDistribution.
Template parameters
| RealType | - | The result type generated by the generator. The effect is undefined if this is not one of float, double, or long double. |
Member types
| Member type | Definition |
|---|---|
result_type |
RealType |
param_type(C++11) |
the type of the parameter set, see RandomNumberDistribution. |
Member functions
|
(C++11)
|
constructs new distribution (public member function) |
|
(C++11)
|
resets the internal state of the distribution (public member function) |
Generation |
|
|
(C++11)
|
generates the next random number in the distribution (public member function) |
Characteristics |
|
| returns the distribution parameters (public member function) |
|
|
(C++11)
|
gets or sets the distribution parameter object (public member function) |
|
(C++11)
|
returns the minimum potentially generated value (public member function) |
|
(C++11)
|
returns the maximum potentially generated value (public member function) |
Non-member functions
|
(C++11)(C++11)(removed in C++20)
|
compares two distribution objects (function) |
|
(C++11)
|
performs stream input and output on pseudo-random number distribution (function template) |
Example
#include <algorithm>
#include <cmath>
#include <iomanip>
#include <iostream>
#include <map>
#include <random>
#include <vector>
template<int Height = 5, int BarWidth = 1, int Padding = 1, int Offset = 0,
bool MinMax = true, class S>
void draw_vbars(S const& s)
{
static_assert((Height > 0) && (BarWidth > 0) && (Padding >= 0) && (Offset >= 0));
const auto repeat_cout = [](auto const& v, int n)
{
while (n-- > 0)
std::cout << v;
};
const auto [min, max] = std::minmax_element(std::cbegin(s), std::cend(s));
std::vector<std::div_t> qr;
for (float e : s) {
qr.push_back(std::div(std::lerp(0.f, Height * 8 , (e - *min) / (*max - *min)), 8));
}
for (auto h{Height}; h-- > 0 ;) {
repeat_cout(' ', Offset);
for (auto [q, r] : qr) {
char d[] = "█"; // == { 0xe2, 0x96, 0x88, 0 }
if (q < h) {
repeat_cout(' ', BarWidth);
} else {
if (q == h) {
d[2] -= (7 - r);
}
repeat_cout(d, BarWidth);
}
repeat_cout(' ', Padding);
}
if (MinMax && Height > 1) {
if (h == Height - 1)
std::cout << "┬ " << *max;
else if (h == 0)
std::cout << "┴ " << *min;
else
std::cout << "│";
}
std::cout << '\n';
}
}
int main()
{
std::random_device rd{};
std::mt19937 gen{rd()};
std::extreme_value_distribution<> d{-1.618f, 1.618f};
const int norm = 10'000;
const float cutoff = 0.000'3f;
std::map<int, int> hist{};
for(int n=0; n<norm; ++n) {
++hist[std::round(d(gen))];
}
std::vector<float> bars;
std::vector<int> indices;
for(const auto [n,p] : hist) {
float x = p*(1.0f/norm);
if (x > cutoff) {
bars.push_back(x);
indices.push_back(n);
}
}
draw_vbars<8,4>(bars);
for (int n : indices) {
std::cout << " " << std::setw(2) << n << " ";
}
std::cout << '\n';
}
Possible output:
████ ▅▅▅▅ ┬ 0.2186
████ ████ │
▁▁▁▁ ████ ████ ▇▇▇▇ │
████ ████ ████ ████ │
████ ████ ████ ████ ▆▆▆▆ │
████ ████ ████ ████ ████ ▁▁▁▁ │
▄▄▄▄ ████ ████ ████ ████ ████ ████ ▃▃▃▃ │
▁▁▁▁ ████ ████ ████ ████ ████ ████ ████ ████ ▆▆▆▆ ▃▃▃▃ ▂▂▂▂ ▁▁▁▁ ▁▁▁▁ ▁▁▁▁ ▁▁▁▁ ┴ 0.0005
-5 -4 -3 -2 -1 0 1 2 3 4 5 6 7 8 9 10
External links
Weisstein, Eric W. "Extreme Value Distribution." From MathWorld--A Wolfram Web Resource.
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https://en.cppreference.com/w/cpp/numeric/random/extreme_value_distribution
