std::cauchy_distribution
From cppreference.com
Defined in header <random>
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template< class RealType = double > class cauchy_distribution; |
(since C++11) | |
Produces random numbers according to a Cauchy distribution (also called Lorentz distribution):
- f(x; a,b) = ⎛
⎜
⎝bπ ⎡
⎢
⎣1 + ⎛
⎜
⎝
⎞x - a b
⎟
⎠2
⎤
⎥
⎦⎞
⎟
⎠-1
std::cauchy_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 (C++11)
|
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 | |
(C++11) |
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
Run this code
#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, class Seq> void draw_vbars(Seq&& s, const bool DrawMinMax = true) { static_assert(0 < Height and 0 < BarWidth and 0 <= Padding and 0 <= Offset); auto cout_n = [](auto&& v, int n = 1) { 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 (typedef decltype(*std::cbegin(s)) V; V e : s) qr.push_back(std::div(std::lerp(V(0), 8 * Height, (e - *min) / (*max - *min)), 8)); for (auto h{Height}; h-- > 0; cout_n('\n')) { cout_n(' ', Offset); for (auto dv : qr) { const auto q{dv.quot}, r{dv.rem}; unsigned char d[]{0xe2, 0x96, 0x88, 0}; // Full Block: '█' q < h ? d[0] = ' ', d[1] = 0 : q == h ? d[2] -= (7 - r) : 0; cout_n(d, BarWidth), cout_n(' ', Padding); } if (DrawMinMax && Height > 1) Height - 1 == h ? std::cout << "┬ " << *max: h ? std::cout << "│ " : std::cout << "┴ " << *min; } } int main() { std::random_device rd{}; std::mt19937 gen{rd()}; auto cauchy = [&gen](const float x0, const float 𝛾) { std::cauchy_distribution<float> d{x0 /* a */, 𝛾 /* b */}; const int norm = 1'00'00; const float cutoff = 0.005f; 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 (auto const& [n, p] : hist) if (float x = p * (1.0 / norm); cutoff < x) { bars.push_back(x); indices.push_back(n); } std::cout << "x₀ = " << x0 << ", 𝛾 = " << 𝛾 << ":\n"; draw_vbars<4,3>(bars); for (int n : indices) std::cout << std::setw(2) << n << " "; std::cout << "\n\n"; }; cauchy(/* x₀ = */ -2.0f, /* 𝛾 = */ 0.50f); cauchy(/* x₀ = */ +0.0f, /* 𝛾 = */ 1.25f); }
Possible output:
x₀ = -2, 𝛾 = 0.5: ███ ┬ 0.5006 ███ │ ▂▂▂ ███ ▁▁▁ │ ▁▁▁ ▁▁▁ ▁▁▁ ▃▃▃ ███ ███ ███ ▂▂▂ ▁▁▁ ▁▁▁ ▁▁▁ ┴ 0.0076 -7 -6 -5 -4 -3 -2 -1 0 1 2 3 x₀ = 0, 𝛾 = 1.25: ███ ┬ 0.2539 ▅▅▅ ███ ▃▃▃ │ ▁▁▁ ███ ███ ███ ▁▁▁ │ ▁▁▁ ▁▁▁ ▁▁▁ ▁▁▁ ▃▃▃ ▅▅▅ ███ ███ ███ ███ ███ ▅▅▅ ▃▃▃ ▂▂▂ ▁▁▁ ▁▁▁ ▁▁▁ ┴ 0.0058 -8 -7 -6 -5 -4 -3 -2 -1 0 1 2 3 4 5 6 7 9
External links
Weisstein, Eric W. "Cauchy Distribution." From MathWorld — A Wolfram Web Resource. |