std::chi_squared_distribution
From cppreference.com
                    
                                        
                    
                    
                                                            
                    |   Defined in header  <random>
  | 
||
|   template< class RealType = double > class chi_squared_distribution;  | 
(since C++11) | |
The chi_squared_distribution produces random numbers x>0 according to the Chi-squared distribution:
- f(x;n) = 
x(n/2)-1 
e-x/2Γ(n/2) 2n/2 
 
Γ is the Gamma function (See also std::tgamma) and n are the degrees of freedom (default 1).
std::chi_squared_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 degrees of freedom (n) distribution parameter  (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 <random> #include <iomanip> #include <map> #include <algorithm> #include <iostream> #include <vector> #include <cmath> 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((Height > 0) && (BarWidth > 0) && (Padding >= 0) && (Offset >= 0)); 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(*cbegin(s)) V; V e : s) qr.push_back(std::div(std::lerp(V(0), Height*8, (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 χ2 = [&gen](const float dof) { std::chi_squared_distribution<float> d{ dof /* n */ }; const int norm = 1'00'00; const float cutoff = 0.002f; 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 << "dof = " << dof << ":\n"; draw_vbars<4,3>(bars); for (int n : indices) { std::cout << "" << std::setw(2) << n << " "; } std::cout << "\n\n"; }; for (float dof : {1.f, 2.f, 3.f, 4.f, 6.f, 9.f}) χ2(dof); }
Possible output:
dof = 1:
███                                 ┬ 0.5271
███                                 │
███ ███                             │
███ ███ ▇▇▇ ▃▃▃ ▂▂▂ ▁▁▁ ▁▁▁ ▁▁▁ ▁▁▁ ┴ 0.003
 0   1   2   3   4   5   6   7   8  
 
dof = 2:
    ███                                     ┬ 0.3169
▆▆▆ ███ ▃▃▃                                 │
███ ███ ███ ▄▄▄                             │
███ ███ ███ ███ ▇▇▇ ▄▄▄ ▃▃▃ ▂▂▂ ▁▁▁ ▁▁▁ ▁▁▁ ┴ 0.004
 0   1   2   3   4   5   6   7   8   9  10  
 
dof = 3:
    ███ ▃▃▃                                         ┬ 0.2439
    ███ ███ ▄▄▄                                     │
▃▃▃ ███ ███ ███ ▇▇▇ ▁▁▁                             │
███ ███ ███ ███ ███ ███ ▆▆▆ ▄▄▄ ▃▃▃ ▂▂▂ ▁▁▁ ▁▁▁ ▁▁▁ ┴ 0.0033
 0   1   2   3   4   5   6   7   8   9  10  11  12  
 
dof = 4:
    ▂▂▂ ███ ▃▃▃                                                 ┬ 0.1864
    ███ ███ ███ ███ ▂▂▂                                         │
    ███ ███ ███ ███ ███ ▅▅▅ ▁▁▁                                 │
▅▅▅ ███ ███ ███ ███ ███ ███ ███ ▆▆▆ ▄▄▄ ▃▃▃ ▂▂▂ ▂▂▂ ▁▁▁ ▁▁▁ ▁▁▁ ┴ 0.0026
 0   1   2   3   4   5   6   7   8   9  10  11  12  13  14  15  
 
dof = 6:
            ▅▅▅ ▇▇▇ ███ ▂▂▂                                                 ┬ 0.1351
        ▅▅▅ ███ ███ ███ ███ ▇▇▇ ▁▁▁                                         │
    ▁▁▁ ███ ███ ███ ███ ███ ███ ███ ▅▅▅ ▂▂▂                                 │
▁▁▁ ███ ███ ███ ███ ███ ███ ███ ███ ███ ███ ███ ▅▅▅ ▄▄▄ ▃▃▃ ▂▂▂ ▁▁▁ ▁▁▁ ▁▁▁ ┴ 0.0031
 0   1   2   3   4   5   6   7   8   9  10  11  12  13  14  15  16  17  18  
 
dof = 9:
            ▅▅▅ ▇▇▇ ███ ███ ▄▄▄ ▂▂▂                                                 ┬ 0.1044
        ▃▃▃ ███ ███ ███ ███ ███ ███ ▅▅▅ ▁▁▁                                         │
    ▄▄▄ ███ ███ ███ ███ ███ ███ ███ ███ ███ ▆▆▆ ▃▃▃                                 │
▄▄▄ ███ ███ ███ ███ ███ ███ ███ ███ ███ ███ ███ ███ ███ ▆▆▆ ▄▄▄ ▃▃▃ ▂▂▂ ▁▁▁ ▁▁▁ ▁▁▁ ┴ 0.0034
 2   3   4   5   6   7   8   9  10  11  12  13  14  15  16  17  18  19  20  21  22External links
- Weisstein, Eric W. "Chi-Squared Distribution." From MathWorld--A Wolfram Web Resource.
 - Chi-squared distribution. From Wikipedia.