libcxx/test/std/numerics/rand/rand.dist/rand.dist.uni/rand.dist.uni.int/eval_param.pass.cpp

   1 //===----------------------------------------------------------------------===//
   2 //
   3 // Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
   4 // See https://llvm.org/LICENSE.txt for license information.
   5 // SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
   6 //
   7 //===----------------------------------------------------------------------===//
   8
   9 // <random>
  10
  11 // template<class _IntType = int>
  12 // class uniform_int_distribution
  13
  14 // template<class _URNG> result_type operator()(_URNG& g, const param_type& parm);
  15
  16 #include <random>
  17 #include <cassert>
  18 #include <vector>
  19 #include <numeric>
  20 #include <cstddef>
  21
  22 #include "test_macros.h"
  23
  24 template <class T>
  25 inline
  26 T
  27 sqr(T x)
  28 {
  29     return x * x;
  30 }
  31
  32 int main(int, char**)
  33 {
  34     {
  35         typedef std::uniform_int_distribution<> D;
  36         typedef std::minstd_rand G;
  37         typedef D::param_type P;
  38         G g;
  39         D d(5, 100);
  40         P p(-10, 20);
  41         const int N = 100000;
  42         std::vector<D::result_type> u;
  43         for (int i = 0; i < N; ++i)
  44         {
  45             D::result_type v = d(g, p);
  46             assert(p.a() <= v && v <= p.b());
  47             u.push_back(v);
  48         }
  49         double mean = std::accumulate(u.begin(), u.end(),
  50                                               double(0)) / u.size();
  51         double var = 0;
  52         double skew = 0;
  53         double kurtosis = 0;
  54         for (std::size_t i = 0; i < u.size(); ++i)
  55         {
  56             double dbl = (u[i] - mean);
  57             double d2 = sqr(dbl);
  58             var += d2;
  59             skew += dbl * d2;
  60             kurtosis += d2 * d2;
  61         }
  62         var /= u.size();
  63         double dev = std::sqrt(var);
  64         skew /= u.size() * dev * var;
  65         kurtosis /= u.size() * var * var;
  66         kurtosis -= 3;
  67         double x_mean = ((double)p.a() + p.b()) / 2;
  68         double x_var = (sqr((double)p.b() - p.a() + 1) - 1) / 12;
  69         double x_skew = 0;
  70         double x_kurtosis = -6. * (sqr((double)p.b() - p.a() + 1) + 1) /
  71                             (5. * (sqr((double)p.b() - p.a() + 1) - 1));
  72         assert(std::abs((mean - x_mean) / x_mean) < 0.01);
  73         assert(std::abs((var - x_var) / x_var) < 0.01);
  74         assert(std::abs(skew - x_skew) < 0.01);
  75         assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
  76     }
  77
  78   return 0;
  79 }