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 RealType = double>
12 // class uniform_real_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
sqr(T x)27 sqr(T x)
28 {
29     return x * x;
30 }
31 
main(int,char **)32 int main(int, char**)
33 {
34     {
35         typedef std::uniform_real_distribution<> D;
36         typedef std::minstd_rand G;
37         typedef D::param_type P;
38         G g;
39         D d(5.5, 25);
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         D::result_type mean = std::accumulate(u.begin(), u.end(),
50                                               D::result_type(0)) / u.size();
51         D::result_type var = 0;
52         D::result_type skew = 0;
53         D::result_type kurtosis = 0;
54         for (std::size_t i = 0; i < u.size(); ++i)
55         {
56             D::result_type dbl = (u[i] - mean);
57             D::result_type d2 = sqr(dbl);
58             var += d2;
59             skew += dbl * d2;
60             kurtosis += d2 * d2;
61         }
62         var /= u.size();
63         D::result_type dev = std::sqrt(var);
64         skew /= u.size() * dev * var;
65         kurtosis /= u.size() * var * var;
66         kurtosis -= 3;
67         D::result_type x_mean = (p.a() + p.b()) / 2;
68         D::result_type x_var = sqr(p.b() - p.a()) / 12;
69         D::result_type x_skew = 0;
70         D::result_type x_kurtosis = -6./5;
71         assert(std::abs((mean - x_mean) / x_mean) < 0.01);
72         assert(std::abs((var - x_var) / x_var) < 0.01);
73         assert(std::abs(skew - x_skew) < 0.01);
74         assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
75     }
76 
77   return 0;
78 }
79