xref: /llvm-project/libcxx/test/std/numerics/rand/rand.dist/rand.dist.uni/rand.dist.uni.int/eval_param.pass.cpp (revision 09e3a360581dc36d0820d3fb6da9bd7cfed87b5d)
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 <cmath>
19 #include <cstddef>
20 #include <numeric>
21 #include <vector>
22 
23 #include "test_macros.h"
24 
25 template <class T>
26 inline
27 T
28 sqr(T x)
29 {
30     return x * x;
31 }
32 
33 int main(int, char**)
34 {
35     {
36         typedef std::uniform_int_distribution<> D;
37         typedef std::minstd_rand G;
38         typedef D::param_type P;
39         G g;
40         D d(5, 100);
41         P p(-10, 20);
42         const int N = 100000;
43         std::vector<D::result_type> u;
44         for (int i = 0; i < N; ++i)
45         {
46             D::result_type v = d(g, p);
47             assert(p.a() <= v && v <= p.b());
48             u.push_back(v);
49         }
50         double mean = std::accumulate(u.begin(), u.end(),
51                                               double(0)) / u.size();
52         double var = 0;
53         double skew = 0;
54         double kurtosis = 0;
55         for (std::size_t i = 0; i < u.size(); ++i)
56         {
57             double dbl = (u[i] - mean);
58             double d2 = sqr(dbl);
59             var += d2;
60             skew += dbl * d2;
61             kurtosis += d2 * d2;
62         }
63         var /= u.size();
64         double dev = std::sqrt(var);
65         skew /= u.size() * dev * var;
66         kurtosis /= u.size() * var * var;
67         kurtosis -= 3;
68         double x_mean = ((double)p.a() + p.b()) / 2;
69         double x_var = (sqr((double)p.b() - p.a() + 1) - 1) / 12;
70         double x_skew = 0;
71         double x_kurtosis = -6. * (sqr((double)p.b() - p.a() + 1) + 1) /
72                             (5. * (sqr((double)p.b() - p.a() + 1) - 1));
73         assert(std::abs((mean - x_mean) / x_mean) < 0.01);
74         assert(std::abs((var - x_var) / x_var) < 0.01);
75         assert(std::abs(skew - x_skew) < 0.01);
76         assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);
77     }
78 
79   return 0;
80 }
81