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// REQUIRES: long_tests
10
11// <random>
12
13// template<class RealType = double>
14// class normal_distribution
15
16// template<class _URNG> result_type operator()(_URNG& g, const param_type& parm);
17
18#include <random>
19#include <cassert>
20#include <vector>
21#include <numeric>
22#include <cstddef>
23
24#include "test_macros.h"
25
26template <class T>
27inline
28T
29sqr(T x)
30{
31 return x * x;
32}
33
34int main(int, char**)
35{
36 {
37 typedef std::normal_distribution<> D;
38 typedef D::param_type P;
39 typedef std::minstd_rand G;
40 G g;
41 D d(5, 4);
42 P p(50, .5);
43 const int N = 1000000;
44 std::vector<D::result_type> u;
45 for (int i = 0; i < N; ++i)
46 u.push_back(d(g, p));
47 double mean = std::accumulate(u.begin(), u.end(), 0.0) / u.size();
48 double var = 0;
49 double skew = 0;
50 double kurtosis = 0;
51 for (std::size_t i = 0; i < u.size(); ++i)
52 {
53 double dbl = (u[i] - mean);
54 double d2 = sqr(dbl);
55 var += d2;
56 skew += dbl * d2;
57 kurtosis += d2 * d2;
58 }
59 var /= u.size();
60 double dev = std::sqrt(x: var);
61 skew /= u.size() * dev * var;
62 kurtosis /= u.size() * var * var;
63 kurtosis -= 3;
64 double x_mean = p.mean();
65 double x_var = sqr(p.stddev());
66 double x_skew = 0;
67 double x_kurtosis = 0;
68 assert(std::abs((mean - x_mean) / x_mean) < 0.01);
69 assert(std::abs((var - x_var) / x_var) < 0.01);
70 assert(std::abs(skew - x_skew) < 0.01);
71 assert(std::abs(kurtosis - x_kurtosis) < 0.01);
72 }
73
74 return 0;
75}
76

source code of libcxx/test/std/numerics/rand/rand.dist/rand.dist.norm/rand.dist.norm.normal/eval_param.pass.cpp