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

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