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 <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 std::minstd_rand G;
39 G g;
40 D d(5, 4);
41 const int N = 1000000;
42 std::vector<D::result_type> u;
43 for (int i = 0; i < N; ++i)
44 u.push_back(d(g));
45 double mean = std::accumulate(u.begin(), u.end(), 0.0) / u.size();
46 double var = 0;
47 double skew = 0;
48 double kurtosis = 0;
49 for (std::size_t i = 0; i < u.size(); ++i)
50 {
51 double dbl = (u[i] - mean);
52 double d2 = sqr(dbl);
53 var += d2;
54 skew += dbl * d2;
55 kurtosis += d2 * d2;
56 }
57 var /= u.size();
58 double dev = std::sqrt(x: var);
59 skew /= u.size() * dev * var;
60 kurtosis /= u.size() * var * var;
61 kurtosis -= 3;
62 double x_mean = d.mean();
63 double x_var = sqr(d.stddev());
64 double x_skew = 0;
65 double x_kurtosis = 0;
66 assert(std::abs((mean - x_mean) / x_mean) < 0.01);
67 assert(std::abs((var - x_var) / x_var) < 0.01);
68 assert(std::abs(skew - x_skew) < 0.01);
69 assert(std::abs(kurtosis - x_kurtosis) < 0.01);
70 }
71
72 return 0;
73}
74

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