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// class bernoulli_distribution
12
13// template<class _URNG> result_type operator()(_URNG& g);
14
15#include <random>
16#include <numeric>
17#include <vector>
18#include <cassert>
19#include <cstddef>
20
21#include "test_macros.h"
22
23template <class T>
24inline
25T
26sqr(T x)
27{
28 return x * x;
29}
30
31int main(int, char**)
32{
33 {
34 typedef std::bernoulli_distribution D;
35 typedef std::minstd_rand G;
36 G g;
37 D d(.75);
38 const int N = 100000;
39 std::vector<D::result_type> u;
40 for (int i = 0; i < N; ++i)
41 u.push_back(d(g));
42 double mean = std::accumulate(u.begin(), u.end(),
43 double(0)) / u.size();
44 double var = 0;
45 double skew = 0;
46 double kurtosis = 0;
47 for (std::size_t i = 0; i < u.size(); ++i)
48 {
49 double dbl = (u[i] - mean);
50 double d2 = sqr(dbl);
51 var += d2;
52 skew += dbl * d2;
53 kurtosis += d2 * d2;
54 }
55 var /= u.size();
56 double dev = std::sqrt(x: var);
57 skew /= u.size() * dev * var;
58 kurtosis /= u.size() * var * var;
59 kurtosis -= 3;
60 double x_mean = d.p();
61 double x_var = d.p()*(1-d.p());
62 double x_skew = (1 - 2 * d.p())/std::sqrt(x: x_var);
63 double x_kurtosis = (6 * sqr(d.p()) - 6 * d.p() + 1)/x_var;
64 assert(std::abs((mean - x_mean) / x_mean) < 0.01);
65 assert(std::abs((var - x_var) / x_var) < 0.01);
66 assert(std::abs((skew - x_skew) / x_skew) < 0.01);
67 assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.02);
68 }
69 {
70 typedef std::bernoulli_distribution D;
71 typedef std::minstd_rand G;
72 G g;
73 D d(.25);
74 const int N = 100000;
75 std::vector<D::result_type> u;
76 for (int i = 0; i < N; ++i)
77 u.push_back(d(g));
78 double mean = std::accumulate(u.begin(), u.end(),
79 double(0)) / u.size();
80 double var = 0;
81 double skew = 0;
82 double kurtosis = 0;
83 for (std::size_t i = 0; i < u.size(); ++i)
84 {
85 double dbl = (u[i] - mean);
86 double d2 = sqr(dbl);
87 var += d2;
88 skew += dbl * d2;
89 kurtosis += d2 * d2;
90 }
91 var /= u.size();
92 double dev = std::sqrt(x: var);
93 skew /= u.size() * dev * var;
94 kurtosis /= u.size() * var * var;
95 kurtosis -= 3;
96 double x_mean = d.p();
97 double x_var = d.p()*(1-d.p());
98 double x_skew = (1 - 2 * d.p())/std::sqrt(x: x_var);
99 double x_kurtosis = (6 * sqr(d.p()) - 6 * d.p() + 1)/x_var;
100 assert(std::abs((mean - x_mean) / x_mean) < 0.01);
101 assert(std::abs((var - x_var) / x_var) < 0.01);
102 assert(std::abs((skew - x_skew) / x_skew) < 0.01);
103 assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.02);
104 }
105
106 return 0;
107}
108

source code of libcxx/test/std/numerics/rand/rand.dist/rand.dist.bern/rand.dist.bern.bernoulli/eval.pass.cpp