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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-exception6//7//===----------------------------------------------------------------------===//8 9// <random>10 11// template<class RealType = double>12// class uniform_real_distribution13 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 25template <class T>26inline27T28sqr(T x)29{30    return x * x;31}32 33int main(int, char**)34{35    {36        typedef std::uniform_real_distribution<> D;37        typedef std::minstd_rand G;38        typedef D::param_type P;39        G g;40        D d(5.5, 25);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        D::result_type mean = std::accumulate(u.begin(), u.end(),51                                              D::result_type(0)) / u.size();52        D::result_type var = 0;53        D::result_type skew = 0;54        D::result_type kurtosis = 0;55        for (std::size_t i = 0; i < u.size(); ++i)56        {57            D::result_type dbl = (u[i] - mean);58            D::result_type d2 = sqr(dbl);59            var += d2;60            skew += dbl * d2;61            kurtosis += d2 * d2;62        }63        var /= u.size();64        D::result_type dev = std::sqrt(var);65        skew /= u.size() * dev * var;66        kurtosis /= u.size() * var * var;67        kurtosis -= 3;68        D::result_type x_mean = (p.a() + p.b()) / 2;69        D::result_type x_var = sqr(p.b() - p.a()) / 12;70        D::result_type x_skew = 0;71        D::result_type x_kurtosis = -6./5;72        assert(std::abs((mean - x_mean) / x_mean) < 0.01);73        assert(std::abs((var - x_var) / x_var) < 0.01);74        assert(std::abs(skew - x_skew) < 0.01);75        assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01);76    }77 78  return 0;79}80