197dc2f35c3d0d797ece43f5598023c6952144f37Howard Hinnant//===----------------------------------------------------------------------===// 297dc2f35c3d0d797ece43f5598023c6952144f37Howard Hinnant// 397dc2f35c3d0d797ece43f5598023c6952144f37Howard Hinnant// The LLVM Compiler Infrastructure 497dc2f35c3d0d797ece43f5598023c6952144f37Howard Hinnant// 5b64f8b07c104c6cc986570ac8ee0ed16a9f23976Howard Hinnant// This file is dual licensed under the MIT and the University of Illinois Open 6b64f8b07c104c6cc986570ac8ee0ed16a9f23976Howard Hinnant// Source Licenses. See LICENSE.TXT for details. 797dc2f35c3d0d797ece43f5598023c6952144f37Howard Hinnant// 897dc2f35c3d0d797ece43f5598023c6952144f37Howard Hinnant//===----------------------------------------------------------------------===// 9d9144e8d1783617b279146f397a6ab3defefefc4Jonathan Roelofs// 10d9144e8d1783617b279146f397a6ab3defefefc4Jonathan Roelofs// REQUIRES: long_tests 1197dc2f35c3d0d797ece43f5598023c6952144f37Howard Hinnant 1297dc2f35c3d0d797ece43f5598023c6952144f37Howard Hinnant// <random> 1397dc2f35c3d0d797ece43f5598023c6952144f37Howard Hinnant 1497dc2f35c3d0d797ece43f5598023c6952144f37Howard Hinnant// template<class RealType = double> 1597dc2f35c3d0d797ece43f5598023c6952144f37Howard Hinnant// class chi_squared_distribution 1697dc2f35c3d0d797ece43f5598023c6952144f37Howard Hinnant 1797dc2f35c3d0d797ece43f5598023c6952144f37Howard Hinnant// template<class _URNG> result_type operator()(_URNG& g); 1897dc2f35c3d0d797ece43f5598023c6952144f37Howard Hinnant 1997dc2f35c3d0d797ece43f5598023c6952144f37Howard Hinnant#include <random> 2097dc2f35c3d0d797ece43f5598023c6952144f37Howard Hinnant#include <cassert> 2197dc2f35c3d0d797ece43f5598023c6952144f37Howard Hinnant#include <vector> 2297dc2f35c3d0d797ece43f5598023c6952144f37Howard Hinnant#include <numeric> 23a9bcd3dae859f02ab496d175d50840f43a2d4ed2Stephan T. Lavavej#include <cstddef> 2497dc2f35c3d0d797ece43f5598023c6952144f37Howard Hinnant 2597dc2f35c3d0d797ece43f5598023c6952144f37Howard Hinnanttemplate <class T> 2697dc2f35c3d0d797ece43f5598023c6952144f37Howard Hinnantinline 2797dc2f35c3d0d797ece43f5598023c6952144f37Howard HinnantT 2897dc2f35c3d0d797ece43f5598023c6952144f37Howard Hinnantsqr(T x) 2997dc2f35c3d0d797ece43f5598023c6952144f37Howard Hinnant{ 3097dc2f35c3d0d797ece43f5598023c6952144f37Howard Hinnant return x * x; 3197dc2f35c3d0d797ece43f5598023c6952144f37Howard Hinnant} 3297dc2f35c3d0d797ece43f5598023c6952144f37Howard Hinnant 3397dc2f35c3d0d797ece43f5598023c6952144f37Howard Hinnantint main() 3497dc2f35c3d0d797ece43f5598023c6952144f37Howard Hinnant{ 3597dc2f35c3d0d797ece43f5598023c6952144f37Howard Hinnant { 3697dc2f35c3d0d797ece43f5598023c6952144f37Howard Hinnant typedef std::chi_squared_distribution<> D; 3797dc2f35c3d0d797ece43f5598023c6952144f37Howard Hinnant typedef std::minstd_rand G; 3897dc2f35c3d0d797ece43f5598023c6952144f37Howard Hinnant G g; 3997dc2f35c3d0d797ece43f5598023c6952144f37Howard Hinnant D d(0.5); 40df40dc6c1a8ca0bf00fb6aec030f69042f61d974Howard Hinnant const int N = 1000000; 4197dc2f35c3d0d797ece43f5598023c6952144f37Howard Hinnant std::vector<D::result_type> u; 4297dc2f35c3d0d797ece43f5598023c6952144f37Howard Hinnant for (int i = 0; i < N; ++i) 43df40dc6c1a8ca0bf00fb6aec030f69042f61d974Howard Hinnant { 44df40dc6c1a8ca0bf00fb6aec030f69042f61d974Howard Hinnant D::result_type v = d(g); 45df40dc6c1a8ca0bf00fb6aec030f69042f61d974Howard Hinnant assert(d.min() < v); 46df40dc6c1a8ca0bf00fb6aec030f69042f61d974Howard Hinnant u.push_back(v); 47df40dc6c1a8ca0bf00fb6aec030f69042f61d974Howard Hinnant } 48df40dc6c1a8ca0bf00fb6aec030f69042f61d974Howard Hinnant double mean = std::accumulate(u.begin(), u.end(), 0.0) / u.size(); 49df40dc6c1a8ca0bf00fb6aec030f69042f61d974Howard Hinnant double var = 0; 50df40dc6c1a8ca0bf00fb6aec030f69042f61d974Howard Hinnant double skew = 0; 51df40dc6c1a8ca0bf00fb6aec030f69042f61d974Howard Hinnant double kurtosis = 0; 52a9bcd3dae859f02ab496d175d50840f43a2d4ed2Stephan T. Lavavej for (std::size_t i = 0; i < u.size(); ++i) 53df40dc6c1a8ca0bf00fb6aec030f69042f61d974Howard Hinnant { 54d6c0cf0ebdfd1d237fe7e07ab3732467dbd14c91Eric Fiselier double dbl = (u[i] - mean); 55d6c0cf0ebdfd1d237fe7e07ab3732467dbd14c91Eric Fiselier double d2 = sqr(dbl); 56df40dc6c1a8ca0bf00fb6aec030f69042f61d974Howard Hinnant var += d2; 57d6c0cf0ebdfd1d237fe7e07ab3732467dbd14c91Eric Fiselier skew += dbl * d2; 58df40dc6c1a8ca0bf00fb6aec030f69042f61d974Howard Hinnant kurtosis += d2 * d2; 59df40dc6c1a8ca0bf00fb6aec030f69042f61d974Howard Hinnant } 6097dc2f35c3d0d797ece43f5598023c6952144f37Howard Hinnant var /= u.size(); 61df40dc6c1a8ca0bf00fb6aec030f69042f61d974Howard Hinnant double dev = std::sqrt(var); 62df40dc6c1a8ca0bf00fb6aec030f69042f61d974Howard Hinnant skew /= u.size() * dev * var; 63df40dc6c1a8ca0bf00fb6aec030f69042f61d974Howard Hinnant kurtosis /= u.size() * var * var; 64df40dc6c1a8ca0bf00fb6aec030f69042f61d974Howard Hinnant kurtosis -= 3; 65df40dc6c1a8ca0bf00fb6aec030f69042f61d974Howard Hinnant double x_mean = d.n(); 66df40dc6c1a8ca0bf00fb6aec030f69042f61d974Howard Hinnant double x_var = 2 * d.n(); 67df40dc6c1a8ca0bf00fb6aec030f69042f61d974Howard Hinnant double x_skew = std::sqrt(8 / d.n()); 68df40dc6c1a8ca0bf00fb6aec030f69042f61d974Howard Hinnant double x_kurtosis = 12 / d.n(); 69d6d1171f2c3f254582ae1d5b9e14cea0ea8e701bHoward Hinnant assert(std::abs((mean - x_mean) / x_mean) < 0.01); 70d6d1171f2c3f254582ae1d5b9e14cea0ea8e701bHoward Hinnant assert(std::abs((var - x_var) / x_var) < 0.01); 71d6d1171f2c3f254582ae1d5b9e14cea0ea8e701bHoward Hinnant assert(std::abs((skew - x_skew) / x_skew) < 0.01); 72d6d1171f2c3f254582ae1d5b9e14cea0ea8e701bHoward Hinnant assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01); 7397dc2f35c3d0d797ece43f5598023c6952144f37Howard Hinnant } 7497dc2f35c3d0d797ece43f5598023c6952144f37Howard Hinnant { 7597dc2f35c3d0d797ece43f5598023c6952144f37Howard Hinnant typedef std::chi_squared_distribution<> D; 7697dc2f35c3d0d797ece43f5598023c6952144f37Howard Hinnant typedef std::minstd_rand G; 7797dc2f35c3d0d797ece43f5598023c6952144f37Howard Hinnant G g; 7897dc2f35c3d0d797ece43f5598023c6952144f37Howard Hinnant D d(1); 79df40dc6c1a8ca0bf00fb6aec030f69042f61d974Howard Hinnant const int N = 1000000; 8097dc2f35c3d0d797ece43f5598023c6952144f37Howard Hinnant std::vector<D::result_type> u; 8197dc2f35c3d0d797ece43f5598023c6952144f37Howard Hinnant for (int i = 0; i < N; ++i) 82df40dc6c1a8ca0bf00fb6aec030f69042f61d974Howard Hinnant { 83df40dc6c1a8ca0bf00fb6aec030f69042f61d974Howard Hinnant D::result_type v = d(g); 84df40dc6c1a8ca0bf00fb6aec030f69042f61d974Howard Hinnant assert(d.min() < v); 85df40dc6c1a8ca0bf00fb6aec030f69042f61d974Howard Hinnant u.push_back(v); 86df40dc6c1a8ca0bf00fb6aec030f69042f61d974Howard Hinnant } 87df40dc6c1a8ca0bf00fb6aec030f69042f61d974Howard Hinnant double mean = std::accumulate(u.begin(), u.end(), 0.0) / u.size(); 88df40dc6c1a8ca0bf00fb6aec030f69042f61d974Howard Hinnant double var = 0; 89df40dc6c1a8ca0bf00fb6aec030f69042f61d974Howard Hinnant double skew = 0; 90df40dc6c1a8ca0bf00fb6aec030f69042f61d974Howard Hinnant double kurtosis = 0; 91a9bcd3dae859f02ab496d175d50840f43a2d4ed2Stephan T. Lavavej for (std::size_t i = 0; i < u.size(); ++i) 92df40dc6c1a8ca0bf00fb6aec030f69042f61d974Howard Hinnant { 93d6c0cf0ebdfd1d237fe7e07ab3732467dbd14c91Eric Fiselier double dbl = (u[i] - mean); 94d6c0cf0ebdfd1d237fe7e07ab3732467dbd14c91Eric Fiselier double d2 = sqr(dbl); 95df40dc6c1a8ca0bf00fb6aec030f69042f61d974Howard Hinnant var += d2; 96d6c0cf0ebdfd1d237fe7e07ab3732467dbd14c91Eric Fiselier skew += dbl * d2; 97df40dc6c1a8ca0bf00fb6aec030f69042f61d974Howard Hinnant kurtosis += d2 * d2; 98df40dc6c1a8ca0bf00fb6aec030f69042f61d974Howard Hinnant } 9997dc2f35c3d0d797ece43f5598023c6952144f37Howard Hinnant var /= u.size(); 100df40dc6c1a8ca0bf00fb6aec030f69042f61d974Howard Hinnant double dev = std::sqrt(var); 101df40dc6c1a8ca0bf00fb6aec030f69042f61d974Howard Hinnant skew /= u.size() * dev * var; 102df40dc6c1a8ca0bf00fb6aec030f69042f61d974Howard Hinnant kurtosis /= u.size() * var * var; 103df40dc6c1a8ca0bf00fb6aec030f69042f61d974Howard Hinnant kurtosis -= 3; 104df40dc6c1a8ca0bf00fb6aec030f69042f61d974Howard Hinnant double x_mean = d.n(); 105df40dc6c1a8ca0bf00fb6aec030f69042f61d974Howard Hinnant double x_var = 2 * d.n(); 106df40dc6c1a8ca0bf00fb6aec030f69042f61d974Howard Hinnant double x_skew = std::sqrt(8 / d.n()); 107df40dc6c1a8ca0bf00fb6aec030f69042f61d974Howard Hinnant double x_kurtosis = 12 / d.n(); 108d6d1171f2c3f254582ae1d5b9e14cea0ea8e701bHoward Hinnant assert(std::abs((mean - x_mean) / x_mean) < 0.01); 109d6d1171f2c3f254582ae1d5b9e14cea0ea8e701bHoward Hinnant assert(std::abs((var - x_var) / x_var) < 0.01); 110d6d1171f2c3f254582ae1d5b9e14cea0ea8e701bHoward Hinnant assert(std::abs((skew - x_skew) / x_skew) < 0.01); 111d6d1171f2c3f254582ae1d5b9e14cea0ea8e701bHoward Hinnant assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01); 11297dc2f35c3d0d797ece43f5598023c6952144f37Howard Hinnant } 11397dc2f35c3d0d797ece43f5598023c6952144f37Howard Hinnant { 11497dc2f35c3d0d797ece43f5598023c6952144f37Howard Hinnant typedef std::chi_squared_distribution<> D; 115df40dc6c1a8ca0bf00fb6aec030f69042f61d974Howard Hinnant typedef std::mt19937 G; 11697dc2f35c3d0d797ece43f5598023c6952144f37Howard Hinnant G g; 11797dc2f35c3d0d797ece43f5598023c6952144f37Howard Hinnant D d(2); 118df40dc6c1a8ca0bf00fb6aec030f69042f61d974Howard Hinnant const int N = 1000000; 11997dc2f35c3d0d797ece43f5598023c6952144f37Howard Hinnant std::vector<D::result_type> u; 12097dc2f35c3d0d797ece43f5598023c6952144f37Howard Hinnant for (int i = 0; i < N; ++i) 121df40dc6c1a8ca0bf00fb6aec030f69042f61d974Howard Hinnant { 122df40dc6c1a8ca0bf00fb6aec030f69042f61d974Howard Hinnant D::result_type v = d(g); 123df40dc6c1a8ca0bf00fb6aec030f69042f61d974Howard Hinnant assert(d.min() < v); 124df40dc6c1a8ca0bf00fb6aec030f69042f61d974Howard Hinnant u.push_back(v); 125df40dc6c1a8ca0bf00fb6aec030f69042f61d974Howard Hinnant } 126df40dc6c1a8ca0bf00fb6aec030f69042f61d974Howard Hinnant double mean = std::accumulate(u.begin(), u.end(), 0.0) / u.size(); 127df40dc6c1a8ca0bf00fb6aec030f69042f61d974Howard Hinnant double var = 0; 128df40dc6c1a8ca0bf00fb6aec030f69042f61d974Howard Hinnant double skew = 0; 129df40dc6c1a8ca0bf00fb6aec030f69042f61d974Howard Hinnant double kurtosis = 0; 130a9bcd3dae859f02ab496d175d50840f43a2d4ed2Stephan T. Lavavej for (std::size_t i = 0; i < u.size(); ++i) 131df40dc6c1a8ca0bf00fb6aec030f69042f61d974Howard Hinnant { 132d6c0cf0ebdfd1d237fe7e07ab3732467dbd14c91Eric Fiselier double dbl = (u[i] - mean); 133d6c0cf0ebdfd1d237fe7e07ab3732467dbd14c91Eric Fiselier double d2 = sqr(dbl); 134df40dc6c1a8ca0bf00fb6aec030f69042f61d974Howard Hinnant var += d2; 135d6c0cf0ebdfd1d237fe7e07ab3732467dbd14c91Eric Fiselier skew += dbl * d2; 136df40dc6c1a8ca0bf00fb6aec030f69042f61d974Howard Hinnant kurtosis += d2 * d2; 137df40dc6c1a8ca0bf00fb6aec030f69042f61d974Howard Hinnant } 13897dc2f35c3d0d797ece43f5598023c6952144f37Howard Hinnant var /= u.size(); 139df40dc6c1a8ca0bf00fb6aec030f69042f61d974Howard Hinnant double dev = std::sqrt(var); 140df40dc6c1a8ca0bf00fb6aec030f69042f61d974Howard Hinnant skew /= u.size() * dev * var; 141df40dc6c1a8ca0bf00fb6aec030f69042f61d974Howard Hinnant kurtosis /= u.size() * var * var; 142df40dc6c1a8ca0bf00fb6aec030f69042f61d974Howard Hinnant kurtosis -= 3; 143df40dc6c1a8ca0bf00fb6aec030f69042f61d974Howard Hinnant double x_mean = d.n(); 144df40dc6c1a8ca0bf00fb6aec030f69042f61d974Howard Hinnant double x_var = 2 * d.n(); 145df40dc6c1a8ca0bf00fb6aec030f69042f61d974Howard Hinnant double x_skew = std::sqrt(8 / d.n()); 146df40dc6c1a8ca0bf00fb6aec030f69042f61d974Howard Hinnant double x_kurtosis = 12 / d.n(); 147d6d1171f2c3f254582ae1d5b9e14cea0ea8e701bHoward Hinnant assert(std::abs((mean - x_mean) / x_mean) < 0.01); 148d6d1171f2c3f254582ae1d5b9e14cea0ea8e701bHoward Hinnant assert(std::abs((var - x_var) / x_var) < 0.01); 149d6d1171f2c3f254582ae1d5b9e14cea0ea8e701bHoward Hinnant assert(std::abs((skew - x_skew) / x_skew) < 0.01); 150d6d1171f2c3f254582ae1d5b9e14cea0ea8e701bHoward Hinnant assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01); 15197dc2f35c3d0d797ece43f5598023c6952144f37Howard Hinnant } 15297dc2f35c3d0d797ece43f5598023c6952144f37Howard Hinnant} 153