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Diffstat (limited to 'test/std/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.geo/eval_param.pass.cpp')
-rw-r--r-- | test/std/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.geo/eval_param.pass.cpp | 160 |
1 files changed, 160 insertions, 0 deletions
diff --git a/test/std/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.geo/eval_param.pass.cpp b/test/std/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.geo/eval_param.pass.cpp new file mode 100644 index 000000000000..91dea8aa1337 --- /dev/null +++ b/test/std/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.geo/eval_param.pass.cpp @@ -0,0 +1,160 @@ +//===----------------------------------------------------------------------===// +// +// The LLVM Compiler Infrastructure +// +// This file is dual licensed under the MIT and the University of Illinois Open +// Source Licenses. See LICENSE.TXT for details. +// +//===----------------------------------------------------------------------===// +// +// REQUIRES: long_tests + +// <random> + +// template<class IntType = int> +// class geometric_distribution + +// template<class _URNG> result_type operator()(_URNG& g, const param_type& parm); + +#include <random> +#include <numeric> +#include <vector> +#include <cassert> + +template <class T> +inline +T +sqr(T x) +{ + return x * x; +} + +int main() +{ + { + typedef std::geometric_distribution<> D; + typedef D::param_type P; + typedef std::mt19937 G; + G g; + D d(.75); + P p(.03125); + const int N = 1000000; + std::vector<D::result_type> u; + for (int i = 0; i < N; ++i) + { + D::result_type v = d(g, p); + assert(d.min() <= v && v <= d.max()); + u.push_back(v); + } + double mean = std::accumulate(u.begin(), u.end(), + double(0)) / u.size(); + double var = 0; + double skew = 0; + double kurtosis = 0; + for (int i = 0; i < u.size(); ++i) + { + double d = (u[i] - mean); + double d2 = sqr(d); + var += d2; + skew += d * d2; + kurtosis += d2 * d2; + } + var /= u.size(); + double dev = std::sqrt(var); + skew /= u.size() * dev * var; + kurtosis /= u.size() * var * var; + kurtosis -= 3; + double x_mean = (1 - p.p()) / p.p(); + double x_var = x_mean / p.p(); + double x_skew = (2 - p.p()) / std::sqrt((1 - p.p())); + double x_kurtosis = 6 + sqr(p.p()) / (1 - p.p()); + assert(std::abs((mean - x_mean) / x_mean) < 0.01); + assert(std::abs((var - x_var) / x_var) < 0.01); + assert(std::abs((skew - x_skew) / x_skew) < 0.01); + assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.01); + } + { + typedef std::geometric_distribution<> D; + typedef D::param_type P; + typedef std::mt19937 G; + G g; + D d(.75); + P p(.25); + const int N = 1000000; + std::vector<D::result_type> u; + for (int i = 0; i < N; ++i) + { + D::result_type v = d(g, p); + assert(d.min() <= v && v <= d.max()); + u.push_back(v); + } + double mean = std::accumulate(u.begin(), u.end(), + double(0)) / u.size(); + double var = 0; + double skew = 0; + double kurtosis = 0; + for (int i = 0; i < u.size(); ++i) + { + double d = (u[i] - mean); + double d2 = sqr(d); + var += d2; + skew += d * d2; + kurtosis += d2 * d2; + } + var /= u.size(); + double dev = std::sqrt(var); + skew /= u.size() * dev * var; + kurtosis /= u.size() * var * var; + kurtosis -= 3; + double x_mean = (1 - p.p()) / p.p(); + double x_var = x_mean / p.p(); + double x_skew = (2 - p.p()) / std::sqrt((1 - p.p())); + double x_kurtosis = 6 + sqr(p.p()) / (1 - p.p()); + assert(std::abs((mean - x_mean) / x_mean) < 0.01); + assert(std::abs((var - x_var) / x_var) < 0.01); + assert(std::abs((skew - x_skew) / x_skew) < 0.01); + assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.03); + } + { + typedef std::geometric_distribution<> D; + typedef D::param_type P; + typedef std::minstd_rand G; + G g; + D d(.5); + P p(.75); + const int N = 1000000; + std::vector<D::result_type> u; + for (int i = 0; i < N; ++i) + { + D::result_type v = d(g, p); + assert(d.min() <= v && v <= d.max()); + u.push_back(v); + } + double mean = std::accumulate(u.begin(), u.end(), + double(0)) / u.size(); + double var = 0; + double skew = 0; + double kurtosis = 0; + for (int i = 0; i < u.size(); ++i) + { + double d = (u[i] - mean); + double d2 = sqr(d); + var += d2; + skew += d * d2; + kurtosis += d2 * d2; + } + var /= u.size(); + double dev = std::sqrt(var); + skew /= u.size() * dev * var; + kurtosis /= u.size() * var * var; + kurtosis -= 3; + double x_mean = (1 - p.p()) / p.p(); + double x_var = x_mean / p.p(); + double x_skew = (2 - p.p()) / std::sqrt((1 - p.p())); + double x_kurtosis = 6 + sqr(p.p()) / (1 - p.p()); + assert(std::abs((mean - x_mean) / x_mean) < 0.01); + assert(std::abs((var - x_var) / x_var) < 0.01); + assert(std::abs((skew - x_skew) / x_skew) < 0.01); + assert(std::abs((kurtosis - x_kurtosis) / x_kurtosis) < 0.02); + } +} |