9de6e30761
git-svn-id: https://llvm.org/svn/llvm-project/libcxx/trunk@103891 91177308-0d34-0410-b5e6-96231b3b80d8
96 lines
3.1 KiB
C++
96 lines
3.1 KiB
C++
//===----------------------------------------------------------------------===//
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//
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// The LLVM Compiler Infrastructure
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//
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// This file is distributed under the University of Illinois Open Source
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// License. See LICENSE.TXT for details.
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//
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//===----------------------------------------------------------------------===//
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// <random>
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// template<class RealType = double>
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// class weibull_distribution
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// template<class _URNG> result_type operator()(_URNG& g);
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#include <random>
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#include <cassert>
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#include <vector>
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#include <numeric>
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template <class T>
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inline
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T
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sqr(T x)
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{
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return x * x;
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}
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int main()
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{
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{
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typedef std::weibull_distribution<> D;
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typedef D::param_type P;
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typedef std::mt19937 G;
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G g;
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D d(0.5, 2);
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const int N = 100000;
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std::vector<D::result_type> u;
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for (int i = 0; i < N; ++i)
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u.push_back(d(g));
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D::result_type mean = std::accumulate(u.begin(), u.end(),
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D::result_type(0)) / u.size();
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D::result_type var = 0;
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for (int i = 0; i < u.size(); ++i)
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var += sqr(u[i] - mean);
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var /= u.size();
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D::result_type x_mean = d.b() * std::tgamma(1 + 1/d.a());
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D::result_type x_var = sqr(d.b()) * std::tgamma(1 + 2/d.a()) - sqr(x_mean);
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assert(std::abs(mean - x_mean) / x_mean < 0.02);
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assert(std::abs(var - x_var) / x_var < 0.02);
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}
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{
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typedef std::weibull_distribution<> D;
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typedef D::param_type P;
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typedef std::mt19937 G;
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G g;
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D d(1, .5);
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const int N = 100000;
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std::vector<D::result_type> u;
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for (int i = 0; i < N; ++i)
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u.push_back(d(g));
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D::result_type mean = std::accumulate(u.begin(), u.end(),
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D::result_type(0)) / u.size();
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D::result_type var = 0;
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for (int i = 0; i < u.size(); ++i)
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var += sqr(u[i] - mean);
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var /= u.size();
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D::result_type x_mean = d.b() * std::tgamma(1 + 1/d.a());
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D::result_type x_var = sqr(d.b()) * std::tgamma(1 + 2/d.a()) - sqr(x_mean);
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assert(std::abs(mean - x_mean) / x_mean < 0.02);
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assert(std::abs(var - x_var) / x_var < 0.02);
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}
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{
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typedef std::weibull_distribution<> D;
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typedef D::param_type P;
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typedef std::mt19937 G;
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G g;
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D d(2, 3);
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const int N = 100000;
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std::vector<D::result_type> u;
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for (int i = 0; i < N; ++i)
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u.push_back(d(g));
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D::result_type mean = std::accumulate(u.begin(), u.end(),
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D::result_type(0)) / u.size();
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D::result_type var = 0;
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for (int i = 0; i < u.size(); ++i)
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var += sqr(u[i] - mean);
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var /= u.size();
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D::result_type x_mean = d.b() * std::tgamma(1 + 1/d.a());
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D::result_type x_var = sqr(d.b()) * std::tgamma(1 + 2/d.a()) - sqr(x_mean);
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assert(std::abs(mean - x_mean) / x_mean < 0.02);
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assert(std::abs(var - x_var) / x_var < 0.02);
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}
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}
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