cxx/test/numerics/rand/rand.dis/rand.dist.pois/rand.dist.pois.exp/eval_param.pass.cpp
Howard Hinnant 30a840f5f0 [rand.dist.pois.exp]
git-svn-id: https://llvm.org/svn/llvm-project/libcxx/trunk@103621 91177308-0d34-0410-b5e6-96231b3b80d8
2010-05-12 17:08:57 +00:00

55 lines
1.4 KiB
C++

//===----------------------------------------------------------------------===//
//
// The LLVM Compiler Infrastructure
//
// This file is distributed under the University of Illinois Open Source
// License. See LICENSE.TXT for details.
//
//===----------------------------------------------------------------------===//
// <random>
// template<class RealType = double>
// class exponential_distribution
// template<class _URNG> result_type operator()(_URNG& g, const param_type& parm);
#include <random>
#include <cassert>
#include <vector>
#include <numeric>
template <class T>
inline
T
sqr(T x)
{
return x * x;
}
int main()
{
{
typedef std::exponential_distribution<> D;
typedef D::param_type P;
typedef std::knuth_b G;
G g;
D d(.75);
P p(2);
const int N = 1000;
std::vector<D::result_type> u;
for (int i = 0; i < N; ++i)
u.push_back(d(g, p));
D::result_type mean = std::accumulate(u.begin(), u.end(),
D::result_type(0)) / u.size();
D::result_type var = 0;
for (int i = 0; i < u.size(); ++i)
var += sqr(u[i] - mean);
var /= u.size();
D::result_type x_mean = 1/p.lambda();
D::result_type x_var = 1/sqr(p.lambda());
assert(std::abs(mean - x_mean) / x_mean < 0.01);
assert(std::abs(var - x_var) / x_var < 0.01);
}
}