Revisited [rand.dist.bern.bin] and [rand.dist.pois.poisson] with better algorithms

git-svn-id: https://llvm.org/svn/llvm-project/libcxx/trunk@103886 91177308-0d34-0410-b5e6-96231b3b80d8

test/numerics/rand/rand.dis/rand.dist.bern/rand.dist.bern.bernoulli/eval_param.pass.cpp

@@ -14,24 +14,62 @@
 // 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::bernoulli_distribution D;
         typedef D::param_type P;
-        typedef std::minstd_rand0 G;
+        typedef std::minstd_rand G;
         G g;
         D d(.75);
         P p(.25);
-        int count = 0;
-        for (int i = 0; i < 10000; ++i)
-        {
-            bool u = d(g, p);
-            if (u)
-                ++count;
-        }
-        assert(count < 2600);
+        const int N = 100000;
+        std::vector<D::result_type> u;
+        for (int i = 0; i < N; ++i)
+            u.push_back(d(g, p));
+        double mean = std::accumulate(u.begin(), u.end(),
+                                              double(0)) / u.size();
+        double var = 0;
+        for (int i = 0; i < u.size(); ++i)
+            var += sqr(u[i] - mean);
+        var /= u.size();
+        double x_mean = p.p();
+        double x_var = 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);
+    }
+    {
+        typedef std::bernoulli_distribution D;
+        typedef D::param_type P;
+        typedef std::minstd_rand G;
+        G g;
+        D d(.25);
+        P p(.75);
+        const int N = 100000;
+        std::vector<D::result_type> u;
+        for (int i = 0; i < N; ++i)
+            u.push_back(d(g, p));
+        double mean = std::accumulate(u.begin(), u.end(),
+                                              double(0)) / u.size();
+        double var = 0;
+        for (int i = 0; i < u.size(); ++i)
+            var += sqr(u[i] - mean);
+        var /= u.size();
+        double x_mean = p.p();
+        double x_var = 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);
     }
 }