int main(int, char**) {
RandomLib::Random r; r.Reseed();
#if HAVE_LAMBDA
std::cout << "Illustrate calling STL routines with lambda expressions\n";
#else
std::cout << "Illustrate calling STL routines without lambda expressions\n";
#endif
std::cout << "Using " << r.Name() << "\n"
<< "with seed " << r.SeedString() << "\n\n";
std::vector<unsigned> c(10); // Fill with unsigned in [0, 2^32)
#if HAVE_LAMBDA
std::generate(c.begin(), c.end(),
[&r]() throw() -> unsigned { return r(); });
#else
std::generate<std::vector<unsigned>::iterator, RandomLib::Random&>
(c.begin(), c.end(), r);
#endif
std::vector<double> b(10); // Fill with normal deviates
#if HAVE_LAMBDA
RandomLib::NormalDistribution<> nf;
std::generate(b.begin(), b.end(),
[&r, &nf]() throw() -> double
{ return nf(r,0.0,2.0); });
#else
std::generate(b.begin(), b.end(), RandomNormal<>(r,0.0,2.0));
#endif
std::vector<int> a(20); // How to shuffle large vectors
#if HAVE_LAMBDA
int i = 0;
std::generate(a.begin(), a.end(),
[&i]() throw() -> int { return i++; });
std::random_shuffle(a.begin(), a.end(),
[&r](unsigned long long n) throw() -> unsigned long long
{ return r.Integer<unsigned long long>(n); });
#else
for (size_t i = 0; i < a.size(); ++i) a[i] = int(i);
RandomInt<unsigned long long> shuffler(r);
std::random_shuffle(a.begin(), a.end(), shuffler);
#endif
return 0;
}
int main(int, char**) {
// Create r with a random seed
RandomLib::Random r; r.Reseed();
std::cout << "Using " << r.Name() << "\n"
<< "with seed " << r.SeedString() << "\n\n";
{
std::cout
<< "Sampling exactly from the normal distribution. First number is\n"
<< "in binary with ... indicating an infinite sequence of random\n"
<< "bits. Second number gives the corresponding interval. Third\n"
<< "number is the result of filling in the missing bits and rounding\n"
<< "exactly to the nearest representable double.\n";
const int bits = 1;
RandomLib::ExactNormal<bits> ndist;
long long num = 20000000ll;
long long bitcount = 0;
int numprint = 16;
for (long long i = 0; i < num; ++i) {
long long k = r.Count();
RandomLib::RandomNumber<bits> x = ndist(r); // Sample
bitcount += r.Count() - k;
if (i < numprint) {
std::pair<double, double> z = x.Range();
std::cout << x << " = " // Print in binary with ellipsis
<< "(" << z.first << "," << z.second << ")"; // Print range
double v = x.Value<double>(r); // Round exactly to nearest double
std::cout << " = " << v << "\n";
} else if (i == numprint)
std::cout << std::flush;
}
std::cout
<< "Number of bits needed to obtain the binary representation averaged\n"
<< "over " << num << " samples = " << bitcount/double(num) << "\n\n";
}
{
std::cout
<< "Sampling exactly from exp(-x). First number is in binary with\n"
<< "... indicating an infinite sequence of random bits. Second\n"
<< "number gives the corresponding interval. Third number is the\n"
<< "result of filling in the missing bits and rounding exactly to\n"
<< "the nearest representable double.\n";
const int bits = 1;
RandomLib::ExactExponential<bits> edist;
long long num = 50000000ll;
long long bitcount = 0;
int numprint = 16;
for (long long i = 0; i < num; ++i) {
long long k = r.Count();
RandomLib::RandomNumber<bits> x = edist(r); // Sample
bitcount += r.Count() - k;
if (i < numprint) {
std::pair<double, double> z = x.Range();
std::cout << x << " = " // Print in binary with ellipsis
<< "(" << z.first << "," << z.second << ")"; // Print range
double v = x.Value<double>(r); // Round exactly to nearest double
std::cout << " = " << v << "\n";
} else if (i == numprint)
std::cout << std::flush;
}
std::cout
<< "Number of bits needed to obtain the binary representation averaged\n"
<< "over " << num << " samples = " << bitcount/double(num) << "\n\n";
}
{
std::cout
<< "Sampling exactly from the discrete normal distribution with\n"
<< "sigma = 7 and mu = 1/2.\n";
RandomLib::DiscreteNormal<int> gdist(7,1,1,2);
long long num = 50000000ll;
long long count = r.Count();
int numprint = 16;
for (long long i = 0; i < num; ++i) {
int k = gdist(r); // Sample
if (i < numprint)
std::cout << k << " ";
else if (i == numprint)
std::cout << std::endl;
}
count = r.Count() - count;
std::cout
<< "Number of random variates needed averaged\n"
<< "over " << num << " samples = " << count/double(num) << "\n\n";
}
{
std::cout
<< "Sampling exactly from the discrete normal distribution with\n"
<< "sigma = 1024 and mu = 1/7. First result printed is a uniform\n"
<< "range (with covers a power of two). The second number is the\n"
<< "result of sampling additional bits within that range to obtain\n"
<< "a definite result.\n";
RandomLib::DiscreteNormalAlt<int,1> gdist(1024,1,1,7);
long long num = 20000000ll;
long long count = r.Count();
long long entropy = 0;
int numprint = 16;
for (long long i = 0; i < num; ++i) {
RandomLib::UniformInteger<int,1> u = gdist(r);
entropy += u.Entropy();
if (i < numprint)
std::cout << u << " = ";
int k = u(r);
if (i < numprint)
std::cout << k << "\n";
else if (i == numprint)
std::cout << std::flush;
}
count = r.Count() - count;
std::cout
<< "Number of random bits needed for full result (for range) averaged\n"
<< "over " << num << " samples = " << count/double(num) << " ("
<< (count - entropy)/double(num) << ")\n\n";
}
{
std::cout
<< "Random bits with 1 occurring with probability 1/pi exactly:\n";
long long num = 100000000ll;
int numprint = 72;
RandomLib::InversePiProb pp;
long long nbits = 0;
long long k = r.Count();
for (long long i = 0; i < num; ++i) {
bool b = pp(r);
nbits += int(b);
if (i < numprint) std::cout << int(b);
else if (i == numprint) std::cout << "..." << std::flush;
}
std::cout << "\n";
std::cout << "Frequency of 1 averaged over " << num << " samples = 1/"
<< double(num)/nbits << "\n"
<< "bits/sample = " << (r.Count() - k)/double(num) << "\n\n";
}
{
std::cout
<< "Random bits with 1 occurring with probability 1/e exactly:\n";
long long num = 200000000ll;
int numprint = 72;
RandomLib::InverseEProb ep;
long long nbits = 0;
long long k = r.Count();
for (long long i = 0; i < num; ++i) {
bool b = ep(r);
nbits += int(b);
if (i < numprint) std::cout << int(b);
else if (i == numprint) std::cout << "..." << std::flush;
}
std::cout << "\n";
std::cout << "Frequency of 1 averaged over " << num << " samples = 1/"
<< double(num)/nbits << "\n"
<< "bits/sample = " << (r.Count() - k)/double(num) << "\n";
}
return 0;
}