/* boost random_demo.cpp profane demo * * Copyright Jens Maurer 2000 * Permission to use, copy, modify, sell, and distribute this software * is hereby granted without fee provided that the above copyright notice * appears in all copies and that both that copyright notice and this * permission notice appear in supporting documentation, * * Jens Maurer makes no representations about the suitability of this * software for any purpose. It is provided "as is" without express or * implied warranty. * * $Id$ * * A short demo program how to use the random number library. */ #include #include #include // std::time #include #include #include // Sun CC doesn't handle boost::iterator_adaptor yet #if !defined(__SUNPRO_CC) || (__SUNPRO_CC > 0x530) #include #endif #ifdef BOOST_NO_STDC_NAMESPACE namespace std { using ::time; } #endif // try boost::mt19937 or boost::ecuyer1988 instead of boost::minstd_rand typedef boost::minstd_rand base_generator_type; // This is a reproducible simulation experiment. void experiment(base_generator_type & generator) { typedef boost::uniform_smallint generator_type; generator_type die_gen(generator, 1, 6); #if !defined(__SUNPRO_CC) || (__SUNPRO_CC > 0x530) // For an STL iterator interface, use iterator_adaptors.hpp boost::generator_iterator_generator::type die = boost::make_generator_iterator(die_gen); for(int i = 0; i < 10; i++) std::cout << *die++ << " "; std::cout << '\n'; #endif } int main() { // initialize by reproducible seed // Make sure it's unsigned, otherwise the wrong overload may be selected // with mt19937. base_generator_type generator(42u); std::cout << "10 samples of a uniform distribution in [0..1):\n"; boost::uniform_01 uni(generator); std::cout.setf(std::ios::fixed); // Random number generators have an STL Generator interface for(int i = 0; i < 10; i++) std::cout << uni() << '\n'; /* * Change seed to something else * Make sure the seed is unsigned, otherwise the wrong overload may be * selected with mt19937. * * Caveat: std::time(0) is not a very good truly-random seed. When * called in rapid succession, it could return the same values, and * thus the same random number sequences could ensue. If not the same * values are returned, the values differ only slightly in the * lowest bits. A linear congruential generator with a small factor * wrapped in a uniform_smallint (see experiment) will produce the same * values for the first few iterations. This is because uniform_smallint * takes only the highest bits of the generator, and the generator itself * needs a few iterations to spread the initial entropy from the lowest bits * to the whole state. */ generator.seed(static_cast(std::time(0))); std::cout << "\nexperiment: roll a die 10 times:\n"; base_generator_type saved_generator = generator; experiment(generator); std::cout << "redo the experiment to verify it:\n"; experiment(saved_generator); // after that, both generators are equivalent assert(generator == saved_generator); #ifndef BOOST_NO_OPERATORS_IN_NAMESPACE { // save the generator state for future use, // can be read again at any time via operator>> std::ofstream file("rng.saved", std::ofstream::trunc); file << generator; } #endif // Some compilers don't pay attention to std:3.6.1/5 and issue a // warning here if "return 0;" is omitted. return 0; }