问题
I need to generate random number with Boost Random.
I tried to follow the general guide.
I extracted the files of the library. So if I want to use the classes and objectj of the library how I should do?
First I know including the library in the program. Then I have to compile the library and the program.cpp itself? (And both with the same compiler - I'm using g++).
I am using a virtual box of ubuntu. It is first time that I am using library so I really don't know.
回答1:
the random number for my case must be double not just integer...
So, you use a real number distribution.
I'm not this kind of "getting started" is the best fit for StackOverflow, but I'll give you this quick hints:
In your Ubuntu virtual box:
sudo apt-get install libboost-all-dev
mkdir -pv ~/myproject
cd ~/myproject
Create a file using your favourite editor. If you have none, gedit main.cpp
or nano main.cpp
is a start:
#include <boost/random.hpp>
#include <iostream>
int main() {
boost::random::mt19937 rng;
boost::random::uniform_real_distribution<double> gen(0.0, 1.0);
for (int i = 0; i < 10; ++i) {
std::cout << gen(rng) << "\n";
}
}
Now compile it using
g++ -O2 -Wall -Wextra -pedantic main.cpp -o demo
The program is now ready to run: Live On Coliru
./demo
Printing
0.814724
0.135477
0.905792
0.835009
0.126987
0.968868
0.913376
0.221034
0.632359
0.308167
Seeding && Non-Header Only Libraries
The above works because the Boost Random library is mostly header only. What if you wanted to use the random_device
implementation to seed the random generator?
Live On Coliru
#include <boost/random.hpp>
#include <boost/random/random_device.hpp>
#include <iostream>
int main() {
boost::random::random_device seeder;
boost::random::mt19937 rng(seeder());
boost::random::uniform_real_distribution<double> gen(0.0, 1.0);
for (int i = 0; i < 10; ++i) {
std::cout << gen(rng) << "\n";
}
}
Now you'll have to link as well: Compiling with
g++ -O2 -Wall -Wextra -pedantic main.cpp -o demo -lboost_random
Now the output will be different each run.
BONUS: Standard Library instead of Boost
You don't need Boost here at all:
Live On Coliru
#include <random>
#include <iostream>
int main() {
std::random_device seeder;
std::mt19937 rng(seeder());
std::uniform_real_distribution<double> gen(0.0, 1.0);
for (int i = 0; i < 10; ++i) {
std::cout << gen(rng) << "\n";
}
}
Compile with
g++ -std=c++11 -O2 -Wall -Wextra -pedantic main.cpp -o demo
And run it again with ./demo
BONUS
Showing a whole gamut of distributions that have mean=0 and stddev=1:
Live On Coliru
#include <random>
#include <iostream>
#include <iomanip>
#include <chrono>
#include <boost/serialization/array_wrapper.hpp>
#include <boost/accumulators/accumulators.hpp>
#include <boost/accumulators/statistics.hpp>
namespace ba = boost::accumulators;
using Accum = ba::accumulator_set<double, ba::stats<ba::tag::variance, ba::tag::mean> >;
using Clock = std::chrono::high_resolution_clock;
using namespace std::chrono_literals;
static double identity(double d) { return d; }
template <typename Prng, typename Dist, typename F = double(double), size_t N = (1ull << 22)>
void test(Prng& rng, Dist dist, F f = &identity) {
Accum accum;
auto s = Clock::now();
for (size_t i = 0; i<N; ++i)
accum(f(dist(rng)));
std::cout
<< std::setw(34) << typeid(Dist).name()
<< ":\t" << ba::mean(accum)
<< " stddev: " << sqrt(ba::variance(accum))
<< " N=" << N
<< " in " << ((Clock::now()-s)/1.s) << "s"
<< std::endl;
}
int main() {
std::mt19937 rng(std::random_device{}());
auto shift = [](double shift) { return [=](double v) { return v + shift; }; };
auto scale = [](double scale) { return [=](double v) { return v * scale; }; };
std::cout << std::fixed << std::showpos;
test(rng, std::uniform_real_distribution<double>(-sqrt(3), sqrt(3)));
test(rng, std::weibull_distribution<double>(), shift(-1));
test(rng, std::exponential_distribution<double>(), shift(-1));
test(rng, std::normal_distribution<double>());
test(rng, std::lognormal_distribution<double>(0, log(0.5)), shift(-exp(pow(log(0.5),2)/2)));
test(rng, std::chi_squared_distribution<double>(0.5), shift(-0.5));
{
auto sigma = sqrt(6)/M_PI;
static constexpr double ec = 0.57721566490153286060;
test(rng, std::extreme_value_distribution<double>(-sigma*ec, sigma));
}
test(rng, std::fisher_f_distribution<double>(48, 8), shift(-(8.0/6.0)));
test(rng, std::student_t_distribution<double>(4), scale(sqrt(0.5)));
test(rng, std::student_t_distribution<double>(4), scale(sqrt(0.5)));
}
Prints
St25uniform_real_distributionIdE: +0.000375 stddev: +1.000056 N=4194304 in +0.169681s
St20weibull_distributionIdE: +0.001030 stddev: +1.000518 N=4194304 in +0.385036s
St24exponential_distributionIdE: -0.000360 stddev: +1.000343 N=4194304 in +0.389443s
St19normal_distributionIdE: -0.000133 stddev: +1.000330 N=4194304 in +0.390235s
St22lognormal_distributionIdE: +0.000887 stddev: +1.000372 N=4194304 in +0.521975s
St24chi_squared_distributionIdE: -0.000092 stddev: +0.999695 N=4194304 in +1.233835s
St26extreme_value_distributionIdE: -0.000381 stddev: +1.000242 N=4194304 in +0.611973s
St21fisher_f_distributionIdE: -0.000073 stddev: +1.001588 N=4194304 in +1.326189s
St22student_t_distributionIdE: +0.000957 stddev: +0.998087 N=4194304 in +1.080468s
St22student_t_distributionIdE: +0.000677 stddev: +0.998786 N=4194304 in +1.079066s
来源:https://stackoverflow.com/questions/48591592/how-do-i-use-boost-random