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Comments (3)

Reputeless avatar Reputeless commented on June 5, 2024 1

As with all other pseudo-random number generators, if the seed value is the same, the generated random number sequence is always the same.

You can make a non-deterministic seed value by the following methods:

# include <iostream>
# include <random> // std::random_device, std::uniform_int_distribution
# include "XoshiroCpp.hpp"

int main()
{
    std::random_device rd;
    std::uniform_int_distribution<std::uint64_t> dist{ 0ULL, std::numeric_limits<std::uint64_t>::max() };
    const std::uint64_t seed = dist(rd);
    std::cout << "seed: " << seed << '\n';

    using namespace XoshiroCpp;
    Xoshiro256PlusPlus rng(seed);

    for (int i = 0; i < 5; ++i)
    {
        std::cout << rng() << '\n';
    }
}
  • Using time
  • Using a seed value entered by the user

from xoshiro-cpp.

Reputeless avatar Reputeless commented on June 5, 2024 1

For runtime performance and reproducibility.
std::random_device is very slow.

from xoshiro-cpp.

romanholidaypancakes avatar romanholidaypancakes commented on June 5, 2024

I have a question, in fact the following code can generate a random value

     std::random_device rd;
     std::uniform_int_distribution<std::uint64_t> dist{ 0ULL, std::numeric_limits<std::uint64_t>::max() };
     const std::uint64_t seed = dist(rd);

So why do we need other pseudo-random algorithms, because no matter the seed value is the same, then all random algorithms generate the same value multiple times.

from xoshiro-cpp.

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