Comments (3)
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:
- Using std::random_device
# 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
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For runtime performance and reproducibility.
std::random_device
is very slow.
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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.
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Related Issues (4)
- Use of jump, longjump HOT 1
- Simplify code HOT 2
- No setting the seed value after creation? HOT 4
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