What Is The New std::sample Algorithm In C++ 17?
The C++ 17 standard bring us a lot of useful methods, templates and algorithms. One of the great algorithms is std::sample
defined in the
header that samples at most n
elements uniformly from a given range. In this post, we explain the std::sample
algorithm and how we can use it with an mt19937 random generator.
What is the std::sample algorithm in C++ 17 and beyond?
The std::sample
algorithm is defined in n
elements uniformly from a given range into the output iterator and random numbers can be generated by using a random number generator function. Generally std::mt19937{}
is used as random generator and std::random_device{}()
is used random generator device.
The std::sample
algorithm is defined as a template algorithm in C++17 as shown below.
template< class PopulationIterator, class SampleIterator, class Distance, class URBG > SampleIterator sample( PopulationIterator first_in, PopulationIterator last_in, SampleIterator output, Distance n, URBG&& function );
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Here, first_in
and last_in
are the iterators that defines range of input. n
is number of elements to be sampled into output
iterator, function
is random number generator function.
Is there a full example about the std::sample algorithm in C++ 17 and beyond?
Here is a full example about std::sample in C++ 17.
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#include #include #include #include #include #include
int main() { std::vector<std::string> vec_in {“This”, “LearnCPlusPlus.org”, “is”, “really”, “amazing”,“!”}; std::vector<std::string> vec_out;
std::cout << “Input vector:”; for(auto v :vec_in) std::cout << v << ” “; std::cout << std::endl;
std::sample( vec_in.begin(), vec_in.end(), std::back_inserter(vec_out), 4, std::mt19937 {std::random_device{}()});
std::cout << “Output vector:”; for(auto v :vec_out) std::cout << v << “,”; std::cout << std::endl;
system(“pause”); return 0; }
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Here is the output,
Input vector:This LearnCPlusPlus.org is really amazing ! Output vector:This,LearnCPlusPlus.org,really,amazing,
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For more details about this feature in C++17 standard, please see these papers; P0220R1 , N4562#alg.random.sample
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