InitializeRandom.hpp

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#ifndef KMEANS_INITIALIZE_RANDOM_HPP
#define KMEANS_INITIALIZE_RANDOM_HPP 
 
#include <algorithm>
#include <cstdint>
#include <random>
 
#include "sanisizer/sanisizer.hpp"
#include "aarand/aarand.hpp"
 
#include "Initialize.hpp"
#include "copy_into_array.hpp"
 
namespace kmeans {
 
typedef std::mt19937_64 InitializeRandomRng;
 
struct InitializeRandomOptions {
    typename InitializeRandomRng::result_type seed = sanisizer::cap<InitializeRandomRng::result_type>(6523);
};
 
template<typename Index_, typename Data_, typename Cluster_, typename Float_, class Matrix_ = Matrix<Index_, Data_> >
class InitializeRandom final : public Initialize<Index_, Data_, Cluster_, Float_, Matrix_> { 
private:
    InitializeRandomOptions my_options;
 
public:
    InitializeRandom(InitializeRandomOptions options) : my_options(std::move(options)) {}
 
    InitializeRandom() = default;
 
public:
    InitializeRandomOptions& get_options() {
        return my_options;
    }
 
public:
    Cluster_ run(const Matrix_& data, const Cluster_ ncenters, Float_* const centers) const {
        InitializeRandomRng eng(my_options.seed);
        const auto nobs = data.num_observations();
        const decltype(I(nobs)) nchosen = sanisizer::min(nobs, ncenters);
        auto chosen = sanisizer::create<std::vector<Index_> >(nchosen);
        aarand::sample(nobs, nchosen, chosen.begin(), eng);
        internal::copy_into_array(data, chosen, centers);
        return nchosen;
    }
};
 
}
 
#endif