compute_wcss.hpp

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#ifndef KMEANS_COMPUTE_WCSS_HPP
#define KMEANS_COMPUTE_WCSS_HPP
 
#include <algorithm>
#include <cstddef>
 
#include "sanisizer/sanisizer.hpp"
 
#include "utils.hpp"
 
namespace kmeans {
 
template<class Matrix_, typename Cluster_, typename Float_>
void compute_wcss(const Matrix_& data, const Cluster_ num_centers, const Float_* const centers, const Cluster_* const clusters, Float_* const wcss) {
    const auto nobs = data.num_observations();
    const auto ndim = data.num_dimensions();
    std::fill_n(wcss, num_centers, 0);
 
    auto work = data.new_extractor(static_cast<I<decltype(nobs)> >(0), nobs);
    for (I<decltype(nobs)> obs = 0; obs < nobs; ++obs) {
        const auto curdata = work->get_observation();
        const auto cen = clusters[obs];
 
        Float_& curwcss = wcss[cen];
        for (I<decltype(ndim)> d = 0; d < ndim; ++d) {
            const auto curcenter = centers[sanisizer::nd_offset<std::size_t>(d, ndim, cen)];
            const Float_ delta = static_cast<Float_>(curdata[d]) - curcenter; // cast for consistent precision regardless of the input data type.
            curwcss += delta * delta;
        }
    }
}
 
}
 
#endif