initialize.hpp

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#ifndef QDTSNE_INITIALIZE_HPP
#define QDTSNE_INITIALIZE_HPP
 
#include "knncolle/knncolle.hpp"
 
#include <vector>
#include <stdexcept>
 
#include "Status.hpp"
#include "Options.hpp"
#include "gaussian.hpp"
#include "symmetrize.hpp"
 
namespace qdtsne {
 
namespace internal {
 
template<int num_dim_, typename Index_, typename Float_>
Status<num_dim_, Index_, Float_> initialize(NeighborList<Index_, Float_> nn, Float_ perp, const Options& options) {
    compute_gaussian_perplexity(nn, perp, options.num_threads);
    symmetrize_matrix(nn);
    return Status<num_dim_, Index_, Float_>(std::move(nn), options);
}
 
}
template<int num_dim_, typename Index_, typename Float_>
Status<num_dim_, Index_, Float_> initialize(NeighborList<Index_, Float_> neighbors, const Options& options) {
    Float_ perp;
    if (options.infer_perplexity && neighbors.size()) {
        perp = static_cast<Float_>(neighbors.front().size())/3;
    } else {
        perp = options.perplexity;
    }
    return internal::initialize<num_dim_>(std::move(neighbors), perp, options);
}
 
template<int num_dim_, typename Dim_, typename Index_, typename Float_>
Status<num_dim_, Index_, Float_> initialize(const knncolle::Prebuilt<Dim_, Index_, Float_>& prebuilt, const Options& options) { 
    const int K = perplexity_to_k(options.perplexity); 
    auto neighbors = find_nearest_neighbors(prebuilt, K, options.num_threads);
    return internal::initialize<num_dim_>(std::move(neighbors), static_cast<Float_>(options.perplexity), options);
}
 
template<int num_dim_, typename Dim_, typename Index_, typename Float_>
Status<num_dim_, Index_, Float_> initialize(
    Dim_ data_dim,
    Index_ num_points,
    const Float_* data,
    const knncolle::Builder<knncolle::SimpleMatrix<Dim_, Index_, Float_>, Float_>& builder,
    const Options& options) 
{
    auto index = builder.build_unique(knncolle::SimpleMatrix<Dim_, Index_, Float_>(data_dim, num_points, data));
    return initialize<num_dim_>(*index, options);
}
 
}
 
#endif