1#ifndef QDTSNE_INITIALIZE_HPP
2#define QDTSNE_INITIALIZE_HPP
12#include "gaussian.hpp"
13#include "symmetrize.hpp"
27template<std::
size_t num_dim_,
typename Index_,
typename Float_>
28Status<num_dim_, Index_, Float_>
initialize(NeighborList<Index_, Float_> nn, Float_ perp,
const Options& options) {
29 compute_gaussian_perplexity(nn, perp, options.num_threads);
30 symmetrize_matrix(nn);
31 return Status<num_dim_, Index_, Float_>(std::move(nn), options);
53template<std::
size_t num_dim_,
typename Index_,
typename Float_>
57 perp =
static_cast<Float_
>(neighbors.front().size())/3;
61 return internal::initialize<num_dim_>(std::move(neighbors), perp, options);
79template<std::
size_t num_dim_,
typename Index_,
typename Input_,
typename Float_>
83 return internal::initialize<num_dim_>(std::move(neighbors),
static_cast<Float_
>(options.
perplexity), options);
104template<std::
size_t num_dim_,
typename Index_,
typename Float_,
class Matrix_>
106 std::size_t data_dim,
107 std::size_t num_points,
Options for the t-SNE algorithm.
Status of the t-SNE iterations.
std::unique_ptr< Prebuilt< Index_, Data_, Distance_ > > build_unique(const Matrix_ &data) const
Status of the t-SNE iterations.
Definition Status.hpp:65
NeighborList< Index_, Distance_ > find_nearest_neighbors(const Prebuilt< Index_, Data_, Distance_ > &index, int k, int num_threads=1)
knncolle::NeighborList< Index_, Float_ > NeighborList
Lists of neighbors for each observation.
Definition utils.hpp:36
int perplexity_to_k(double perplexity)
Definition utils.hpp:45
Status< num_dim_, Index_, Float_ > initialize(NeighborList< Index_, Float_ > neighbors, const Options &options)
Definition initialize.hpp:54
Options for initialize().
Definition Options.hpp:14
bool infer_perplexity
Definition Options.hpp:30
int num_threads
Definition Options.hpp:109
double perplexity
Definition Options.hpp:22