UMAP implementation from a pre-computed kNN graph — rs_umap_from_knn

This is the wrapper function into the Rust interface for UMAP and takes a pre-computed kNN graph, skipping the graph build. GPU acceleration applies to the optimisation.

Usage

rs_umap_from_knn_gpu(
  embd,
  knn_data,
  n_dim,
  min_dist,
  spread,
  k,
  umap_params,
  seed,
  use_high_precision,
  verbose
)

Arguments

embd: Numerical matrix. The data to use to generate the embeddings. Should be of dimensions samples x features.
knn_data: NearestNeighbours class from R.
n_dim: Integer. Number of UMAP dimensions to return.
min_dist: Numeric. Minimum distance to use.
spread: Numeric. Spread parameter to use.
k: Integer. Number of nearest neighbours to consider
umap_params: Named list. List that contains all of the key parameters for the UMAP generation.
seed: Integer. Seed for reproducibility.
use_high_precision: Optional logical. Controls fp32 vs fp64 for. If NULL will use sensible default thresholding.
verbose: Integer. If 0L -> silent or 1L for normal verbosity; 2L for detailed verbosity.

Value

The UMAP embeddings.