Run PHATE dimensionality reduction from a precomputed kNN graph

Leverages the PHATE implementation in manifolds-rs - a very fast Rust-based implementation. This version uses a pre-computed kNN graph, please see new_nearest_neighbour().

Usage

rs_phate_from_knn(
  embd,
  knn_data,
  n_dim,
  k,
  phate_params,
  seed,
  use_high_precision,
  verbose
)

Arguments

embd

Numerical matrix. The data to embed of shape samples x features.

knn_data

NearestNeighbours class from R.

n_dim

Integer. Number of PHATE dimensions to return. Currently only 2L is supported.

k

Integer. Number of nearest neighbours used during graph construction. Must match the k used to generate knn_data.

phate_params

Named list. Contains all key parameters for PHATE, see params_phate() and params_nn().

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 PHATE embedding as a matrix of shape samples x n_dim.