Package index

t-SNE Embeddings

Native interpolation-based t-SNE, transform, and landmark workflows.

tsne()

Run native interpolation-based t-SNE from a data matrix

tsne_knn()

Run native interpolation-based t-SNE from precomputed KNN

prepare_tsne_knn()

Precompute reusable t-SNE KNN state

transform_tsne()

Transform query points into an existing t-SNE embedding

UMAP Embeddings

Native UMAP embedding from data or precomputed nearest neighbors.

umap()

Run opinionated fixed-policy UMAP from data or precomputed KNN

umap_knn()

Run UMAP from precomputed nearest neighbors

prepare_umap_knn()

Precompute reusable UMAP graph state from KNN

Initialization

Construct package-native PCA and UMAP initializations.

pca()

Backend-native truncated PCA

umap_init()

Precompute a reusable UMAP initialization

Nearest-Neighbor Precomputation

Build reusable reference and query neighbor structures.

precompute_knn()

Precompute native nearest neighbors

precompute_query_knn()

Precompute query-to-reference nearest neighbors

Landmark Utilities

Select landmarks and project valid landmark models.

select_landmarks()

Select representative landmark observations

project_landmark_model()

Project observations into a fitted landmark embedding

Graph Utilities

Construct and cluster graphs derived from data or embeddings.

knn_graph()

Build a compact nearest-neighbor graph

graph_cluster()

Native graph community detection

Quality Metrics

Score local preservation, labels, and global structure.

evaluate_embedding()

Evaluate an embedding against high-dimensional structure

Massive Matrices and PCA

File-backed data access and streamed principal components.

massive_matrix()

Experimental disk-backed float32 matrix

massive_read_rows()

Read a bounded range from an experimental massive matrix

massive_open_pca()

EXPERIMENTAL reopen of completed file-backed PCA

Massive Neighbors and Postings

Disk-backed nearest-neighbor construction and inspection.

massive_coarse_postings()

EXPERIMENTAL physical posting lists for a file-backed matrix

massive_open_postings()

EXPERIMENTAL reopen of completed physical posting lists

massive_read_posting()

Read a bounded part of an experimental physical posting list

massive_search_postings()

EXPERIMENTAL bounded search over physical posting lists

massive_posting_recall_pilot()

EXPERIMENTAL recall preflight for physical posting search

massive_select_landmarks()

Experimental streaming reservoir landmarks

massive_landmark_knn()

Experimental file-backed query-to-landmark nearest neighbors

massive_audit_landmark_knn()

EXPERIMENTAL measured recall for file-backed landmark neighbors

massive_read_knn_rows()

Read a bounded range of experimental landmark KNN rows

massive_knn_graph()

Import an experimental file-backed full KNN graph

massive_full_knn_graph()

Build an experimental file-backed full KNN graph

massive_read_graph_edges()

Read a bounded edge range from an experimental full KNN graph

Massive Embeddings

File-backed graph, affinity, optimizer, and projection stages.

massive_umap_memberships()

Calculate experimental directed UMAP memberships from disk-backed KNN

massive_umap_fuzzy_graph()

Symmetrize an experimental disk-backed UMAP membership graph

massive_fuzzy_graph()

Reload a package-built experimental fuzzy UMAP graph

massive_affinity_graph()

Reload package-built experimental t-SNE affinities

massive_tsne_affinities()

Construct experimental file-backed t-SNE affinities

massive_tsne_optimize()

Optimize experimental disk-backed t-SNE affinities

massive_umap_optimize()

Optimize an experimental disk-backed UMAP graph

massive_project_landmarks()

Experimental file-backed landmark embedding projection

massive_open_projection()

EXPERIMENTAL reopen of completed landmark projections

Massive Graphs and Clustering

File-backed graph access and community detection.

massive_weighted_graph()

Import an experimental file-backed weighted graph

massive_csr_graph()

Import an experimental file-backed weighted CSR graph

massive_graph_modularity()

Measure modularity of a file-backed fuzzy graph and disk-backed labels

massive_louvain_level()

EXPERIMENTAL first local-moving level of file-backed Louvain

massive_leiden_refine_level()

EXPERIMENTAL file-backed Leiden refinement stage

massive_leiden()

EXPERIMENTAL multilevel Leiden on a file-backed fuzzy graph

massive_read_leiden_rows()

Read bounded labels from experimental file-backed Leiden

massive_louvain()

EXPERIMENTAL multilevel Louvain on a file-backed fuzzy graph

massive_read_louvain_rows()

Read bounded labels from an experimental Louvain level

massive_walktrap()

EXPERIMENTAL partitioned Walktrap on a file-backed fuzzy graph

massive_read_walktrap_rows()

Read bounded labels from an experimental Walktrap fit

massive_graph_partitions()

Plan bounded partitions of an experimental full KNN graph

massive_read_graph_partition()

Read one bounded experimental graph partition

massive_cluster_landmarks()

EXPERIMENTAL file-backed landmark graph clustering

massive_cluster()

EXPERIMENTAL massive-data community clustering

massive_read_cluster_rows()

Read bounded rows from an experimental clustering result

Object Methods

Print and plot package result objects.

plot(<fastEmbedR_embedding>)

Plot an embedding result

print(<fastEmbedR_embedding>)

Print an embedding result

print(<fastEmbedR_graph>)

Print a nearest-neighbor graph

print(<fastEmbedR_graph_cluster>)

Print a graph-clustering result

print(<fastEmbedR_umap_initialization>)

Print a reusable UMAP initialization