simplicial_set_intersect: Merge Similarity Graph by Simplicial Set Intersection

In jlmelville/uwot: The Uniform Manifold Approximation and Projection (UMAP) Method for Dimensionality Reduction

Merge Similarity Graph by Simplicial Set Intersection

Description

Combine two similarity graphs by treating them as fuzzy topological sets and forming the intersection.

Usage

simplicial_set_intersect(x, y, weight = 0.5, n_threads = NULL, verbose = FALSE)

Arguments

x	A sparse matrix representing the first similarity graph in the intersection operation.
y	A sparse matrix representing the second similarity graph in the intersection operation.
weight	A value between 0 - 1, controlling the relative influence of x and y in the intersection. Default (0.5) gives equal influence. Values smaller than 0.5 put more weight on x. Values greater than 0.5 put more weight on y.
n_threads	Number of threads to use when resetting the local metric. Default is half the number of concurrent threads supported by the system.
verbose	If TRUE, log progress to the console.

Value

A sparse matrix containing the intersection of x and y.

Examples

# Form two different "views" of the same data
iris30 <- iris[c(1:10, 51:60, 101:110), ]
iris_sg12 <- similarity_graph(iris30[, 1:2], n_neighbors = 5)
iris_sg34 <- similarity_graph(iris30[, 3:4], n_neighbors = 5)

# Combine the two representations into one
iris_combined <- simplicial_set_intersect(iris_sg12, iris_sg34)

# Optimize the layout based on the combined view
iris_combined_umap <- optimize_graph_layout(iris_combined, n_epochs = 100)

jlmelville/uwot documentation built on Sept. 9, 2024, 11:17 a.m.