umap {umap} | R Documentation |
Computes a manifold approximation and projection
Description
Computes a manifold approximation and projection
Usage
umap(
d,
config = umap.defaults,
method = c("naive", "umap-learn"),
preserve.seed = TRUE,
...
)
Arguments
d |
matrix, input data |
config |
object of class umap.config |
method |
character, implementation. Available methods are 'naive' (an implementation written in pure R) and 'umap-learn' (requires python package 'umap-learn') |
preserve.seed |
logical, leave TRUE to insulate external code from randomness within the umap algorithms; set FALSE to allow randomness used in umap algorithms to alter the external random-number generator |
... |
list of settings; values overwrite defaults from config; see documentation of umap.default for details about available settings |
Value
object of class umap, containing at least a component with an embedding and a component with configuration settings
Examples
# embedd iris dataset using default settings
iris.umap = umap(iris[,1:4])
# display object summary
iris.umap
# display embedding coordinates
head(iris.umap$layout)
[Package umap version 0.2.10.0 Index]