specmine (version 4.0.0)

pca_kmeans_plot3D: PCA 3D k-means plot

Description

Plots PCA scores in 3D coloured by k-means cluster assignment.

Usage

pca_kmeans_plot3D(
  dataset,
  pca.result,
  num.clusters = 3,
  pcas = c(1, 2, 3),
  kmeans.result = NULL,
  labels = FALSE,
  size = 1,
  ...
)

Value

No return value, called for its side effect of plotting.

Arguments

dataset

Dataset used in the PCA.

pca.result

PCA result object.

num.clusters

Number of clusters.

pcas

Principal components to plot.

kmeans.result

Optional precomputed k-means result.

labels

Logical indicating whether sample labels should be shown.

size

Point size.

...

Additional arguments passed to rgl::plot3d().

Examples

# \donttest{
datamat <- matrix(
  rnorm(20),
  nrow = 4,
  dimnames = list(paste0("x", 1:4), paste0("s", 1:5))
)
metadata <- data.frame(class = factor(c("A", "A", "B", "B", "A")))
dataset <- list(data = datamat, metadata = metadata)
pca_res <- pca_analysis_dataset(dataset)
pca_kmeans_plot3D(dataset, pca_res, num.clusters = 2)
# }