plot_clustering: Plot Data With Clustering Information

In qcluster: Clustering via Quadratic Scoring

Plot Data With Clustering Information

Description

This function plots data and optionally adds clustering information such as clustering assignments, contours, or boundaries.

Usage

plot_clustering(
  data,
  subset = NULL,
  cluster = NULL,
  params = NULL,
  what = c("clustering", "contour", "boundary"),
  col_cl = NULL,
  pch_cl = NULL
)

Arguments

data	a numeric vector, matrix, or data frame of observations. Rows correspond to observations and columns correspond to variables/features. Categorical variables and NA values are not allowed.
subset	A numeric vector indexing columns of data to be visualized. Default is NULL.
cluster	A vector of cluster assignments. If provided, the plot can display clustering information as specified in what. Must have the same number of observations as data.
params	A list of clustering parameters, including proportion, mean, and cov. If provided, the plot can display contour and boundary information. For "contour" and "boundary", params must be valid mixture parameters.
what	Character vector specifying which elements to plot. Options are "clustering", "contour", and "boundary". The default request is all three. Requested features that are incompatible with the supplied inputs are dropped with a warning; if none remain, the function stops with an error.
col_cl	A vector of colors to use for clusters (one for each cluster). Default is NULL, which uses a default sequence of colors.
pch_cl	A vector of plotting symbols (one for each cluster) to use for clusters. Default is NULL, which uses a default sequence of symbols.

Details

At least one of cluster or params must be supplied. Contours and boundaries require Gaussian-ready parameters. Depending on the data dimension, the function produces one-dimensional plots, two-dimensional plots, or a scatterplot matrix over feature pairs. When subset is used, params are restricted to the selected coordinates before plotting.

Value

No return value, called for side effects.

See Also

bqs, clust2params

Examples

# Example data
set.seed(123)
data <- rbind(
            matrix(rnorm(100 * 2), ncol = 2),
            matrix(rnorm(100 * 2) + 2, ncol = 2)
        )
cluster <- c(rep(1, 100), rep(2, 100))
params <- clust2params(data, cluster)

# Plot with clustering information
plot_clustering(data, cluster = cluster, what = "clustering")

# Plot with subset of variables
plot_clustering(data, cluster = cluster, subset = 1,
                what = c("clustering", "contour"))

# Plot with customized colors and symbols
plot_clustering(data, cluster = cluster, params = params,
                col_cl = c("magenta", "orange"),
                pch_cl = c("A", "B"))

qcluster documentation built on June 5, 2026, 5:07 p.m.