qcluster (version 1.2.1)

plot_clustering: 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)

Value

No return value, called for side effects

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 subset and focus the plot on specific features. 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.

what

Character vector specifying which elements to plot. Options are "clustering", "contour", and "boundary". Default is to plot "clustering" whenever cluster is not NULL, and "contour" and "boundary" whenever params is not NULL.

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.

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"))