% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/cluster_data.R
\name{plot.net_clustering}
\alias{plot.net_clustering}
\title{Plot Sequence Clustering Results}
\usage{
\method{plot}{net_clustering}(
  x,
  type = c("silhouette", "mds", "heatmap", "predictors"),
  combined = TRUE,
  ...
)
}
\arguments{
\item{x}{A \code{net_clustering} object.}

\item{type}{Character. Plot type: \code{"silhouette"} (per-observation
silhouette bars), \code{"mds"} (2D MDS projection), or
\code{"heatmap"} (distance matrix heatmap ordered by cluster).
Default: \code{"silhouette"}.}

\item{combined}{Logical. For \code{type = "predictors"} only: when
\code{TRUE} (default), covariate forest panels are combined into a
single faceted plot; when \code{FALSE}, a list of separate ggplots is
returned.}

\item{...}{Unsupported. Supplying unused arguments raises an error.}
}
\value{
A \code{ggplot} object (invisibly).
}
\description{
Plot Sequence Clustering Results
}
\examples{
seqs <- data.frame(V1 = c("A","B","C","A","B"), V2 = c("B","C","A","B","A"),
                   V3 = c("C","A","B","C","B"))
cl <- build_clusters(seqs, k = 2)
plot(cl, type = "silhouette")
\donttest{
set.seed(1)
seqs <- data.frame(
  V1 = sample(c("A","B","C"), 20, TRUE),
  V2 = sample(c("A","B","C"), 20, TRUE),
  V3 = sample(c("A","B","C"), 20, TRUE)
)
cl <- build_clusters(seqs, k = 2)
plot(cl, type = "silhouette")
}

}
