% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/cluster_data.R
\name{print.net_clustering}
\alias{print.net_clustering}
\title{Print Method for net_clustering}
\usage{
\method{print}{net_clustering}(x, digits = 3L, ...)
}
\arguments{
\item{x}{A \code{net_clustering} object.}

\item{digits}{Integer. Decimal places used for floating-point statistics
in the printout. Default \code{3}. Non-breaking: existing
\code{print(x)} calls keep their previous formatting.}

\item{...}{Unsupported. Supplying unused arguments raises an error.}
}
\value{
The input object, invisibly.
}
\description{
Compact, fixed-width summary of a sequence-clustering result. The header
carries the clustering method and dissimilarity; the per-cluster table
carries cluster size (count and percentage) and mean within-cluster
distance when available. Optional medoid and covariate lines surface
only when those fields are populated.
}
\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)
print(cl)
\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)
print(cl)
}

}
