R/print.tclust.R

In tclust: Robust Trimmed Clustering

#'
#' @export

print.tclust <- function (x, ...)
{
  cat ("* Results for TCLUST algorithm: *\n")
  cat ("opt=", x$par$opt, ", trim = ", x$par$alpha, ", k = ", x$k, 
    "\nRestriction on: ", ifelse(x$par$restr=="eigen", "eigenvalues", "determinants"), "\n\n", sep = "")

  cat ("Classification (trimmed points are indicated by 0", "):\n")

  print (x$cluster)
  cat ("Means:\n")
  print (x$centers)
  if (x$obj < (-1e+20))
    warning ("The solution is not reliable. More iterations are probably needed.")
  cat ("\nTrimmed objective function: ", x$obj, "\n")

    if (!is.null (x$par$restr.fact))
        cat ("Selected restriction factor:", x$par$restr.fact, "\n")
  
    ##  cat (round (x$int$iter.converged / x$int$iter.successful* 100), 
    ##        "% of iterations converged successfully.\n", sep= "")

  invisible(x)
}

#' @export

print.tkmeans <- function (x, ...) {
  cat ("* Results for TKMEANS algorithm: *\n")
  cat ("trim = ", x$par$alpha, ", k = ", x$k, "\n", sep = "")

  cat ("Classification (trimmed points are indicated by 0", "):\n")

  print (x$cluster)
  cat ("Means:\n")
  print (x$centers)
  if (x$obj < (-1e+20))
    warning ("The solution is not reliable. More iterations are probably needed.")
  cat ("\nTrimmed objective function: ", x$obj, "\n")

  if (!is.null (x$restr.fact))
    cat ("Selected restriction factor:", x$restr.fact, "\n")
  
  cat (round (x$int$iter.converged / x$int$iter.successful* 100), "% of iterations converged successfully.\n", sep= "")

  invisible(x)
}