R/best_acca.R

In meantrix/corrP: corrp (Compute correlations type analysis in parallel)

#' @title Silhouette (clustering)
#'
#' @description Determining the optimal number of cluster in the ACCA clustering using the
#' average silhouette aproach.
#'
#' @param m  \[\code{matrix(1)}]\cr correlation matrix from \code{\link{corr_matrix}}.
#' @param mink \[\code{integer(1)}]\cr minimum number of clusters considered.
#' @param maxk \[\code{integer(1)}]\cr maximum number of clusters considered.
#' @param maxrep \[\code{integer(1)}]\cr maximum number of interactions without change in the clusters in the ACCA method.
#' @param maxiter \[\code{integer(1)}]\cr maximum number of interactions in the ACCA method.
#' @param ... Additional arguments (TODO).
#'
#' @return \[\code{list(3)}]\cr A list with: silhouette average with per k `$silhouette.ave`;
#' the sequence of clusters tested `$k` and the optimal number of clusters `$best.k`.
#' @seealso \code{\link{sil_acca}}
#'
#' @author Igor D.S. Siciliani
#'
#' @keywords silhouette , acca , optimal , k
#'
#' @references
#' Leonard Kaufman; Peter J. Rousseeuw (1990).
#' Finding groups in data : An introduction to cluster analysis.
#' Hoboken, NJ: Wiley-Interscience. p. 87. doi:10.1002/9780470316801. ISBN 9780471878766.
#'
#' Starczewski, Artur, and Adam Krzyżak. "Performance evaluation of the silhouette index.
#' " International Conference on Artificial Intelligence and Soft Computing. Springer, Cham, 2015.
#'
#'
#' @examples
#' \dontrun{
#'
#' x = corrp::corrp(iris)
#' m = corrp::corr_matrix(x)
#' best_acca(m,2,6)
#'
#'}
#'
#' @export
#'
best_acca = function(m,...) {
  UseMethod('best_acca',m)
}


#' @export
#' @rdname best_acca
best_acca.cmatrix <- function(m, mink,maxk, maxrep = 2L, maxiter = 100L,...) {

  mink = as.integer(mink)
  maxk = as.integer(maxk)
  maxrep = as.integer(maxrep)
  maxiter = as.integer(maxiter)
  checkmate::assert_int(mink,lower = 2)
  checkmate::assert_true(mink < maxk)
  checkmate::assert_int(maxrep,lower = 2,upper = maxiter)
  checkmate::assert_int(maxiter,lower = maxrep)

  .Call(`_corrp_best_acca_sil`, m, mink, maxk, maxrep, maxiter)
}

#' @export
#' @rdname best_acca
best_acca.matrix <- function(m, mink,maxk, maxrep = 2L, maxiter = 100L,...) {

  warning("m is not an object of the 'cmatrix' class some results may go wrong.")


  mink = as.integer(mink)
  maxk = as.integer(maxk)
  maxrep = as.integer(maxrep)
  maxiter = as.integer(maxiter)
  checkmate::assert_int(mink,lower = 2)
  checkmate::assert_true(mink < maxk)
  checkmate::assert_int(maxrep,lower = 2,upper = maxiter)
  checkmate::assert_int(maxiter,lower = maxrep)

  .Call(`_corrp_best_acca_sil`, m, mink, maxk, maxrep, maxiter)

}