R/RcppExports.R

In WOAkMedoids: Whale Optimization Algorithm for K-Medoids Clustering

# Generated by using Rcpp::compileAttributes() -> do not edit by hand
# Generator token: 10BE3573-1514-4C36-9D1C-5A225CD40393

totalDistance <- function(dist_vec, nrows, medoids, clustering) {
    .Call(`_WOAkMedoids_totalDistance`, dist_vec, nrows, medoids, clustering)
}

#' Fitness function for WOA optimization (C++ implementation)
#'
#' Combines cluster assignment and total distance calculation.
#' Returns Inf if any cluster has fewer than 2 members.
#'
#' @param dist_vec Distance vector (from dist object)
#' @param nrows Number of rows in the original data
#' @param medoids Integer vector of medoid indices (1-indexed)
#' @return total_dist (double), Inf if invalid clustering
#' @keywords internal
fitnessFunction_cpp <- function(dist_vec, nrows, medoids) {
    .Call(`_WOAkMedoids_fitnessFunction_cpp`, dist_vec, nrows, medoids)
}

#' Deterministic serial fitness function for final evaluation
#'
#' @param dist_vec Distance vector (from dist object)
#' @param nrows Number of rows in the original data
#' @param medoids Integer vector of medoid indices (1-indexed)
#' @return total_dist (double), Inf if invalid clustering
#' @keywords internal
fitnessFunction_serial_cpp <- function(dist_vec, nrows, medoids) {
    .Call(`_WOAkMedoids_fitnessFunction_serial_cpp`, dist_vec, nrows, medoids)
}

#' Check if two medoid solutions are identical
#'
#' @param medoids1 First medoid vector (1-indexed)
#' @param medoids2 Second medoid vector (1-indexed)
#' @return TRUE if identical (regardless of order), FALSE otherwise
#' @keywords internal
medoidsEqual_cpp <- function(medoids1, medoids2) {
    .Call(`_WOAkMedoids_medoidsEqual_cpp`, medoids1, medoids2)
}

#' Project MDS coordinates to nearest unique sample indices
#'
#' Finds the nearest sample in the MDS embedded space for each medoid coordinate,
#' while enforcing a one-to-one mapping between medoids and samples (no duplicates).
#'
#' @param medoid_coords NumericMatrix of medoid coordinates in MDS space (ClusNum x mds_dim)
#' @param Z NumericMatrix of sample coordinates in MDS space (nrows x mds_dim)
#' @return IntegerVector of nearest unique sample indices (1-indexed, length = ClusNum)
#' @keywords internal
projectToIndex_cpp <- function(medoid_coords, Z) {
    .Call(`_WOAkMedoids_projectToIndex_cpp`, medoid_coords, Z)
}