R/RcppExports.R

In Core-Bioinformatics/ClustAssess: Tools for Assessing Clustering

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

myContTable <- function(a, b, minim_mb1, minim_mb2) {
    .Call('_ClustAssess_myContTable', PACKAGE = 'ClustAssess', a, b, minim_mb1, minim_mb2)
}

disjointECS <- function(mb1, mb2) {
    .Call('_ClustAssess_disjointECS', PACKAGE = 'ClustAssess', mb1, mb2)
}

calculate_pac_cpp <- function(indicator, connectivity, lower_lim, upper_lim) {
    .Call('_ClustAssess_calculate_pac_cpp', PACKAGE = 'ClustAssess', indicator, connectivity, lower_lim, upper_lim)
}

pruneSNN <- function(snnMatrix, prune = 0) {
    .Call('_ClustAssess_pruneSNN', PACKAGE = 'ClustAssess', snnMatrix, prune)
}

computeSNN <- function(nnMatrix, k, prune = 0) {
    .Call('_ClustAssess_computeSNN', PACKAGE = 'ClustAssess', nnMatrix, k, prune)
}

#' Computes the NN adjacency matrix given the neighbours
#'
#' @param nnRanked A matrix with the lists of the nearest neighbours for each point
#' @param k The number of neighbours to consider. Defaults to `-1`, which means all neighbours.
#' @param start The index of the first neighbour to consider. Defaults to `0`.
#' @param prune The threshold to prune the SNN matrix. If -1, the function will only return the NN matrix. Defaults to `0`.
#'
#' @export
#'
#' @return A list with the NN and SNN adjacency matrices.
getNNmatrix <- function(nnRanked, k = -1L, start = 0L, prune = 0) {
    .Call('_ClustAssess_getNNmatrix', PACKAGE = 'ClustAssess', nnRanked, k, start, prune)
}

update_connectivity_cpp <- function(connectivity, sampling_indices, cluster_assignments) {
    .Call('_ClustAssess_update_connectivity_cpp', PACKAGE = 'ClustAssess', connectivity, sampling_indices, cluster_assignments)
}

wilcox_test <- function(rank_values, n1, max_rank) {
    .Call('_ClustAssess_wilcox_test', PACKAGE = 'ClustAssess', rank_values, n1, max_rank)
}