R/RcppExports.R

In slideimp: Numeric Matrices K-NN and PCA Imputation

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

pca_imp_internal_cpp <- function(X, miss, ncp, scale, regularized, threshold, init, maxiter, miniter, row_w, coeff_ridge) {
    .Call(`_slideimp_pca_imp_internal_cpp`, X, miss, ncp, scale, regularized, threshold, init, maxiter, miniter, row_w, coeff_ridge)
}

find_windows <- function(x, window, overlap = 0.0) {
    .Call(`_slideimp_find_windows`, x, window, overlap)
}

find_windows_flank <- function(location, subset, window_size) {
    .Call(`_slideimp_find_windows_flank`, location, subset, window_size)
}

impute_knn_brute <- function(obj, nmiss, k, grp_impute, grp_miss_no_imp, grp_complete, method, dist_pow, cache = TRUE, cores = 1L) {
    .Call(`_slideimp_impute_knn_brute`, obj, nmiss, k, grp_impute, grp_miss_no_imp, grp_complete, method, dist_pow, cache, cores)
}

impute_knn_mlpack <- function(obj, nmiss, k, grp_impute, method, dist_pow, cores = 1L) {
    .Call(`_slideimp_impute_knn_mlpack`, obj, nmiss, k, grp_impute, method, dist_pow, cores)
}

col_min_max <- function(mat) {
    .Call(`_slideimp_col_min_max`, mat)
}

col_vars_internal <- function(mat, cores = 1L) {
    .Call(`_slideimp_col_vars_internal`, mat, cores)
}

mean_imp_col_internal <- function(mat, col_idx, cores = 1L) {
    .Call(`_slideimp_mean_imp_col_internal`, mat, col_idx, cores)
}

check_finite <- function(mat) {
    invisible(.Call(`_slideimp_check_finite`, mat))
}

has_openmp <- function() {
    .Call(`_slideimp_has_openmp`)
}

sample_each_rep_cpp <- function(obj, pool_idx_in, na_per_col, row_room, col_room, max_attempts) {
    .Call(`_slideimp_sample_each_rep_cpp`, obj, pool_idx_in, na_per_col, row_room, col_room, max_attempts)
}