R/RcppExports.R

In xyz: The 'xyz' Algorithm for Fast Interaction Search in High-Dimensional Data

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

order_vector <- function(x, decreasing) {
    .Call('xyz_order_vector', PACKAGE = 'xyz', x, decreasing)
}

sort_using_order_numvec <- function(x, x_o) {
    invisible(.Call('xyz_sort_using_order_numvec', PACKAGE = 'xyz', x, x_o))
}

sort_using_order_intmat <- function(x, x_o) {
    invisible(.Call('xyz_sort_using_order_intmat', PACKAGE = 'xyz', x, x_o))
}

sample_uniform <- function(range, n) {
    .Call('xyz_sample_uniform', PACKAGE = 'xyz', range, n)
}

sample_int_replace <- function(probabilities, n) {
    .Call('xyz_sample_int_replace', PACKAGE = 'xyz', probabilities, n)
}

prod_matrix_vector <- function(X, r) {
    .Call('xyz_prod_matrix_vector', PACKAGE = 'xyz', X, r)
}

colsum_index <- function(X, indexes) {
    .Call('xyz_colsum_index', PACKAGE = 'xyz', X, indexes)
}

absolute_covariates <- function(X, Y) {
    .Call('xyz_absolute_covariates', PACKAGE = 'xyz', X, Y)
}

absolute_covariates_pairs <- function(pairs, X, Y) {
    .Call('xyz_absolute_covariates_pairs', PACKAGE = 'xyz', pairs, X, Y)
}

clean_pairs <- function(pairs) {
    .Call('xyz_clean_pairs', PACKAGE = 'xyz', pairs)
}

translate_to_binary <- function(X, max_number_of_iterations) {
    .Call('xyz_translate_to_binary', PACKAGE = 'xyz', X, max_number_of_iterations)
}

estimate_background_interaction_frequency <- function(X, Y, number_of_samples) {
    .Call('xyz_estimate_background_interaction_frequency', PACKAGE = 'xyz', X, Y, number_of_samples)
}

find_strongest_pairs <- function(pairs, X, Y, max_number_of_pairs) {
    .Call('xyz_find_strongest_pairs', PACKAGE = 'xyz', pairs, X, Y, max_number_of_pairs)
}

equalpairs <- function(u, v, ou, ov, max_number_of_pairs) {
    .Call('xyz_equalpairs', PACKAGE = 'xyz', u, v, ou, ov, max_number_of_pairs)
}

projected_equal_pairs <- function(X, Y, number_of_runs, max_number_of_collisions, negative) {
    .Call('xyz_projected_equal_pairs', PACKAGE = 'xyz', X, Y, number_of_runs, max_number_of_collisions, negative)
}

naive_interaction_search <- function(X, Y, max_number_of_pairs) {
    .Call('xyz_naive_interaction_search', PACKAGE = 'xyz', X, Y, max_number_of_pairs)
}

interaction_search <- function(X, Y, number_of_runs, max_number_of_pairs, negative, binary) {
    .Call('xyz_interaction_search', PACKAGE = 'xyz', X, Y, number_of_runs, max_number_of_pairs, negative, binary)
}

interaction_search_low_level <- function(X_binary, X, Y, number_of_runs, max_number_of_pairs) {
    .Call('xyz_interaction_search_low_level', PACKAGE = 'xyz', X_binary, X, Y, number_of_runs, max_number_of_pairs)
}

soft_threshold <- function(beta_tilde, normalization, lambda, alpha) {
    .Call('xyz_soft_threshold', PACKAGE = 'xyz', beta_tilde, normalization, lambda, alpha)
}

create_lambda_sequence <- function(lambda_max, n_lambda, factor_eps_inv) {
    .Call('xyz_create_lambda_sequence', PACKAGE = 'xyz', lambda_max, n_lambda, factor_eps_inv)
}

scan_main_effects <- function(X, Y, residuals, main_effects, beta_main, lambdas, alpha, r, add_max, strong) {
    .Call('xyz_scan_main_effects', PACKAGE = 'xyz', X, Y, residuals, main_effects, beta_main, lambdas, alpha, r, add_max, strong)
}

scale_intr <- function(X, pair_x, pair_y) {
    .Call('xyz_scale_intr', PACKAGE = 'xyz', X, pair_x, pair_y)
}

scan_intr_effects <- function(X, Y, X_bin, residuals, intr_effects, beta_intr, intr_vars, lambdas, alpha, r, projections, strong) {
    .Call('xyz_scan_intr_effects', PACKAGE = 'xyz', X, Y, X_bin, residuals, intr_effects, beta_intr, intr_vars, lambdas, alpha, r, projections, strong)
}

update_intr_final <- function(intr_effects, beta_intr) {
    invisible(.Call('xyz_update_intr_final', PACKAGE = 'xyz', intr_effects, beta_intr))
}

calculate_xbeta <- function(X, Y, intercept, main_effects, beta_main, intr_effects, beta_intr, intr_vars, r) {
    .Call('xyz_calculate_xbeta', PACKAGE = 'xyz', X, Y, intercept, main_effects, beta_main, intr_effects, beta_intr, intr_vars, r)
}

calculate_residuals <- function(X, Y, intercept, main_effects, beta_main, intr_effects, beta_intr, intr_vars, r) {
    .Call('xyz_calculate_residuals', PACKAGE = 'xyz', X, Y, intercept, main_effects, beta_main, intr_effects, beta_intr, intr_vars, r)
}

iterate <- function(X, Y, residuals, intercept, main_effects, beta_main, intr_effects, beta_intr, intr_vars, weights, lambdas, alpha, r, maxiter_inner) {
    .Call('xyz_iterate', PACKAGE = 'xyz', X, Y, residuals, intercept, main_effects, beta_main, intr_effects, beta_intr, intr_vars, weights, lambdas, alpha, r, maxiter_inner)
}

update_intr_vars <- function(X, intr_effects, standardize, r) {
    .Call('xyz_update_intr_vars', PACKAGE = 'xyz', X, intr_effects, standardize, r)
}

clean_all_effects <- function(main_effects, beta_main, intr_effects, beta_intr, r) {
    invisible(.Call('xyz_clean_all_effects', PACKAGE = 'xyz', main_effects, beta_main, intr_effects, beta_intr, r))
}

warm_start <- function(main_effects, beta_main, intr_effects, beta_intr, r) {
    invisible(.Call('xyz_warm_start', PACKAGE = 'xyz', main_effects, beta_main, intr_effects, beta_intr, r))
}

gaussiglmnet <- function(X, Y, lambdas, alpha, standardize, max_main_effects, max_interaction_effects, max_outer, number_of_nnis_runs) {
    .Call('xyz_gaussiglmnet', PACKAGE = 'xyz', X, Y, lambdas, alpha, standardize, max_main_effects, max_interaction_effects, max_outer, number_of_nnis_runs)
}