R/RcppExports.R

In ChenMengjie/VIPER: VIPER: a variability-preserving imputation method for single cell RNA sequencing data

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

calculate_weights <- function(z, X) {
    .Call('_VIPER_calculate_weights', PACKAGE = 'VIPER', z, X)
}

fitting_lasso <- function(y, X, min, alpha) {
    .Call('_VIPER_fitting_lasso', PACKAGE = 'VIPER', y, X, min, alpha)
}

log_factorial <- function(Y) {
    .Call('_VIPER_log_factorial', PACKAGE = 'VIPER', Y)
}

log_factorial_calculated <- function(N) {
    .Call('_VIPER_log_factorial_calculated', PACKAGE = 'VIPER', N)
}

alpha_optim <- function(val) {
    .Call('_VIPER_alpha_optim', PACKAGE = 'VIPER', val)
}

log_poisson_likelihood_mix <- function(Y, psi, mu, n, log_factorial_Y) {
    .Call('_VIPER_log_poisson_likelihood_mix', PACKAGE = 'VIPER', Y, psi, mu, n, log_factorial_Y)
}

gradient_all_mix <- function(Y, psi, mu, posterior_y, n1) {
    .Call('_VIPER_gradient_all_mix', PACKAGE = 'VIPER', Y, psi, mu, posterior_y, n1)
}

gradient_all_combined_mix <- function(Y, psi, mu, posterior1, n1) {
    .Call('_VIPER_gradient_all_combined_mix', PACKAGE = 'VIPER', Y, psi, mu, posterior1, n1)
}

test_stepsize_for_psi_mix <- function(Y, gra_psi, ll, psi, mu, n1, gamma, down, log_factorial_Y) {
    .Call('_VIPER_test_stepsize_for_psi_mix', PACKAGE = 'VIPER', Y, gra_psi, ll, psi, mu, n1, gamma, down, log_factorial_Y)
}

test_stepsize_for_mu_mix <- function(Y, gra_mu, ll, psi, mu, n1, gamma, down, log_factorial_Y) {
    .Call('_VIPER_test_stepsize_for_mu_mix', PACKAGE = 'VIPER', Y, gra_mu, ll, psi, mu, n1, gamma, down, log_factorial_Y)
}

gradient_descent_mix <- function(Y, n1, mixing_weights_Y, posterior_Y, psi, mu, log_factorial_Y, steps, gamma, down) {
    .Call('_VIPER_gradient_descent_mix', PACKAGE = 'VIPER', Y, n1, mixing_weights_Y, posterior_Y, psi, mu, log_factorial_Y, steps, gamma, down)
}

take_exp_weight <- function(x) {
    .Call('_VIPER_take_exp_weight', PACKAGE = 'VIPER', x)
}

EM_discrete_mix <- function(Y, steps, iter, gamma, down, cutoff) {
    .Call('_VIPER_EM_discrete_mix', PACKAGE = 'VIPER', Y, steps, iter, gamma, down, cutoff)
}

gradient_descent_mix_easy <- function(Y, n1, mixing_weights_Y, posterior_Y, psi, mu, log_factorial_Y, steps, down) {
    .Call('_VIPER_gradient_descent_mix_easy', PACKAGE = 'VIPER', Y, n1, mixing_weights_Y, posterior_Y, psi, mu, log_factorial_Y, steps, down)
}

EM_discrete_mix_easy <- function(Y, steps, iter, down, cutoff) {
    .Call('_VIPER_EM_discrete_mix_easy', PACKAGE = 'VIPER', Y, steps, iter, down, cutoff)
}

reweighting_sum_new_posterior_expectation_C <- function(Ymat, Yflagmat, Ycountmat, Y, Yflag, prior_weight) {
    .Call('_VIPER_reweighting_sum_new_posterior_expectation_C', PACKAGE = 'VIPER', Ymat, Yflagmat, Ycountmat, Y, Yflag, prior_weight)
}

reweighting_sum_new_posterior_expectation_simplified_C <- function(Ymat, Yflagmat, Ycountmat, Y, Yflag, prior_weight) {
    .Call('_VIPER_reweighting_sum_new_posterior_expectation_simplified_C', PACKAGE = 'VIPER', Ymat, Yflagmat, Ycountmat, Y, Yflag, prior_weight)
}

imputation_by_samples_posterior_expectation <- function(data, selected_logxx, logxx, zero_matrix, xx, n, p, minbool, alpha) {
    .Call('_VIPER_imputation_by_samples_posterior_expectation', PACKAGE = 'VIPER', data, selected_logxx, logxx, zero_matrix, xx, n, p, minbool, alpha)
}

imputation_by_samples_posterior_expectation_simplified <- function(data, selected_logxx, logxx, zero_matrix, xx, n, p, minbool, alpha) {
    .Call('_VIPER_imputation_by_samples_posterior_expectation_simplified', PACKAGE = 'VIPER', data, selected_logxx, logxx, zero_matrix, xx, n, p, minbool, alpha)
}