R/dimarDoOptimalImputation.R

In kreutz-lab/DIMAR: Data-driven selection of an imputation algorithm in R

#' dimarDoOptimalImputation
#'
#' @description Performs imputation of the quantitative matrix with the given method (optimally selected by DIMA)
#' @return Imputed matrix
#' @param mtx Quantitative matrix
#' @param method Optimal imputation method
#' @param lib R package of imputation method
#' @export dimarDoOptimalImputation
#' @examples
#' mtx <- matrix(rnorm(1000),nrow=100)
#' mtx[sample(c(1:1000),100)] <- NA
#' Imp <- dimarDoOptimalImputation(mtx, 'impSeq')

dimarDoOptimalImputation <- function(mtx, method, lib = NULL) {
  m <- 0
  Imp <- NULL
  while (is.null(Imp) || any(is.na(Imp))) {
    m <- m + 1
    eval(parse(text = paste('require(', dimarGetLib(method[m]), ')')))
    Imp <- dimarDoImputationsR(mtx, method[m], dimarGetLib(method[m]))
  }
  Imputation <- as.matrix(Imp[, 1:ncol(mtx)])
  print(paste('Imputation of input data with algorithm', method[m], 'is performed.'))
  Imp <- list(Imputation,method[m])
  names(Imp) <- c('Imputation','method')
  return(Imp)
}