R/mnrva_item_matrix.R

In CrumpLab/minerva: Helper Functions for MINERVA modeling

#' Create a matrix of items
#'
#' @param n_items integer number of items to create (rows)
#' @param vec_length integer (even) number of features in each item, or vector length
#' @param all_unique logical default is FALSE, setting to TRUE ensures that all item entries are unique. Currently this is accomplished by brute force (iterating and checking until the entire matrix).
#'
#' @return matrix items across rows, and features across columns
#' @details This functions creates a matrix of items. Each item is a randomly permuted vector of 1s and -1s.
#' @export
#'
#' @examples
#' 
#' mnrva_item_matrix(n_items = 5, vec_length = 10)
#' mnrva_item_matrix(n_items = 5, vec_length = 10, all_unique = TRUE)
#' 
mnrva_item_matrix <- function(n_items = 5,
                              vec_length = 10,
                              all_unique = FALSE,
                              max_iteration = 5) {
  
  # return matrix without checking for unique rows
  if (all_unique == FALSE) {
    temp_mat <- t(replicate(n_items, mnrva_single_rvector(vec_length)))
    message(paste("rows are all unique: ",mnrva_check_unique(temp_mat)))
    return(temp_mat)
  }
  
  # iterate until all rows are unique
  if (all_unique == TRUE) {
    max_iteration = 5
    for(i in 1:max_iteration){
      temp_mat <- t(replicate(n_items, mnrva_single_rvector(vec_length)))
      if(mnrva_check_unique(temp_mat) == TRUE){
        message(paste("rows are all unique: ",mnrva_check_unique(temp_mat)))
        return(temp_mat)
      }
      if(i == max_iteration && mnrva_check_unique(temp_mat) == FALSE){ 
        warning("Failed to find unique matrix")
      }
    }
  }
}