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# TODO extend this to adpcr
#' Binarize digital PCR data
#'
#' Transforms multinomial (number of molecules per partition) or continuous (fluorescence)
#' digital PCR data to binary (positive/negative partition) format.
#'
#' @aliases binarize
#' @param input object of the class \code{\linkS4class{adpcr}} or
#' \code{\linkS4class{dpcr}} with one of following types:\code{"ct"}, \code{"fluo"} or
#' \code{"nm"}.
#' @return object of the class \code{\linkS4class{adpcr}} or
#' \code{\linkS4class{dpcr}} (depending on \code{input}) with type \code{"np"}.
#' @author Michal Burdukiewicz.
#' @keywords manip
#' @export
#' @examples
#'
#' #adpcr object
#' rand_array <- sim_adpcr(200, 300, 100, pos_sums = FALSE, n_panels = 1)
#' binarize(rand_array)
#'
#' #dpcr object
#' rand_droplets <- sim_dpcr(200, 300, 100, pos_sums = FALSE, n_exp = 1)
#' binarize(rand_droplets)
binarize <- function(input) {
if (class(input) %in% c("adpcr", "dpcr")) {
if(slot(input, "type") %in% c("tp", "tnp"))
stop("Cannot binarize already binary data")
positive_threshold <- slot(input, "threshold")
} else {
stop("Input must have 'adpcr' or 'dpcr' class.")
}
bin_data <- slot(input, ".Data") >= positive_threshold
storage.mode(bin_data) <- "integer"
slot(input, ".Data") <- bin_data
slot(input, "type") <- "np"
slot(input, "threshold") <- 1
input
}
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