#' @title tSNE map

#' @description Visualizing the k-means or model-based clusters using tSNE maps

#' @param object \code{DISCBIO} class object.

#' @importFrom graphics text

#' @return A plot of t-SNEs.

setGeneric("plottSNE", function(object) {

  standardGeneric("plottSNE")

})

#' @rdname plottSNE

#' @export

setMethod(

  "plottSNE",

  signature = "DISCBIO",

  definition = function(object) {

    # ======================================================================

    # Validating

    # ======================================================================

    ran_k <- length(object@tsne) > 0

    ran_m <- length(object@MBtsne) > 0

    if (ran_k) {

      part <- object@kmeans$kpart

      x <- object@tsne

    } else if (ran_m) {

      part <- object@MBclusters$clusterid

      x <- object@MBtsne

    } else {

      stop("run comptsne before plottSNE")

    }

    # ======================================================================

    # Plotting

    # ======================================================================

    col <- c("black", "blue", "green", "red", "yellow", "gray")

    LEN <- length(levels(factor(part)))

    plot(

      x,

      las = 1,

      xlab = "Dim 1",

      ylab = "Dim 2",

      pch = 20,

      cex = 1.5,

      col = "lightgrey"

    )

    for (i in seq_len(LEN)) {

      if (sum(part == i) > 0) {

        text(

          x[part == i, 1],

          x[part == i, 2],

          i,

          col = col[i],

          cex = .75,

          font = 4

        )

      }

    }

  }

)