#' @title tSNE map for K-means clustering with symbols

#' @description Visualizing the K-means clusters using tSNE maps

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

#' @param types If types=NULL then the names of the cells will be grouped

#'   automatically. Default is NULL

#' @param legloc A keyword from the list "bottomright", "bottom", "bottomleft",

#'   "left", "topleft", "top", "topright", "right" and "center". Default is

#'   "bottomright"

setGeneric(

  "plotSymbolstSNE",

  function(object, types = NULL, legloc = "bottomright") {

    standardGeneric("plotSymbolstSNE")

  }

)

#' @export

#' @return Plot of tsne objet slot, grouped by gene.

#' @rdname plotSymbolstSNE

setMethod(

  "plotSymbolstSNE",

  signature = "DISCBIO",

  definition = function(object, types, legloc = "bottomright") {

    if (is.null(types)) {

      types <- names(object@fdata)

    }

    if (length(object@tsne) == 0) {

      stop("run comptsne before plotSymbolstSNE")

    }

    if (length(types) != ncol(object@fdata)) {

      stop(

        "types argument has wrong length.",

        "Length has to equal to the column number of object@ndata"

      )

    }

    coloc <- rainbow(length(unique(types)))

    syms <- vector()

    plot(

      object@tsne,

      xlab = "Dim 1",

      ylab = "Dim 2",

      pch = 20,

      col = "grey"

    )

    for (i in seq_len(length(unique(types)))) {

      f <- types == sort(unique(types))[i]

      syms <- append(syms, ((i - 1) %% 25) + 1)

      points(

        object@tsne[f, 1],

        object@tsne[f, 2],

        col = coloc[i],

        pch = ((i - 1) %% 25) + 1,

        cex = 1

      )

    }

    legend(legloc, legend = sort(unique(types)), col = coloc, pch = syms)

  }

)