R/semi_pheatmap.R

In celda: CEllular Latent Dirichlet Allocation

# Adapted originally from the very excellent pheatmap package
# (https://cran.r-project.org/web/packages/pheatmap/index.html)

#' @importFrom gtable gtable
.lo <- function(rown,
                coln,
                nrow,
                ncol,
                cellHeight = NA,
                cellWidth = NA,
                treeHeightCol,
                treeHeightRow,
                legend,
                annotationRow,
                annotationCol,
                annotationColors,
                annotationLegend,
                annotationNamesRow,
                annotationNamesCol,
                main,
                fontSize,
                fontSizeRow,
                fontSizeCol,
                gapsRow,
                gapsCol,
                ...) {
  # Get height of colnames and length of rownames
  if (!is.null(coln[1]) |
    (!.is.na2(annotationRow) & annotationNamesRow)) {
    if (!is.null(coln[1])) {
      t <- coln
    } else {
      t <- ""
    }
    tw <- strwidth(t, units = "in", cex = fontSizeCol / fontSize)
    if (annotationNamesRow) {
      t <- c(t, colnames(annotationRow))
      tw <- c(tw, strwidth(colnames(annotationRow), units = "in"))
    }
    longestColn <- which.max(tw)
    gp <- list(fontSize = ifelse(longestColn <= length(coln),
      fontSizeCol,
      fontSize
    ), ...)
    colnHeight <- unit(
      1,
      "grobheight",
      textGrob(t[longestColn],
        rot = 90,
        gp = do.call(gpar, gp)
      )
    ) +
      unit(10, "bigpts")
  } else {
    colnHeight <- unit(5, "bigpts")
  }

  if (!is.null(rown[1])) {
    t <- rown
    tw <- strwidth(t, units = "in", cex = fontSizeRow / fontSize)
    if (annotationNamesCol) {
      t <- c(t, colnames(annotationCol))
      tw <- c(tw, strwidth(colnames(annotationCol), units = "in"))
    }
    longestRown <- which.max(tw)
    gp <- list(fontSize = ifelse(longestRown <= length(rown),
      fontSizeRow,
      fontSize
    ), ...)
    rownWidth <- unit(
      1,
      "grobwidth",
      textGrob(t[longestRown],
        gp = do.call(gpar, gp)
      )
    ) +
      unit(10, "bigpts")
  } else {
    rownWidth <- unit(5, "bigpts")
  }

  gp <- list(fontSize = fontSize, ...)
  # Legend position
  if (!.is.na2(legend)) {
    longestBreak <- which.max(nchar(names(legend)))
    longestBreak <- unit(
      1.1,
      "grobwidth",
      textGrob(as.character(names(legend))[longestBreak],
        gp = do.call(gpar, gp)
      )
    )
    titleLength <- unit(
      1.1,
      "grobwidth",
      textGrob("Scale",
        gp = gpar(
          fontface = "bold",
          ...
        )
      )
    )
    legendWidth <- unit(12, "bigpts") + longestBreak * 1.2
    legendWidth <- max(titleLength, legendWidth)
  } else {
    legendWidth <- unit(0, "bigpts")
  }

  # Set main title height
  if (is.na(main)) {
    mainHeight <- unit(0, "npc")
  } else {
    mainHeight <- unit(
      1.5,
      "grobheight",
      textGrob(main,
        gp = gpar(
          fontSize = 1.3 * fontSize,
          ...
        )
      )
    )
  }

  # Column annotations
  textheight <- unit(fontSize, "bigpts")

  if (!.is.na2(annotationCol)) {
    # Column annotation height
    annotColHeight <-
      ncol(annotationCol) *
      (textheight + unit(2, "bigpts")) +
      unit(2, "bigpts")

    # Width of the correponding legend
    t <- c(as.vector(as.matrix(annotationCol)), colnames(annotationCol))
    annotColLegendWidth <- unit(
      1.2,
      "grobwidth",
      textGrob(t[which.max(nchar(t))],
        gp = gpar(...)
      )
    ) +
      unit(12, "bigpts")
    if (!annotationLegend) {
      annotColLegendWidth <- unit(0, "npc")
    }
  } else {
    annotColHeight <- unit(0, "bigpts")
    annotColLegendWidth <- unit(0, "bigpts")
  }

  # Row annotations
  if (!.is.na2(annotationRow)) {
    # Row annotation width
    annotRowWidth <- ncol(annotationRow) *
      (textheight + unit(2, "bigpts")) +
      unit(2, "bigpts")

    # Width of the correponding legend
    t <- c(
      as.vector(as.matrix(annotationRow)),
      colnames(annotationRow)
    )
    annotRowLegendWidth <- unit(
      1.2,
      "grobwidth",
      textGrob(t[which.max(nchar(t))],
        gp = gpar(...)
      )
    ) +
      unit(
        12,
        "bigpts"
      )

    if (!annotationLegend) {
      annotRowLegendWidth <- unit(0, "npc")
    }
  } else {
    annotRowWidth <- unit(0, "bigpts")
    annotRowLegendWidth <- unit(0, "bigpts")
  }

  annotLegendWidth <- max(annotRowLegendWidth, annotColLegendWidth)

  # Tree height
  treeHeightCol <- unit(treeHeightCol, "bigpts") + unit(5, "bigpts")
  treeHeightRow <- unit(treeHeightRow, "bigpts") + unit(5, "bigpts")

  # Set cell sizes
  if (is.na(cellWidth)) {
    matWidth <- unit(1, "npc") -
      rownWidth -
      legendWidth -
      treeHeightRow -
      annotRowWidth -
      annotLegendWidth
  } else {
    matWidth <- unit(cellWidth * ncol, "bigpts") +
      length(gapsCol) *
        unit(0, "bigpts")
  }

  if (is.na(cellHeight)) {
    matHeight <- unit(1, "npc") -
      mainHeight -
      colnHeight -
      treeHeightCol -
      annotColHeight
  } else {
    matHeight <- unit(cellHeight * nrow, "bigpts") +
      length(gapsRow) *
        unit(0, "bigpts")
  }

  # Produce gtable
  gt <- gtable::gtable(
    widths = unit.c(
      treeHeightRow,
      annotRowWidth,
      matWidth,
      rownWidth,
      legendWidth,
      annotLegendWidth
    ),
    heights = unit.c(
      mainHeight,
      treeHeightCol,
      annotColHeight,
      matHeight,
      colnHeight
    ),
    vp = viewport(gp = do.call(gpar, gp))
  )

  cw <- convertWidth(matWidth -
    (length(gapsCol) * unit(0, "bigpts")),
  "bigpts",
  valueOnly = TRUE
  ) / ncol
  ch <- convertHeight(matHeight -
    (length(gapsRow) * unit(0, "bigpts")),
  "bigpts",
  valueOnly = TRUE
  ) / nrow

  # Return minimal cell dimension in bigpts to decide if borders are drawn
  mindim <- min(cw, ch)

  res <- list(gt = gt, mindim = mindim)

  return(res)
}

.findCoordinates <- function(n, gaps, m = seq(1, n)) {
  if (length(gaps) == 0) {
    return(list(
      coord = unit(m / n, "npc"),
      size = unit(1 / n, "npc")
    ))
  }

  if (max(gaps) > n) {
    stop("Gaps do not match with matrix size")
  }

  size <- (1 / n) *
    (unit(1, "npc") - length(gaps) * unit("0", "bigpts"))

  gaps2 <- base::apply(vapply(
    gaps,
    function(gap, x) {
      x > gap
    },
    integer(n), m
  ), 1, sum)
  coord <- m * size + (gaps2 * unit("0", "bigpts"))

  return(list(coord = coord, size = size))
}

.drawDendrogram <- function(hc, gaps, horizontal = TRUE) {
  h <- hc$height / max(hc$height) / 1.05
  m <- hc$merge
  o <- hc$order
  n <- length(o)

  m[m > 0] <- n + m[m > 0]
  m[m < 0] <- abs(m[m < 0])

  dist <- matrix(0,
    nrow = 2 * n - 1,
    ncol = 2,
    dimnames = list(NULL, c("x", "y"))
  )
  dist[seq(1, n), 1] <- 1 / n / 2 + (1 / n) *
    (match(seq(1, n), o) - 1)

  for (i in seq(1, nrow(m))) {
    dist[n + i, 1] <- (dist[m[i, 1], 1] + dist[m[i, 2], 1]) / 2
    dist[n + i, 2] <- h[i]
  }

  drawConnection <- function(x1, x2, y1, y2, y) {
    res <- list(
      x = c(x1, x1, x2, x2),
      y = c(y1, y, y, y2)
    )

    return(res)
  }

  x <- rep(NA, nrow(m) * 4)
  y <- rep(NA, nrow(m) * 4)
  id <- rep(seq(nrow(m)), rep(4, nrow(m)))

  for (i in seq(1, nrow(m))) {
    c <- drawConnection(
      dist[m[i, 1], 1],
      dist[m[i, 2], 1],
      dist[m[i, 1], 2],
      dist[m[i, 2], 2],
      h[i]
    )
    k <- (i - 1) * 4 + 1
    x[seq(k, k + 3)] <- c$x
    y[seq(k, k + 3)] <- c$y
  }

  x <- .findCoordinates(n, gaps, x * n)$coord
  y <- unit(y, "npc")

  if (!horizontal) {
    a <- x
    x <- unit(1, "npc") - y
    y <- unit(1, "npc") - a
  }
  res <- polylineGrob(x = x, y = y, id = id)

  return(res)
}

.drawMatrix <- function(matrix,
                        borderColor,
                        gapsRows,
                        gapsCols,
                        fmat,
                        fontSizeNumber,
                        numberColor) {
  n <- nrow(matrix)
  m <- ncol(matrix)

  coordX <- .findCoordinates(m, gapsCols)
  coordY <- .findCoordinates(n, gapsRows)

  x <- coordX$coord -
    0.5 * coordX$size
  y <- unit(1, "npc") -
    (coordY$coord - 0.5 * coordY$size)

  coord <- expand.grid(y = y, x = x)

  res <- gList()

  res[["rect"]] <- rectGrob(
    x = coord$x,
    y = coord$y,
    width = coordX$size,
    height = coordY$size,
    gp = gpar(fill = matrix, col = borderColor)
  )

  if (attr(fmat, "draw")) {
    res[["text"]] <- textGrob(
      x = coord$x,
      y = coord$y,
      label = fmat,
      gp = gpar(col = numberColor, fontSize = fontSizeNumber)
    )
  }

  res <- gTree(children = res)

  return(res)
}

.drawColnames <- function(coln, gaps, ...) {
  coord <- .findCoordinates(length(coln), gaps)
  x <- coord$coord - 0.5 * coord$size

  res <- textGrob(coln,
    x = x,
    y = unit(1, "npc") -
      unit(3, "bigpts"),
    vjust = 0.5,
    hjust = 0,
    rot = 270,
    gp = gpar(...)
  )

  return(res)
}

.drawRownames <- function(rown, gaps, ...) {
  coord <- .findCoordinates(length(rown), gaps)
  y <- unit(1, "npc") - (coord$coord - 0.5 * coord$size)

  res <- textGrob(rown,
    x = unit(3, "bigpts"),
    y = y,
    vjust = 0.5,
    hjust = 0,
    gp = gpar(...)
  )

  return(res)
}

.drawLegend <- function(color, breaks, legend, ...) {
  height <- min(unit(1, "npc"), unit(150, "bigpts"))

  legendPos <- (legend - min(breaks)) / (max(breaks) - min(breaks))
  legendPos <- height * legendPos + (unit(1, "npc") - height)

  breaks <- (breaks - min(breaks)) / (max(breaks) - min(breaks))
  breaks <- height * breaks + (unit(1, "npc") - height)

  h <- breaks[-1] - breaks[-length(breaks)]

  rect <- rectGrob(
    x = 0,
    y = breaks[-length(breaks)],
    width = unit(10, "bigpts"),
    height = h,
    hjust = 0,
    vjust = 0,
    gp = gpar(fill = color, col = "#FFFFFF00")
  )

  text <- textGrob(names(legend),
    x = unit(14, "bigpts"),
    y = legendPos,
    hjust = 0,
    gp = gpar(...)
  )

  res <- grobTree(rect, text)

  return(res)
}

.convertAnnotations <- function(annotation, annotationColors) {
  new <- annotation
  for (i in seq(ncol(annotation))) {
    a <- annotation[, i]
    b <- annotationColors[[colnames(annotation)[i]]]
    if (is.character(a) | is.factor(a)) {
      a <- as.character(a)

      if (length(setdiff(setdiff(a, NA), names(b))) > 0) {
        stop(sprintf(
          "Factor levels on variable %s do not match
                        with annotationColors",
          colnames(annotation)[i]
        ))
      }
      new[, i] <- b[a]
    } else {
      a <- cut(a, breaks = 100)
      new[, i] <- colorRampPalette(b)(100)[a]
    }
  }
  return(as.matrix(new))
}

.drawAnnotations <- function(convertedAnnotations,
                             borderColor,
                             gaps,
                             fontSize,
                             horizontal) {
  n <- ncol(convertedAnnotations)
  m <- nrow(convertedAnnotations)

  coordX <- .findCoordinates(m, gaps)

  x <- coordX$coord - 0.5 * coordX$size

  # y = cumsum(rep(fontSize, n)) - 4 + cumsum(rep(2, n))
  y <- cumsum(rep(fontSize, n)) +
    cumsum(rep(2, n)) -
    fontSize / 2 + 1
  y <- unit(y, "bigpts")

  if (horizontal) {
    coord <- expand.grid(x = x, y = y)
    res <- rectGrob(
      x = coord$x,
      y = coord$y,
      width = coordX$size,
      height = unit(fontSize, "bigpts"),
      gp = gpar(fill = convertedAnnotations, col = borderColor)
    )
  } else {
    a <- x
    x <- unit(1, "npc") - y
    y <- unit(1, "npc") - a

    coord <- expand.grid(y = y, x = x)
    res <- rectGrob(
      x = coord$x,
      y = coord$y,
      width = unit(fontSize, "bigpts"),
      height = coordX$size,
      gp = gpar(fill = convertedAnnotations, col = borderColor)
    )
  }

  return(res)
}

.drawAnnotationNames <- function(annotations, fontSize, horizontal) {
  n <- ncol(annotations)

  x <- unit(3, "bigpts")

  y <- cumsum(rep(fontSize, n)) +
    cumsum(rep(2, n)) -
    fontSize / 2 + 1

  y <- unit(y, "bigpts")

  if (horizontal) {
    res <- textGrob(colnames(annotations),
      x = x,
      y = y,
      hjust = 0,
      gp = gpar(fontSize = fontSize, fontface = 2)
    )
  } else {
    a <- x
    x <- unit(1, "npc") - y
    y <- unit(1, "npc") - a

    res <- textGrob(colnames(annotations),
      x = x,
      y = y,
      vjust = 0.5,
      hjust = 0,
      rot = 270,
      gp = gpar(fontSize = fontSize, fontface = 2)
    )
  }

  return(res)
}

.drawAnnotationLegend <- function(annotation,
                                  annotationColors,
                                  borderColor,
                                  ...) {
  y <- unit(1, "npc")
  textHeight <- unit(
    1,
    "grobheight",
    textGrob("FGH", gp = gpar(...))
  )

  res <- gList()
  for (i in names(annotation)) {
    res[[i]] <- textGrob(i,
      x = 0,
      y = y,
      vjust = 1,
      hjust = 0,
      gp = gpar(fontface = "bold", ...)
    )

    y <- y - 1.5 * textHeight
    if (is.character(annotation[[i]]) |
      is.factor(annotation[[i]])) {
      n <- length(annotationColors[[i]])
      yy <- y - (seq(n) - 1) * 2 * textHeight

      res[[paste(i, "r")]] <- rectGrob(
        x = unit(0, "npc"),
        y = yy,
        hjust = 0,
        vjust = 1,
        height = 2 * textHeight,
        width = 2 * textHeight,
        gp = gpar(col = borderColor, fill = annotationColors[[i]])
      )

      res[[paste(i, "t")]] <- textGrob(names(annotationColors[[i]]),
        x = textHeight * 2.4,
        y = yy - textHeight,
        hjust = 0,
        vjust = 0.5,
        gp = gpar(...)
      )

      y <- y - n * 2 * textHeight
    } else {
      yy <- y - 8 * textHeight + seq(0, 1, 0.25)[-1] * 8 * textHeight
      h <- 8 * textHeight * 0.25

      res[[paste(i, "r")]] <- rectGrob(
        x = unit(0, "npc"),
        y = yy,
        hjust = 0,
        vjust = 1,
        height = h,
        width = 2 * textHeight,
        gp = gpar(
          col = NA,
          fill = colorRampPalette(annotationColors[[i]])(4)
        )
      )
      res[[paste(i, "r2")]] <- rectGrob(
        x = unit(0, "npc"),
        y = y,
        hjust = 0,
        vjust = 1,
        height = 8 * textHeight,
        width = 2 * textHeight,
        gp = gpar(col = borderColor, fill = NA)
      )

      txt <- rev(range(grid::grid.pretty(range(annotation[[i]],
        na.rm = TRUE
      ))))

      yy <- y - c(1, 7) * textHeight
      res[[paste(i, "t")]] <- textGrob(txt,
        x = textHeight * 2.4,
        y = yy,
        hjust = 0,
        vjust = 0.5,
        gp = gpar(...)
      )
      y <- y - 8 * textHeight
    }
    y <- y - 1.5 * textHeight
  }

  res <- gTree(children = res)

  return(res)
}

.drawMain <- function(text, ...) {
  res <- textGrob(text, gp = gpar(fontface = "bold", ...))

  return(res)
}

vplayout <- function(x, y) {
  return(viewport(layout.pos.row = x, layout.pos.col = y))
}

#' @importFrom gtable gtable_height
#' @importFrom gtable gtable_width
#' @importFrom gtable gtable_add_grob
#' @import grDevices
.heatmapMotor <- function(matrix,
                          borderColor,
                          cellWidth,
                          cellHeight,
                          treeCol,
                          treeRow,
                          treeHeightCol,
                          treeHeightRow,
                          fileName,
                          width,
                          height,
                          breaks,
                          color,
                          legend,
                          annotationRow,
                          annotationCol,
                          annotationColors,
                          annotationLegend,
                          annotationNamesRow,
                          annotationNamesCol,
                          main,
                          fontSize,
                          fontSizeRow,
                          fontSizeCol,
                          fmat,
                          fontSizeNumber,
                          numberColor,
                          gapsCol,
                          gapsRow,
                          labelsRow,
                          labelsCol,
                          ...) {
  # Set layout
  lo <- .lo(
    coln = labelsCol,
    rown = labelsRow,
    nrow = nrow(matrix),
    ncol = ncol(matrix),
    cellWidth = cellWidth,
    cellHeight = cellHeight,
    treeHeightCol = treeHeightCol,
    treeHeightRow = treeHeightRow,
    legend = legend,
    annotationCol = annotationCol,
    annotationRow = annotationRow,
    annotationColors = annotationColors,
    annotationLegend = annotationLegend,
    annotationNamesRow = annotationNamesRow,
    annotationNamesCol = annotationNamesCol,
    main = main,
    fontSize = fontSize,
    fontSizeRow = fontSizeRow,
    fontSizeCol = fontSizeCol,
    gapsRow = gapsRow,
    gapsCol = gapsCol,
    ...
  )

  res <- lo$gt
  mindim <- lo$mindim

  if (!is.na(fileName)) {
    if (is.na(height)) {
      height <- convertHeight(gtable::gtable_height(res),
        "inches",
        valueOnly = TRUE
      )
    }
    if (is.na(width)) {
      width <- convertWidth(gtable::gtable_width(res),
        "inches",
        valueOnly = TRUE
      )
    }

    # Get file type
    r <- regexpr("\\.[a-zA-Z]*$", fileName)
    if (r == -1) {
      stop("Improper fileName")
    }
    ending <- substr(
      fileName,
      r + 1,
      r + attr(r, "match.length")
    )

    f <- switch(ending,
      pdf = function(x, ...) {
        pdf(x, ...)
      },
      png = function(x, ...) {
        png(x,
          units = "in",
          res = 300, ...
        )
      },
      jpeg = function(x, ...) {
        jpeg(x,
          units = "in",
          res = 300, ...
        )
      },
      jpg = function(x, ...) {
        jpeg(x,
          units = "in",
          res = 300, ...
        )
      },
      tiff = function(x, ...) {
        tiff(x,
          units = "in",
          res = 300,
          compression = "lzw",
          ...
        )
      },
      bmp = function(x, ...) {
        bmp(x,
          units = "in",
          res = 300, ...
        )
      },
      stop("File type should be: pdf, png, bmp, jpg, tiff")
    )

    # print(sprintf("height:%f width:%f", height, width))

    # gt = .heatmapMotor(matrix,
    #     cellWidth = cellWidth,
    #     cellHeight = cellHeight,
    #     borderColor = borderColor,
    #     treeCol = treeCol,
    #     treeRow = treeRow,
    #     treeHeightCol = treeHeightCol,
    #     treeHeightRow = treeHeightRow,
    #     breaks = breaks,
    #     color = color,
    #     legend = legend,
    #     annotationCol = annotationCol,
    #     annotationRow = annotationRow,
    #     annotationColors = annotationColors,
    #     annotationLegend = annotationLegend,
    #     fileName = NA, main = main,
    #     fontSize = fontSize,
    #     fontSizeRow = fontSizeRow,
    #     fontSizeCol = fontSizeCol,
    #     fmat = fmat,
    #     fontSizeNumber =  fontSizeNumber,
    #     numberColor = numberColor,
    #     labelsRow = labelsRow,
    #     labelsCol = labelsCol,
    #     gapsCol = gapsCol,
    #     gapsRow = gapsRow, ...)

    f(fileName, height = height, width = width)
    gt <- .heatmapMotor(matrix,
      cellWidth = cellWidth,
      cellHeight = cellHeight,
      borderColor = borderColor,
      treeCol = treeCol,
      treeRow = treeRow,
      treeHeightCol = treeHeightCol,
      treeHeightRow = treeHeightRow,
      breaks = breaks,
      color = color,
      legend = legend,
      annotationCol = annotationCol,
      annotationRow = annotationRow,
      annotationColors = annotationColors,
      annotationLegend = annotationLegend,
      annotationNamesRow = annotationNamesRow,
      annotationNamesCol = annotationNamesCol,
      fileName = NA,
      main = main,
      fontSize = fontSize,
      fontSizeRow = fontSizeRow,
      fontSizeCol = fontSizeCol,
      fmat = fmat,
      fontSizeNumber = fontSizeNumber,
      numberColor = numberColor,
      labelsRow = labelsRow,
      labelsCol = labelsCol,
      gapsCol = gapsCol,
      gapsRow = gapsRow,
      ...
    )
    grid.draw(gt)
    dev.off()

    return(gt)
  }

  # Omit border color if cell size is too small
  if (mindim < 3) {
    borderColor <- NA
  }

  # Draw title
  if (!is.na(main)) {
    elem <- .drawMain(main, fontSize = 1.3 * fontSize, ...)
    res <- gtable::gtable_add_grob(res,
      elem,
      t = 1,
      l = 3,
      name = "main",
      clip = "off"
    )
  }

  # Draw tree for the columns
  if (!.is.na2(treeCol) & treeHeightCol != 0) {
    elem <- .drawDendrogram(treeCol, gapsCol, horizontal = TRUE)
    res <- gtable::gtable_add_grob(res,
      elem,
      t = 2,
      l = 3,
      name = "col_tree"
    )
  }

  # Draw tree for the rows
  if (!.is.na2(treeRow) & treeHeightRow != 0) {
    elem <- .drawDendrogram(treeRow, gapsRow, horizontal = FALSE)
    res <- gtable::gtable_add_grob(res,
      elem,
      t = 4,
      l = 1,
      name = "row_tree"
    )
  }

  # Draw matrix
  elem <- .drawMatrix(
    matrix,
    borderColor,
    gapsRow,
    gapsCol,
    fmat,
    fontSizeNumber,
    numberColor
  )

  res <- gtable::gtable_add_grob(res,
    elem,
    t = 4,
    l = 3,
    clip = "off",
    name = "matrix"
  )

  # Draw colnames
  if (length(labelsCol) != 0) {
    pars <- list(labelsCol,
      gaps = gapsCol,
      fontSize = fontSizeCol,
      ...
    )
    elem <- do.call(.drawColnames, pars)
    res <- gtable::gtable_add_grob(res,
      elem,
      t = 5,
      l = 3,
      clip = "off",
      name = "col_names"
    )
  }

  # Draw rownames
  if (length(labelsRow) != 0) {
    pars <- list(labelsRow,
      gaps = gapsRow,
      fontSize = fontSizeRow, ...
    )
    elem <- do.call(.drawRownames, pars)
    res <- gtable::gtable_add_grob(res,
      elem,
      t = 4,
      l = 4,
      clip = "off",
      name = "row_names"
    )
  }

  # Draw annotation tracks on cols
  if (!.is.na2(annotationCol)) {
    # Draw tracks
    convertedAnnotation <- .convertAnnotations(
      annotationCol,
      annotationColors
    )
    elem <- .drawAnnotations(convertedAnnotation,
      borderColor,
      gapsCol,
      fontSize,
      horizontal = TRUE
    )
    res <- gtable::gtable_add_grob(res,
      elem,
      t = 3,
      l = 3,
      clip = "off",
      name = "col_annotation"
    )

    # Draw names
    if (annotationNamesCol) {
      elem <- .drawAnnotationNames(annotationCol,
        fontSize,
        horizontal = TRUE
      )
      res <- gtable::gtable_add_grob(res,
        elem,
        t = 3,
        l = 4,
        clip = "off",
        name = "col_annotation_names"
      )
    }
  }

  # Draw annotation tracks on rows
  if (!.is.na2(annotationRow)) {
    # Draw tracks
    convertedAnnotation <- .convertAnnotations(
      annotationRow,
      annotationColors
    )
    elem <- .drawAnnotations(convertedAnnotation,
      borderColor,
      gapsRow,
      fontSize,
      horizontal = FALSE
    )
    res <- gtable::gtable_add_grob(res,
      elem,
      t = 4,
      l = 2,
      clip = "off",
      name = "row_annotation"
    )

    # Draw names
    if (annotationNamesRow) {
      elem <- .drawAnnotationNames(annotationRow,
        fontSize,
        horizontal = FALSE
      )
      res <- gtable::gtable_add_grob(res,
        elem,
        t = 5,
        l = 2,
        clip = "off",
        name = "row_annotation_names"
      )
    }
  }

  # Draw annotation legend
  annotation <- c(
    annotationCol[seq(length(annotationCol), 1)],
    annotationRow[seq(length(annotationRow), 1)]
  )
  annotation <- annotation[unlist(lapply(
    annotation,
    function(x) !.is.na2(x)
  ))]

  if (length(annotation) > 0 & annotationLegend) {
    elem <- .drawAnnotationLegend(annotation,
      annotationColors,
      borderColor,
      fontSize = fontSize,
      ...
    )

    t <- ifelse(is.null(labelsRow), 4, 3)
    res <- gtable::gtable_add_grob(res,
      elem,
      t = t,
      l = 6,
      b = 5,
      clip = "off",
      name = "annotationLegend"
    )
  }

  # Draw legend
  if (!.is.na2(legend)) {
    elem <- .drawLegend(color, breaks, legend, fontSize = fontSize, ...)

    t <- ifelse(is.null(labelsRow), 4, 3)
    res <- gtable::gtable_add_grob(res,
      elem,
      t = t,
      l = 5,
      b = 5,
      clip = "off",
      name = "legend"
    )
  }

  return(res)
}

.generateBreaks <- function(x, n, center = FALSE) {
  if (center) {
    m <- max(abs(c(
      min(x, na.rm = TRUE),
      max(x, na.rm = TRUE)
    )))
    res <- seq(-m, m, length.out = n + 1)
  } else {
    res <- seq(min(x, na.rm = TRUE),
      max(x, na.rm = TRUE),
      length.out = n + 1
    )
  }

  return(res)
}

.scaleVecColours <- function(x, col = rainbow(10), breaks = NA) {
  return(col[as.numeric(cut(x, breaks = breaks, include.lowest = TRUE))])
}

.scaleColours <- function(mat,
                          col = rainbow(10),
                          breaks = NA) {
  mat <- as.matrix(mat)
  return(matrix(
    .scaleVecColours(as.vector(mat), col = col, breaks = breaks),
    nrow(mat),
    ncol(mat),
    dimnames = list(rownames(mat), colnames(mat))
  ))
}

## changed the original clusterMat() in the pheatmap.r
#' @importFrom scales hue_pal
.clusterMat <- function(mat, labels, distance, method) {
  # this funciton is going to change the .clusterMat() in pheatmap

  if (!(method %in% c(
    "ward.D",
    "ward.D2",
    "ward",
    "single",
    "complete",
    "average",
    "mcquitty",
    "median",
    "centroid"
  ))) {
    stop("clustering method has to one form the list:
            'ward',
            'ward.D',
            'ward.D2',
            'single',
            'complete',
            'average',
            'mcquitty',
            'median'
            or 'centroid'.")
  }

  class.label <- unique(labels)

  nGroup <- length(class.label) # [#group]
  # get "hclust" object for each group then wrap them up as group.hclust

  # distance function preparation
  dis <- function(mat, distance) {
    if (!(distance[1] %in% c(
      "correlation",
      "euclidean",
      "maximum",
      "manhattan",
      "canberra",
      "binary",
      "minkowski"
    )) &
      !methods::is(distance, "dist")) {
      stop(
        "distance has to be a dissimilarity structure as produced by",
        " dist or one measure  form the list: 'correlation',",
        " 'euclidean', 'maximum', 'manhattan', 'canberra', 'binary',",
        " 'minkowski'"
      )
    }

    if (distance[1] == "correlation") {
      # this part should be confirmed whether being wrong?
      # ToDo: how is the correlation matrix converted to a dsit matrix
      d <- stats::as.dist(1 - stats::cor(t(mat)))
    } else {
      d <- stats::dist(mat, method = distance)
    }

    return(d)
  }

  # initiate the final returning value: a "hclust" object
  cum.hclust <- list()

  if (nGroup == 1) {
    # matrix has only 1 group
    if (length(labels) == 1) {
      stop("only one row/column for the matrix")
    }
    group.hclust <- stats::hclust(dis(
      mat = mat,
      distance = distance
    ),
    method = method
    )

    cum.hclust <- group.hclust
  } else {
    #  matrix has more than 1 groups
    group.hclust <- vapply(
      class.label, function(x) {
        # get the positions of class label
        class.pos <- which(labels == x)

        if (length(class.pos) == 1) {
          # if only 1 row in the group return a manually made "hclust"
          # object
          sub.hclust <- as.list(seq(7))
          names(sub.hclust) <- c(
            "merge",
            "height",
            "order",
            "labels",
            "method",
            "call",
            "dist.method"
          )

          class(sub.hclust) <- "hclust"
          sub.hclust$merge <- matrix(c(0, 0), nrow = 1)
          sub.hclust$height <- 0
          sub.hclust$order <- 1
          return(sub.hclust)
        } else if (length(class.pos) > 1) {
          # if >1 rows return the "hclust" object
          return(stats::hclust(dis(
            mat = mat[class.pos, ],
            distance = distance
          ),
          method = method
          ))
        }
      },
      list(
        "merge" = 0,
        "height" = 0,
        "order" = 0,
        "labels" = 0,
        "method" = 0,
        "call" = 0,
        "dist.method" = 0
      )
    )
    # the length(group.hclust) is the [#group] == nGroup   ,
    # group.hclust[[i]] to get each "hclust"

    # then modify the "hclust" object and get them merged into one
    # "hclust" object

    # initiate the final "hclust" object
    cum.hclust <- group.hclust[, nGroup]

    # merge function preparation
    mergeHclust <- function(hclust1, hclust2) {
      # "hclust" object modifying function preparation
      if (hclust1$merge[1, 1] == 0 &
        hclust2$merge[1, 1] == 0) {
        # both groups have only 1 row
        hclustCom <- as.list(seq(7))
        names(hclustCom) <-
          c(
            "merge",
            "height",
            "order",
            "labels",
            "method",
            "call",
            "dist.method"
          )

        class(hclustCom) <- "hclust"
        hclustCom$merge <- matrix(c(-1, -2), nrow = 1)
        # check for different matrix whether 1 should be good
        hclustCom$height <- 1
        hclustCom$order <- c(1, 2)
        return(hclustCom)
      } else if (hclust1$merge[1, 1] != 0 &
        hclust2$merge[1, 1] != 0) {
        # both group have >1 rows

        # nodes in the hclust1 group, so actually the #rows should
        # be dim()[1]+1
        row.1 <- dim(hclust1$merge)[1]
        # nodes in the hclust2 group
        row.2 <- dim(hclust2$merge)[1]
        hclustCom <- list()
        mer <- hclust2$merge
        # modify the hclust2$merge matrix
        hclustCom$merge <- (mer > 0) *
          (mer + row.1) + (mer < 0) *
            (mer - row.1 - 1)
        # combine the merge matrix from the 2 groups
        hclustCom$merge <- rbind(
          hclust1$merge,
          hclustCom$merge
        )
        hclustCom$merge <- rbind(
          hclustCom$merge,
          c(row.1, row.1 + row.2)
        )
        hclustCom$height <- c(hclust1$height, hclust2$height)
        # check for different matrix whether 1 should be good
        hclustCom$height <- c(
          hclustCom$height,
          max(hclustCom$height) + 1
        )
        hclustCom$order <- c(
          hclust1$order,
          hclust2$order + row.1 + 1
        )
        class(hclustCom) <- "hclust"
      } else {
        # one group has only 1 row, the other group has >1 rows
        if (hclust1$merge[1, 1] == 0) {
          # hclust1 has 1 row , hclust2 has >1 rows

          # nodes in the hclust2 group
          row.2 <- dim(hclust2$merge)[1]
          hclustCom <- as.list(seq(7))
          names(hclustCom) <- c(
            "merge",
            "height",
            "order",
            "labels",
            "method",
            "call",
            "dist.method"
          )
          class(hclustCom) <- "hclust"
          mer <- hclust2$merge
          hclustCom$merge <- (mer > 0) *
            (mer) +
            (mer < 0) *
              (mer - 1)
          hclustCom$merge <- rbind(
            hclustCom$merge,
            c(-1, row.2)
          )
          # check for different matrix whether 1 should be good
          hclustCom$height <- c(
            hclust2$height,
            max(hclust2$height) + 1
          )
          hclustCom$order <- c(1, hclust2$order + 1)
        } else if (hclust2$merge[1, 1] == 0) {
          # the hclust1 has >1 rows , and hclust2 has 1 row

          # nodes in the hclust1 group
          row.1 <- dim(hclust1$merge)[1]
          hclustCom <- as.list(seq(1, 7))
          names(hclustCom) <-
            c(
              "merge",
              "height",
              "order",
              "labels",
              "method",
              "call",
              "dist.method"
            )
          class(hclustCom) <- "hclust"
          hclustCom$merge <- hclust1$merge
          hclustCom$merge <- rbind(
            hclustCom$merge,
            c(row.1, - (row.1 + 2))
          )
          hclustCom$height <- c(
            hclust1$height,
            max(hclust1$height) + 1
          )
          hclustCom$order <- c(
            hclust1$order,
            max(hclust1$order) + 1
          )
        }
      }

      return(hclustCom)
    }

    # merge the "hclust" object into the final one "hclust" object
    for (i in seq(nGroup - 1, 1, -1)) {
      cum.hclust <- mergeHclust(group.hclust[, i], cum.hclust)
    }
  }

  cum.hclust$labels <- NULL
  cum.hclust$call <- NULL
  cum.hclust$method <- NULL
  cum.hclust$dist.method <- NULL

  return(cum.hclust)
}

.scaleRows <- function(x) {
  m <- base::apply(x, 1, mean, na.rm = TRUE)
  s <- base::apply(x, 1, stats::sd, na.rm = TRUE)
  return((x - m) / s)
}

.scaleMat <- function(mat, scale) {
  if (!(scale %in% c("none", "row", "column"))) {
    stop("scale argument shoud take values: 'none', 'row' or 'column'")
  }
  mat <- switch(scale,
    none = mat,
    row = .scaleRows(mat),
    column = t(.scaleRows(t(mat)))
  )
  return(mat)
}

#' @importFrom scales dscale
#' @importFrom scales brewer_pal
.generateAnnotationColours <- function(annotation,
                                       annotationColors,
                                       drop) {
  if (.is.na2(annotationColors)) {
    annotationColors <- list()
  }
  count <- 0
  for (i in seq(length(annotation))) {
    annotation[[i]] <- annotation[[i]][!is.na(annotation[[i]])]
    if (is.character(annotation[[i]]) |
      is.factor(annotation[[i]])) {
      if (is.factor(annotation[[i]]) & !drop) {
        count <- count + length(levels(annotation[[i]]))
      } else {
        count <- count + length(unique(annotation[[i]]))
      }
    }
  }

  factorColors <- scales::dscale(
    factor(seq(1, count)),
    scales::hue_pal(l = 75)
  )

  contCounter <- 2
  for (i in seq(length(annotation))) {
    if (!(names(annotation)[i] %in% names(annotationColors))) {
      if (is.character(annotation[[i]]) |
        is.factor(annotation[[i]])) {
        n <- length(unique(annotation[[i]]))

        if (is.factor(annotation[[i]]) & !drop) {
          n <- length(levels(annotation[[i]]))
        }

        ind <- sample(seq_along(factorColors), n)
        annotationColors[[names(annotation)[i]]] <-
          factorColors[ind]
        l <- levels(as.factor(annotation[[i]]))
        l <- l[l %in% unique(annotation[[i]])]
        if (is.factor(annotation[[i]]) & !drop) {
          l <- levels(annotation[[i]])
        }

        names(annotationColors[[names(annotation)[i]]]) <- l
        factorColors <- factorColors[-ind]
      } else {
        annotationColors[[names(annotation)[i]]] <-
          scales::brewer_pal("seq", contCounter)(5)[seq(4)]
        contCounter <- contCounter + 1
      }
    }
  }
  return(annotationColors)
}


.findGaps <- function(tree, cutreeN) {
  v <- stats::cutree(tree, cutreeN)[tree$order]
  gaps <- which((v[-1] - v[-length(v)]) != 0)
  return(gaps)
}

.is.na2 <- function(x) {
  if (is.list(x) | length(x) > 1) {
    return(FALSE)
  }
  if (length(x) == 0) {
    return(TRUE)
  }

  return(is.na(x))
}

.identity2 <- function(x, ...) {
  return(x)
}

#' @title A function to draw clustered heatmaps.
#' @description A function to draw clustered heatmaps where one has better
#'  control over some graphical parameters such as cell size, etc.
#'
#' The function also allows to aggregate the rows using kmeans clustering.
#'  This is advisable if number of rows is so big that R cannot handle their
#'  hierarchical clustering anymore, roughly more than 1000. Instead of showing
#'  all the rows separately one can cluster the rows in advance and show only
#'  the cluster centers. The number of clusters can be tuned with parameter
#'  kmeansK.
#' @param mat numeric matrix of the values to be plotted.
#' @param color vector of colors used in heatmap.
#' @param kmeansK the number of kmeans clusters to make, if we want to
#'  agggregate the rows before drawing heatmap. If NA then the rows are not
#'  aggregated.
#' @param breaks Numeric vector. A sequence of numbers that covers the range
#'  of values in the normalized `counts`. Values in the normalized `matrix` are
#'  assigned to each bin in `breaks`. Each break is assigned to a unique color
#'  from `col`. If NULL, then breaks are calculated automatically. Default NULL.
#' @param borderColor color of cell borders on heatmap, use NA if no border
#'  should be drawn.
#' @param cellWidth individual cell width in points. If left as NA, then the
#'  values depend on the size of plotting window.
#' @param cellHeight individual cell height in points. If left as NA, then the
#'  values depend on the size of plotting window.
#' @param scale character indicating if the values should be centered and
#'  scaled in either the row direction or the column direction, or none.
#'  Corresponding values are \code{"row"}, \code{"column"} and \code{"none"}.
#' @param clusterRows boolean values determining if rows should be clustered or
#'  \code{hclust} object,
#' @param clusterCols boolean values determining if columns should be clustered
#'  or \code{hclust} object.
#' @param clusteringDistanceRows distance measure used in clustering rows.
#'  Possible values are \code{"correlation"} for Pearson correlation and all
#'  the distances supported by \code{\link{dist}}, such as \code{"euclidean"},
#'  etc. If the value is none of the above it is assumed that a distance matrix
#'  is provided.
#' @param clusteringDistanceCols distance measure used in clustering columns.
#'  Possible values the same as for clusteringDistanceRows.
#' @param clusteringMethod clustering method used. Accepts the same values as
#'  \code{\link{hclust}}.
#' @param clusteringCallback callback function to modify the clustering. Is
#'  called with two parameters: original \code{hclust} object and the matrix
#'  used for clustering. Must return a \code{hclust} object.
#' @param cutreeRows number of clusters the rows are divided into, based on the
#'  hierarchical clustering (using cutree), if rows are not clustered, the
#'  argument is ignored
#' @param cutreeCols similar to \code{cutreeRows}, but for columns
#' @param treeHeightRow the height of a tree for rows, if these are clustered.
#'  Default value 50 points.
#' @param treeHeightCol the height of a tree for columns, if these are
#'  clustered. Default value 50 points.
#' @param legend logical to determine if legend should be drawn or not.
#' @param legendBreaks vector of breakpoints for the legend.
#' @param legendLabels vector of labels for the \code{legendBreaks}.
#' @param annotationRow data frame that specifies the annotations shown on left
#'  side of the heatmap. Each row defines the features for a specific row. The
#'  rows in the data and in the annotation are matched using corresponding row
#'  names. Note that color schemes takes into account if variable is continuous
#'  or discrete.
#' @param annotationCol similar to annotationRow, but for columns.
#' @param annotation deprecated parameter that currently sets the annotationCol
#'  if it is missing.
#' @param annotationColors list for specifying annotationRow and
#'  annotationCol track colors manually. It is  possible to define the colors
#'  for only some of the features. Check examples for  details.
#' @param annotationLegend boolean value showing if the legend for annotation
#'  tracks should be drawn.
#' @param annotationNamesRow boolean value showing if the names for row
#'  annotation tracks should be drawn.
#' @param annotationNamesCol boolean value showing if the names for column
#'  annotation tracks should be drawn.
#' @param dropLevels logical to determine if unused levels are also shown in
#'  the legend.
#' @param showRownames boolean specifying if column names are be shown.
#' @param showColnames boolean specifying if column names are be shown.
#' @param main the title of the plot
#' @param fontSize base fontsize for the plot
#' @param fontSizeRow fontsize for rownames (Default: fontsize)
#' @param fontSizeCol fontsize for colnames (Default: fontsize)
#' @param displayNumbers logical determining if the numeric values are also
#'  printed to the cells. If this is a matrix (with same dimensions as original
#'  matrix), the contents of the matrix are shown instead of original values.
#' @param numberFormat format strings (C printf style) of the numbers shown in
#'  cells. For example "\code{\%.2f}" shows 2 decimal places and "\code{\%.1e}"
#'  shows exponential notation (see more in \code{\link{sprintf}}).
#' @param numberColor color of the text
#' @param fontSizeNumber fontsize of the numbers displayed in cells
#' @param gapsRow vector of row indices that show shere to put gaps into
#'  heatmap. Used only if the rows are not clustered. See \code{cutreeRow}
#'  to see how to introduce gaps to clustered rows.
#' @param gapsCol similar to gapsRow, but for columns.
#' @param labelsRow custom labels for rows that are used instead of rownames.
#' @param labelsCol similar to labelsRow, but for columns.
#' @param fileName file path where to save the picture. Filetype is decided by
#'  the extension in the path. Currently following formats are supported: png,
#'  pdf, tiff, bmp, jpeg. Even if the plot does not fit into the plotting
#'  window, the file size is calculated so that the plot would fit there,
#'  unless specified otherwise.
#' @param width manual option for determining the output file width in inches.
#' @param height manual option for determining the output file height in inches.
#' @param silent do not draw the plot (useful when using the gtable output)
#' @param rowLabel row cluster labels for semi-clustering
#' @param colLabel column cluster labels for semi-clustering
#' @param rowGroupOrder Vector. Specifies the order of feature clusters when
#'  semisupervised clustering is performed on the \code{y} labels.
#' @param colGroupOrder Vector. Specifies the order of cell clusters when
#'  semisupervised clustering is performed on the \code{z} labels.
#' @param \dots graphical parameters for the text used in plot. Parameters
#'  passed to \code{\link{grid.text}}, see \code{\link{gpar}}.
#' @return
#' Invisibly a list of components
#' \itemize{
#'     \item \code{treeRow} the clustering of rows as \code{\link{hclust}}
#'       object
#'     \item \code{treeCol} the clustering of columns as \code{\link{hclust}}
#'       object
#'     \item \code{kmeans} the kmeans clustering of rows if parameter
#'       \code{kmeansK} was specified
#' }
#' @author  Raivo Kolde <rkolde@@gmail.com>
#' #@examples
#' # Create test matrix
#' test = matrix(rnorm(200), 20, 10)
#' test[seq(10), seq(1, 10, 2)] = test[seq(10), seq(1, 10, 2)] + 3
#' test[seq(11, 20), seq(2, 10, 2)] = test[seq(11, 20), seq(2, 10, 2)] + 2
#' test[seq(15, 20), seq(2, 10, 2)] = test[seq(15, 20), seq(2, 10, 2)] + 4
#' colnames(test) = paste("Test", seq(10), sep = "")
#' rownames(test) = paste("Gene", seq(20), sep = "")
#'
#' # Draw heatmaps
#' pheatmap(test)
#' pheatmap(test, kmeansK = 2)
#' pheatmap(test, scale = "row", clusteringDistanceRows = "correlation")
#' pheatmap(test, color = colorRampPalette(c("navy",
#'     "white", "firebrick3"))(50))
#' pheatmap(test, cluster_row = FALSE)
#' pheatmap(test, legend = FALSE)
#'
#' # Show text within cells
#' pheatmap(test, displayNumbers = TRUE)
#' pheatmap(test, displayNumbers = TRUE, numberFormat = "\%.1e")
#' pheatmap(test, displayNumbers = matrix(ifelse(test > 5,
#'     "*", ""), nrow(test)))
#' pheatmap(test, cluster_row = FALSE,
#'     legendBreaks = seq(-1, 4), legendLabels = c("0",
#'     "1e-4", "1e-3", "1e-2", "1e-1", "1"))
#'
#' # Fix cell sizes and save to file with correct size
#' pheatmap(test, cellWidth = 15, cellHeight = 12, main = "Example heatmap")
#' pheatmap(test, cellWidth = 15, cellHeight = 12, fontSize = 8,
#'     fileName = "test.pdf")
#'
#' # Generate annotations for rows and columns
#' annotationCol = data.frame(CellType = factor(rep(c("CT1", "CT2"), 5)),
#'     Time = seq(5))
#' rownames(annotationCol) = paste("Test", seq(10), sep = "")
#'
#' annotationRow = data.frame(GeneClass = factor(rep(c("Path1",
#'    "Path2",
#'    "Path3"),
#'    c(10, 4, 6))))
#' rownames(annotationRow) = paste("Gene", seq(20), sep = "")
#'
#' # Display row and color annotations
#' pheatmap(test, annotationCol = annotationCol)
#' pheatmap(test, annotationCol = annotationCol, annotationLegend = FALSE)
#' pheatmap(test, annotationCol = annotationCol, annotationRow = annotationRow)
#'
#' # Specify colors
#' ann_colors = list(Time = c("white", "firebrick"),
#'     CellType = c(CT1 = "#1B9E77", CT2 = "#D95F02"),
#'     GeneClass = c(Path1 = "#7570B3", Path2 = "#E7298A", Path3 = "#66A61E"))
#'
#' pheatmap(test, annotationCol = annotationCol, annotationColors = ann_colors,
#'     main = "Title")
#' pheatmap(test, annotationCol = annotationCol, annotationRow = annotationRow,
#'     annotationColors = ann_colors)
#' pheatmap(test, annotationCol = annotationCol,
#'     annotationColors = ann_colors[2])
#'
#' # Gaps in heatmaps
#' pheatmap(test, annotationCol = annotationCol, clusterRows = FALSE,
#'     gapsRow = c(10, 14))
#' pheatmap(test, annotationCol = annotationCol, clusterRows = FALSE,
#'     gapsRow = c(10, 14), cutreeCol = 2)
#'
#' # Show custom strings as row/col names
#' labelsRow = c("", "", "", "", "", "", "", "", "", "", "", "", "", "", "",
#' "", "", "Il10", "Il15", "Il1b")
#'
#' pheatmap(test, annotationCol = annotationCol, labelsRow = labelsRow)
#'
#' # Specifying clustering from distance matrix
#' drows = stats::dist(test, method = "minkowski")
#' dcols = stats::dist(t(test), method = "minkowski")
#' pheatmap(test,
#'     clusteringDistanceRows = drows,
#'     clusteringDistanceCols = dcols)
#'
#' # Modify ordering of the clusters using clustering callback option
#' callback = function(hc, mat) {
#'     sv = svd(t(mat))$v[, 1]
#'     dend = reorder(as.dendrogram(hc), wts = sv)
#'     as.hclust(dend)
#' }
#'
#' pheatmap(test, clusteringCallback = callback)
#' @importFrom grid grid.pretty
#' @importFrom RColorBrewer brewer.pal
semiPheatmap <- function(mat,
                         color = colorRampPalette(
                                 rev(brewer.pal(n = 7,
                                                name = "RdYlBu")))(100),
                         kmeansK = NA,
                         breaks = NA,
                         borderColor = "grey60",
                         cellWidth = NA,
                         cellHeight = NA,
                         scale = "none",
                         clusterRows = TRUE,
                         clusterCols = TRUE,
                         clusteringDistanceRows = "euclidean",
                         clusteringDistanceCols = "euclidean",
                         clusteringMethod = "complete",
                         clusteringCallback = .identity2,
                         cutreeRows = NA,
                         cutreeCols = NA,
                         treeHeightRow = ifelse(clusterRows, 50, 0),
                         treeHeightCol = ifelse(clusterCols, 50, 0),
                         legend = TRUE,
                         legendBreaks = NA,
                         legendLabels = NA,
                         annotationRow = NA,
                         annotationCol = NA,
                         annotation = NA,
                         annotationColors = NA,
                         annotationLegend = TRUE,
                         annotationNamesRow = TRUE,
                         annotationNamesCol = TRUE,
                         dropLevels = TRUE,
                         showRownames = TRUE,
                         showColnames = TRUE,
                         main = NA,
                         fontSize = 10,
                         fontSizeRow = fontSize,
                         fontSizeCol = fontSize,
                         displayNumbers = FALSE,
                         numberFormat = "%.2f",
                         numberColor = "grey30",
                         fontSizeNumber = 0.8 * fontSize,
                         gapsRow = NULL,
                         gapsCol = NULL,
                         labelsRow = NULL,
                         labelsCol = NULL,
                         fileName = NA,
                         width = NA,
                         height = NA,
                         silent = FALSE,
                         rowLabel,
                         colLabel,
                         rowGroupOrder = NULL,
                         colGroupOrder = NULL,
                         ...) {

  # Set labels
  if (is.null(labelsRow) & !is.null(rownames(mat))) {
    labelsRow <- rownames(mat)
  }
  if (is.null(labelsRow) & is.null(rownames(mat))) {
    labelsRow <- seq(nrow(mat))
    rownames(mat) <- seq(nrow(mat))
  }

  if (is.null(labelsCol) & !is.null(colnames(mat))) {
    labelsCol <- colnames(mat)
  }
  if (is.null(labelsCol) & is.null(colnames(mat))) {
    labelsCol <- seq(ncol(mat))
    colnames(mat) <- seq(ncol(mat))
  }


  if (.is.na2(breaks)) {
    breaks <- .generateBreaks(mat, length(color), center = TRUE)
  }


  # Kmeans
  if (!is.na(kmeansK)) {
    # Cluster data
    km <- stats::kmeans(mat, kmeansK, iter.max = 100)
    mat <- km$centers

    # Compose rownames
    t <- table(km$cluster)
    labelsRow <- sprintf("Cluster: %s Size: %d", names(t), t)
  } else {
    km <- NA
  }

  # Format numbers to be displayed in cells
  if (is.matrix(displayNumbers) | is.data.frame(displayNumbers)) {
    if (nrow(displayNumbers) != nrow(mat) |
      ncol(displayNumbers) != ncol(mat)) {
      stop("If displayNumbers provided as matrix,
                its dimensions have to match with mat")
    }

    displayNumbers <- as.matrix(displayNumbers)
    fmat <- matrix(as.character(displayNumbers),
      nrow = nrow(displayNumbers),
      ncol = ncol(displayNumbers)
    )
    fmatDraw <- TRUE
  } else {
    if (displayNumbers) {
      fmat <- matrix(sprintf(numberFormat, mat),
        nrow = nrow(mat),
        ncol = ncol(mat)
      )
      fmatDraw <- TRUE
    } else {
      fmat <- matrix(NA, nrow = nrow(mat), ncol = ncol(mat))
      fmatDraw <- FALSE
    }
  }

  # Do clustering for rows
  if (isTRUE(clusterRows)) {
    if (is.null(rowLabel)) {
      rowLabel <- rep(1, nrow(mat))
    } else {
      # o <- order(rowLabel)
      o <- .Order(labels = rowLabel, groupOrder = rowGroupOrder)
      mat <- mat[o, , drop = FALSE]
      fmat <- fmat[o, , drop = FALSE]
      rowLabel <- rowLabel[o]
      if (!is.null(annotationRow) && !is.null(ncol(annotationRow))) {
        annotationRow <- annotationRow[o, , drop = FALSE]
      }
    }

    treeRow <- .clusterMat(mat,
      rowLabel,
      distance = clusteringDistanceRows,
      method = clusteringMethod
    )
    treeRow <- clusteringCallback(treeRow, mat)
    mat <- mat[treeRow$order, , drop = FALSE]
    fmat <- fmat[treeRow$order, , drop = FALSE]
    labelsRow <- labelsRow[treeRow$order]
    if (!is.null(annotationRow) && !is.null(ncol(annotationRow))) {
      annotationRow <- annotationRow[treeRow$order, , drop = FALSE]
    }
    if (!is.na(cutreeRows)) {
      gapsRow <- .findGaps(treeRow, cutreeRows)
    } else {
      gapsRow <- NULL
    }
  } else {
    treeRow <- NA
    treeHeightRow <- 0
  }


  ## Do clustering for columns
  if (isTRUE(clusterCols)) {
    if (is.null(colLabel)) {
      colLabel <- rep(1, ncol(mat))
    } else {
      # o <- order(colLabel)
      o <- .Order(labels = colLabel, groupOrder = colGroupOrder)
      mat <- mat[, o, drop = FALSE]
      fmat <- fmat[, o, drop = FALSE]
      colLabel <- colLabel[o]
      if (!is.null(annotationCol) && !is.null(ncol(annotationCol))) {
        annotationCol <- annotationCol[o, , drop = FALSE]
      }
    }

    treeCol <- .clusterMat(t(mat),
      colLabel,
      distance = clusteringDistanceCols,
      method = clusteringMethod
    )
    treeCol <- clusteringCallback(treeCol, t(mat))

    mat <- mat[, treeCol$order, drop = FALSE]
    fmat <- fmat[, treeCol$order, drop = FALSE]
    labelsCol <- labelsCol[treeCol$order]

    if (!is.null(annotationCol) && !is.null(ncol(annotationCol))) {
      annotationCol <- annotationCol[treeCol$order, , drop = FALSE]
    }
    if (!is.na(cutreeCols)) {
      gapsCol <- .findGaps(treeCol, cutreeCols)
    } else {
      gapsCol <- NULL
    }
  } else {
    treeCol <- NA
    treeHeightCol <- 0
  }

  attr(fmat, "draw") <- fmatDraw

  # Colors and scales
  if (!.is.na2(legendBreaks) & !.is.na2(legendLabels)) {
    if (length(legendBreaks) != length(legendLabels)) {
      stop("Lengths of legendBreaks and legendLabels must be the same")
    }
  }


  if (.is.na2(breaks)) {
    breaks <- .generateBreaks(as.vector(mat), length(color))
  }
  if (legend & .is.na2(legendBreaks)) {
    legend <- grid::grid.pretty(range(as.vector(breaks)))
    names(legend) <- legend
  }
  else if (legend & !.is.na2(legendBreaks)) {
    legend <- legendBreaks[legendBreaks >= min(breaks) &
      legendBreaks <= max(breaks)]

    if (!.is.na2(legendLabels)) {
      legendLabels <- legendLabels[legendBreaks >= min(breaks) &
        legendBreaks <= max(breaks)]
      names(legend) <- legendLabels
    } else {
      names(legend) <- legend
    }
  } else {
    legend <- NA
  }
  mat <- .scaleColours(mat, col = color, breaks = breaks)

  annotation <- c(annotationRow, annotationCol)
  annotation <- annotation[unlist(lapply(
    annotation,
    function(x) !.is.na2(x)
  ))]
  if (length(annotation) != 0) {
    annotationColors <- .generateAnnotationColours(annotation,
      annotationColors,
      drop = dropLevels
    )
  } else {
    annotationColors <- NA
  }

  labelsRow <- rownames(mat)
  labelsCol <- colnames(mat)

  if (!showRownames) {
    labelsRow <- NULL
  }

  if (!showColnames) {
    labelsCol <- NULL
  }

  # Draw heatmap
  gt <- .heatmapMotor(mat,
    borderColor = borderColor,
    cellWidth = cellWidth,
    cellHeight = cellHeight,
    treeHeightCol = treeHeightCol,
    treeHeightRow = treeHeightRow,
    treeCol = treeCol,
    treeRow = treeRow,
    fileName = fileName,
    width = width,
    height = height,
    breaks = breaks,
    color = color,
    legend = legend,
    annotationRow = annotationRow,
    annotationCol = annotationCol,
    annotationColors = annotationColors,
    annotationLegend = annotationLegend,
    annotationNamesRow = annotationNamesRow,
    annotationNamesCol = annotationNamesCol,
    main = main,
    fontSize = fontSize,
    fontSizeRow = fontSizeRow,
    fontSizeCol = fontSizeCol,
    fmat = fmat,
    fontSizeNumber = fontSizeNumber,
    numberColor = numberColor,
    gapsRow = gapsRow,
    gapsCol = gapsCol,
    labelsRow = labelsRow,
    labelsCol = labelsCol,
    ...
  )

  return(gt)
}




# order function that order the row/column labels
# based on the order of the group priority
# return value is a vector of the ordered index
# labels is a vector of any non-zero length
# groupOrder, a column named dataframe/matrix
# with the "groupName" column storing the group
# name and the "groupIndex" storing the group priority
.Order <- function(labels, groupOrder = NULL) {
  if (is.null(groupOrder)) {
    return(order(labels))
  } else {
    # Throw error is length(unique(labels)) != nrow(groupOrder)
    olabels <- plyr::mapvalues(
      x = labels,
      from = groupOrder[, "groupName"],
      to = groupOrder[, "groupIndex"]
    )
    # Make sure the olabels is integer for order() function
    olabels <- as.integer(olabels)
    return(order(olabels))
  }
}