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# Copyright (C) Tal Galili
#
# This file is part of dendextend.
#
# dendextend is free software: you can redistribute it and/or modify it
# under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 2 of the License, or
# (at your option) any later version.
#
# dendextend is distributed in the hope that it will be useful, but
# WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# A copy of the GNU General Public License is available at
# http://www.r-project.org/Licenses/
#
# source: https://stackoverflow.com/questions/5468280/scale-a-series-between-two-points-in-r
# from the {scales} package
# library("scales"); rescale
zero_range <- function(x, tol = .Machine$double.eps * 100) {
if (length(x) == 1) {
return(TRUE)
}
if (length(x) != 2) {
stop("x must be length 1 or 2")
}
if (any(is.na(x))) {
return(NA)
}
if (x[1] == x[2]) {
return(TRUE)
}
if (all(is.infinite(x))) {
return(FALSE)
}
m <- min(abs(x))
if (m == 0) {
return(FALSE)
}
abs((x[1] - x[2]) / m) < tol
}
rescale <- function(x, to = c(0, 1), from = range(x, na.rm = TRUE)) {
if (zero_range(from) || zero_range(to)) {
return(rep(mean(to), length(x)))
}
(x - from[1]) / diff(from) * diff(to) + to[1]
}
# if(T) 2 else 1
# if(F) 2 else 1
# This function is require in order to know the height of the rotated labels in the dendrogram!
# Thanks to Prof. Brian Ripley
# # https://r.789695.n4.nabble.com/strwidth-and-strheight-for-rotated-text-td839105.html
rotated_str_dim <- function(s) {
cha <- s
xusr <- par("usr")
xh <- strwidth(cha, cex = par("cex"))
yh <- strheight(cha, cex = par("cex")) * 5 / 3
tmp <- xh
xh <- yh / (xusr[4] - xusr[3]) * par("pin")[2]
xh <- xh / par("pin")[1] * (xusr[2] - xusr[1])
yh <- tmp / (xusr[2] - xusr[1]) * par("pin")[1]
yh <- yh / par("pin")[2] * (xusr[4] - xusr[3])
c(xh = xh, yh = yh)
}
V_rotated_str_dim <- Vectorize(rotated_str_dim)
max_labels_height <- function(s) {
# s <- paste0(dend_labels, " ")
a <- V_rotated_str_dim(s)
max(a["yh", ])
}
#' @title Add colored dots beside a dendrogram
#' @export
#' @description
#' Add colored dots next to a dendrogram, usually
#' corresponding to either clusters or some outside
#' categorization.
#' @param colors Coloring of the dots beside the dendrogram. Either a vector (one color per object)
#' or a matrix (can also be an array or a data frame)
#' with each column giving one group with color per object.
#' Each column will be plotted as a colored point (when horiz = FALSE)
#' under the dendrogram.
#' As long as the sort_by_labels_order paramter is TRUE (default), the colors vector/matrix should
#' be provided in the order of the original data order (and it will be re-ordered automatically to
#' the order of the dendrogram)
#' @param dend a dendrogram object. If missing, the colors are plotted without and re-ordering
#' (this assumes that the colors are already ordered based on the dend's labels)
#' This is also important in order to get the correct height/location of the colored dots
#' (i.e.: adjusting the y_scale and y_shift)
#' @param rowLabels Labels for the colorings given in \code{colors}. The labels will be printed to the
#' left of the color rows in the plot. If the argument is given, it must be a vector of length
#' equal to the number of columns in \code{colors}. If not given, \code{names(colors)}
#' will be used if available. If not, sequential numbers
#' starting from 1 will be used.
#' @param cex.rowLabels Font size scale factor for the row labels. See \code{\link[graphics]{par}}.
#' @param add logical(TRUE), should the colored dots be added to an existing
#' dendrogram plot?
#' @param y_scale how much should the dots be stretched on the y axis?
#' If no dend is supplied - the default will be 1
#' @param y_shift where should the dots be plotted underneath the x axis?
#' By default it will try to locate the dots underneath the labels (it may miss,
#' in which case you would need to enter a number manually)
#' If no dend is supplied - the default will be 0
#' @param text_shift a dendrogram object
#' @param sort_by_labels_order logical(TRUE) - if TRUE (default), then the order of the
#' colored dots will be sorted based on the order needed to change the original
#' order of the observations to the current order of the labels in the dendrogram.
#' If FALSE the colored dots are plotted as-is, based on the order
#' of the colors vector.
#' @param horiz logical (FALSE by default). Set to TRUE when using plot(dend, horiz = TRUE)
#' @param dot_size numeric (1 by default). Passed to cex argument in points
#' @param ... ignored at this point.
#' @author Steve Horvath \email{SHorvath@@mednet.ucla.edu},
#' Tal Galili \email{Tal.Galili@@gmail.com},
#' Peter Langfelder \email{Peter.Langfelder@@gmail.com},
#' Chase Clark \email{chasec288@@gmail.com}
#' @details
#' The reason you might choose colored_dots over colored_bars is when you have
#' a lot of group types and/or a really large dendrogram.
#' Hint: Make a group for each categorical factor and color it one color when true,
#' and assign a fully transparent color when false.
#'
#' You will often need to adjust the y_scale, y_shift and the text_shift
#' parameters, in order to get the dots in the location you would want.
#'
#' (This can probably be done automatically, but will require more work.
#' since it has to do with the current mar settings,
#' the number of groups, and each computer's specific graphic device.
#' patches for smarter defaults will be appreciated)
#' @return
#' An invisible vector/matrix with the ordered colors.
#'
#' @source
#' This function is based on the \link[moduleColor]{plotHclustColors} from the
#' {moduleColor} R package. It was modified so that it would
#' work with dendrograms (and not just hclust objects), as well allow to
#' add the colored dots on top of an existing plot (and not only as a seperate plot).
#'
#' See: \url{https://cran.r-project.org/package=moduleColor}
#' For more details.
#'
#' @seealso
#' \link{branches_attr_by_clusters},
#' \link[WGCNA]{plotDendroAndColors}
#' @examples
#'
#' rows_picking <- c(1:5, 25:30)
#' dend <- (iris[rows_picking, -5] * 10) %>%
#' dist() %>%
#' hclust() %>%
#' as.dendrogram()
#' odd_numbers <- rows_picking %% 2
#' cols <- c("red", "white")[odd_numbers + 1]
#' plot(dend)
#' colored_dots(cols, dend)
#' # Example of adjusting postion of dots
#' plot(dend)
#' colored_dots(cols, dend,
#' y_shift = -1,
#' rowLabels = "Odd\n numbers"
#' )
#'
#'
#'
#' rows_picking <- c(1:5, 25:30)
#' dend <- (iris[rows_picking, -5] * 10) %>%
#' dist() %>%
#' hclust() %>%
#' as.dendrogram()
#' odd_numbers <- rows_picking %% 2
#' # For leaves that shouldn't have dots, make them the same color as the background,
#' # or set the alpha value to fully transparant
#' cols <- c("black", "white")[odd_numbers + 1]
#' # scale is off
#' plot(dend)
#' colored_dots(cols, dend)
#' # move and scale a bit
#' plot(dend)
#' colored_dots(cols, dend,
#' y_shift = -1,
#' rowLabels = "Odd\n numbers"
#' )
#' # Now let's cut the tree and add that info to the plot:
#' k2 <- cutree(dend, k = 2)
#' cols2 <- c("#1b9e77", "#d95f02")[k2]
#'
#' par(mar = c(5, 6, 1, 1))
#' plot(dend)
#' colored_dots(cbind(cols2, cols), dend,
#' rowLabels = c("2 clusters", "Even numbers")
#' )
#'
#' # The same, but with an horizontal plot!
#' par(mar = c(6, 2, 2, 4))
#' plot(dend, horiz = TRUE)
#' colored_dots(cbind(cols2, cols), dend,
#' rowLabels = c("2 clusters", "Even numbers"),
#' horiz = TRUE
#' )
#'
#' # ==============================
#' # ==============================
#'
#' ## mtcars example
#'
#' # Create the dend:
#' dend <- as.dendrogram(hclust(dist(mtcars)))
#'
#' # Get all company names
#' comp_names <- unlist(lapply(rownames(mtcars), function(x) strsplit(x, " ")[[1]][[1]]))
#' # Get the top three occurring companies
#' top_three <- sort(table(comp_names), decreasing = TRUE)[1:3]
#' # Match the top three companies to where they are found in the dendrogram labels
#' top_three <- sapply(names(top_three), function(x) grepl(x, labels(dend)))
#' top_three <- as.data.frame(top_three)
#' # "top_three" is now a data frame of the top three companies as columns.
#' # Each column represents a vector (rows) which is the length of labels(dend).
#' # The vector has values TRUE and FALSE, for whether the company name matched
#' # labels(dend)[i]
#'
#' # Colorblind friendly vector of HEX colors
#' colorblind_friendly <- c("#1b9e77", "#d95f02", "#7570b3")
#'
#' # If we run the for-loop on "top_three" we will turn the vectors into a character-type too early,
#' # so make a copy to "colored_dataframe" which we will work on
#' colored_dataframe <- top_three
#'
#' for (i in 1:3) {
#' # This replaces TRUE values with a color from our vector of colors
#' colored_dataframe[top_three[, i], i] <- colorblind_friendly[[i]]
#' # This replaces FALSE values with black HEX, but fully transparent (invisible on plot)
#' colored_dataframe[!top_three[, i], i] <- "#00000000"
#' }
#'
#' # Color branches and labels by "cutting" the dendrogram at an arbitrary height
#' dend <- color_branches(dend, h = 170)
#' dend <- color_labels(dend, h = 170)
#'
#' ### plots
#' par(mar = c(12, 4, 1, 1))
#' plot(dend)
#' colored_dots(colored_dataframe, dend,
#' rowLabels = colnames(colored_dataframe), horiz = FALSE, sort_by_labels_order = FALSE
#' )
#' # Show a dotted line where tree was "cut"
#' abline(h = 170, lty = 3)
#'
#' # horiz version:
#' par(mar = c(4, 1, 1, 12))
#' plot(dend, horiz = TRUE)
#' colored_dots(colored_dataframe, dend,
#' rowLabels = colnames(colored_dataframe), horiz = TRUE, sort_by_labels_order = FALSE
#' )
#' # Show a dotted line where the tree was "cut"
#' abline(v = 170, lty = 3)
colored_dots <- function(colors, dend, rowLabels = NULL, cex.rowLabels = 0.9,
add = TRUE,
y_scale, y_shift,
text_shift = 1,
sort_by_labels_order = TRUE,
horiz = FALSE,
# below_labels = TRUE,
dot_size = 1,
...) {
# should either be a vector or a matrix (it could also work with data.frames)
# if(!(is.vector(colors) | is.matrix(colors))) stop("colors must be either a vector or a matrix")
# number of color boxes per row (i.e.: number of dend leaves)
n_colors <- if (is.null(dim(colors))) length(colors) else nrow(colors)
# number of rows (groups) of colors
n_groups <- if (is.null(dim(colors))) 1 else ncol(colors)
if (!missing(dend)) {
# make sure we are working with a dend:
if (is.hclust(dend)) dend <- as.dendrogram(dend)
if (!is.dendrogram(dend)) stop("'dend' should be a dendrogram.")
# get labels' order:
# dend_size <- nleaves(dend)
dend_labels <- labels(dend)
dend_order <- order.dendrogram(dend)
} else { # if we ARE missing dend
dend_labels <- rep("W", n_colors) # assume all labels are W
dend_order <- seq_len(n_colors)
}
if (!sort_by_labels_order) dend_order <- seq_len(n_colors)
# # Get y_shift to be underneath the labels
# if(!horiz) {
# if(missing(y_shift)) y_shift <- -max(strwidth(dend_labels))+par()$usr[3L]-2*strheight("x") # a bit of a hack, oh well...
# if(missing(y_scale)) y_scale <- median(strheight(dend_labels)) * nrow_colors * .8
# } else {
# if(missing(y_shift)) y_shift <- max(abs(strwidth(dend_labels)))+par()$usr[3L]-3*strwidth("x") # a bit of a hack, oh well...
# if(missing(y_scale)) y_scale <- median(abs(strwidth(dend_labels))) * nrow_colors * .8
# }
# Get y_shift to be underneath the labels
if (!horiz) {
# We shift y with the max height of the rotated labels + plot region + one row of values (the height of X)
if (missing(y_shift)) y_shift <- -max_labels_height(dend_labels) + par("usr")[3L] - strheight("X")
if (missing(y_scale)) y_scale <- strheight("X") * n_groups
} else {
if (missing(y_shift)) y_shift <- -(min(strwidth(dend_labels)) + par("usr")[2L] + strwidth("X"))
if (missing(y_scale)) y_scale <- strwidth("X") * n_groups
}
# moving the y location and scale of the dots
# this allows us to have it underneath the dend
# in a way that would look nice.
# if(missing(y_scale)) y_scale <- 1
# this makes sure that the original shift we had is always compared to the top of the dots (instead of the bottom)
# the if-else lowers the y further, to make sure it is below the labels.
y_shift <- y_shift - y_scale
# - if(below_labels) max(strheight(labels(dend))) else 0
colors <- as.matrix(colors)
dimC <- dim(colors)
if (is.null(rowLabels) & (length(dimnames(colors)[[2]]) == dimC[2])) rowLabels <- names(as.data.frame(colors))
op <- options()
pr <- par(no.readonly = TRUE)
options(stringsAsFactors = FALSE)
# par(mar = c(0, 4.1, 0, 2.1))
par(xpd = TRUE)
if (length(dend_order) != dimC[1]) {
stop("ERROR: length of colors vector not compatible with number of objects in the hierarchical tree.")
}
C <- colors[dend_order, ] # new colors vector
C <- as.matrix(C)
step <- 1 / (n_colors - 1)
ystep <- 1 / n_groups
if (!add) {
barplot(height = 1, col = "white", border = FALSE, space = 0, axes = FALSE, ...)
}
charWidth <- strwidth("W") / 2
charHeight <- strheight("W") / 2
for (j in 1:n_groups)
{
ind <- (1:n_colors)
xl <- (ind - 1.5) * step # locations of the x left
xr <- (ind - 0.5) * step
yb <- rep(ystep * (j - 1), n_colors)
yt <- rep(ystep * j, n_colors)
if (add) {
xl <- rescale(xl, to = c(1 - .5, n_colors - .5))
xr <- rescale(xl, to = c(1 + .5, n_colors + .5))
yb <- yb * y_scale + y_shift
yt <- yt * y_scale + y_shift
}
if (horiz) {
# Instead of rectangles, put in points at 1/2 x and y coordinates
# rect(-yb, xl, -yt, xr, col = as.character(C[, j]),
# border = as.character(C[, j]))
points((-yb + (-yt)) / 2, (xl + xr) / 2, pch = 19, col = as.character(C[, j]), cex = dot_size)
# plot the rowLabels text:
par(srt = 90)
if (is.null(rowLabels)) {
s <- as.character(j)
text(s, pos = 1, offset = 0.5, y = charHeight * text_shift - rotated_str_dim(s)[2] / 2, x = -(ystep * (j) * y_scale + y_shift), cex = cex.rowLabels)
# text(as.character(j), pos=2, x= -charWidth -0.5*step, y=ystep*(j-0.5), cex=cex.rowLabels, xpd = TRUE);
} else {
s <- rowLabels[j]
text(s, pos = 1, offset = 0.5, y = charHeight * text_shift - rotated_str_dim(s)[2] / 2, x = -(ystep * (j) * y_scale + y_shift), cex = cex.rowLabels)
# text(rowLabels[j], pos=2, x= -charWidth -0.5*step, y=ystep*(j-0.5), cex=cex.rowLabels, xpd = TRUE);
}
} else { # default
# Instead of rectangles, put in points at 1/2 x and y coordinates
# rect(xl, yb, xr, yt, col = as.character(C[, j]),
# border = as.character(C[, j]))
points((xl + xr) / 2, (yb + yt) / 2, pch = 19, col = as.character(C[, j]), cex = dot_size)
if (is.null(rowLabels)) {
text(as.character(j), pos = 2, x = charWidth * text_shift, y = ystep * (j - 0.5) * y_scale + y_shift, cex = cex.rowLabels)
# text(as.character(j), pos=2, x= -charWidth -0.5*step, y=ystep*(j-0.5), cex=cex.rowLabels, xpd = TRUE);
} else {
text(rowLabels[j], pos = 2, x = charWidth * text_shift, y = ystep * (j - 0.5) * y_scale + y_shift, cex = cex.rowLabels)
# text(rowLabels[j], pos=2, x= -charWidth -0.5*step, y=ystep*(j-0.5), cex=cex.rowLabels, xpd = TRUE);
}
}
}
# we start j from 0 so that it will add a line below the dots (and not just above them)
# Adds lines to seperate the clusters
for (j in 0:n_groups) {
the_x <- rescale(c(0, 1), to = c(1 - .5, n_colors + .5))
if (horiz) {
lines(y = the_x, x = -(c(ystep * j, ystep * j) * y_scale + y_shift))
} else {
lines(x = the_x, y = c(ystep * j, ystep * j) * y_scale + y_shift)
}
}
options(op) # reset (all) initial options
par(pr) # suppressWarnings(par(pr))
return(invisible(C))
}
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