Multiple platform build/check report for BioC 3.18 - CHECK results for ComplexHeatmap on merida1

Hostname	OS	Arch (*)	R version	Installed pkgs
nebbiolo2	Linux (Ubuntu 22.04.3 LTS)	x86_64	4.3.3 (2024-02-29) -- "Angel Food Cake"	4676
palomino4	Windows Server 2022 Datacenter	x64	4.3.3 (2024-02-29 ucrt) -- "Angel Food Cake"	4414
merida1	macOS 12.7.1 Monterey	x86_64	4.3.3 (2024-02-29) -- "Angel Food Cake"	4437
Click on any hostname to see more info about the system (e.g. compilers) () as reported by 'uname -p', except on Windows and Mac OS X*


R version 4.3.3 (2024-02-29) -- "Angel Food Cake"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin20 (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(circlize)
========================================
circlize version 0.4.16
CRAN page: https://cran.r-project.org/package=circlize
Github page: https://github.com/jokergoo/circlize
Documentation: https://jokergoo.github.io/circlize_book/book/

If you use it in published research, please cite:
Gu, Z. circlize implements and enhances circular visualization
  in R. Bioinformatics 2014.

This message can be suppressed by:
  suppressPackageStartupMessages(library(circlize))
========================================

> library(ComplexHeatmap)
Loading required package: grid
========================================
ComplexHeatmap version 2.18.0
Bioconductor page: http://bioconductor.org/packages/ComplexHeatmap/
Github page: https://github.com/jokergoo/ComplexHeatmap
Documentation: http://jokergoo.github.io/ComplexHeatmap-reference

If you use it in published research, please cite either one:
- Gu, Z. Complex Heatmap Visualization. iMeta 2022.
- Gu, Z. Complex heatmaps reveal patterns and correlations in multidimensional 
    genomic data. Bioinformatics 2016.


The new InteractiveComplexHeatmap package can directly export static 
complex heatmaps into an interactive Shiny app with zero effort. Have a try!

This message can be suppressed by:
  suppressPackageStartupMessages(library(ComplexHeatmap))
========================================

> library(GetoptLong)
> 
> if(!exists("normalize_graphic_param_to_mat")) {
+ 	normalize_graphic_param_to_mat = ComplexHeatmap:::normalize_graphic_param_to_mat
+ }
> 
> if(!exists("height")) {
+ 	height = ComplexHeatmap:::height
+ }
> 
> if(!exists("width")) {
+ 	width = ComplexHeatmap:::width
+ }
> 
> normalize_graphic_param_to_mat(1, nc = 2, nr = 4, "foo")
     [,1] [,2]
[1,]    1    1
[2,]    1    1
[3,]    1    1
[4,]    1    1
> normalize_graphic_param_to_mat(1:2, nc = 2, nr = 4, "foo")
     [,1] [,2]
[1,]    1    2
[2,]    1    2
[3,]    1    2
[4,]    1    2
> normalize_graphic_param_to_mat(1:4, nc = 2, nr = 4, "foo")
     [,1] [,2]
[1,]    1    1
[2,]    2    2
[3,]    3    3
[4,]    4    4
> 
> ### AnnotationFunction constructor #####
> fun = function(index) {
+ 	x = runif(10)
+ 	pushViewport(viewport(xscale = c(0.5, 10.5), yscale = c(0, 1)))
+ 	grid.points(index, x[index])
+ 	popViewport()
+ }
> anno = AnnotationFunction(fun = fun)
> 
> x = runif(10)
> fun = function(index) {
+ 	pushViewport(viewport(xscale = c(0.5, 10.5), yscale = c(0, 1)))
+ 	grid.points(index, x[index])
+ 	popViewport()
+ }
> anno = AnnotationFunction(fun = fun, var_import = "x")
> anno = AnnotationFunction(fun = fun, var_import = list(x))
> 
> 
> x = runif(10)
> cell_fun = function(i) {
+ 	pushViewport(viewport(yscale = c(0, 1)))
+ 	grid.points(unit(0.5, "npc"), x[i])
+ 	popViewport()
+ }
> anno = AnnotationFunction(cell_fun = cell_fun, var_import = "x")
> ha = HeatmapAnnotation(foo = anno)
> draw(ha, 1:10, test = T)
> 
> cell_fun = function(i) {
+ 	pushViewport(viewport(xscale = c(0, 1)))
+ 	grid.points(x[i], unit(0.5, "npc"))
+ 	popViewport()
+ }
> anno = AnnotationFunction(cell_fun = cell_fun, var_import = "x", which = "row")
> ha = rowAnnotation(foo = anno)
> draw(ha, 1:10, test = T)
> 
> # devAskNewPage(ask = dev.interactive())
> 
> ########### testing anno_simple ############
> anno = anno_simple(1:10)
> draw(anno, test = "as a simple vector")
> draw(anno[1:5], test = "subset of column annotation")
> anno = anno_simple(1:10, which = "row")
> draw(anno, test = "as row annotation")
> draw(anno[1:5], test = "subste of row annotation")
> 
> anno = anno_simple(1:10, col = structure(rand_color(10), names = 1:10))
> draw(anno, test = "self-define colors")
> 
> anno = anno_simple(1:10, border = TRUE)
> draw(anno, test = "border")
> anno = anno_simple(1:10, gp = gpar(col = "red"))
> draw(anno, test = "gp for the grids")
> 
> anno = anno_simple(c(1:9, NA))
> draw(anno, test = "vector has NA values")
> 
> anno = anno_simple(cbind(1:10, 10:1))
> draw(anno, test = "a matrix")
> draw(anno[1:5], test = "subste of a matrix")
> 
> anno = anno_simple(1:10, pch = 1, pt_gp = gpar(col = "red"), pt_size = unit(seq(1, 10), "mm"))
> draw(anno, test = "with symbols + pt_gp + pt_size")
> anno = anno_simple(1:10, pch = 1:10)
> draw(anno, test = "pch is a vector")
> anno = anno_simple(1:10, pch = c(1:4, NA, 6:8, NA, 10, 11))
> draw(anno, test = "pch has NA values")
> 
> anno = anno_simple(cbind(1:10, 10:1), pch = 1, pt_gp = gpar(col = "blue"))
> draw(anno, test = "matrix with symbols")
> anno = anno_simple(cbind(1:10, 10:1), pch = 1:2)
> draw(anno, test = "matrix, length of pch is number of annotations")
> anno = anno_simple(cbind(1:10, 10:1), pch = 1:10)
> draw(anno, test = "matrix, length of pch is length of samples")
> anno = anno_simple(cbind(1:10, 10:1), pch = matrix(1:20, nc = 2))
> draw(anno, test = "matrix, pch is a matrix")
> pch = matrix(1:20, nc = 2)
> pch[sample(length(pch), 10)] = NA
> anno = anno_simple(cbind(1:10, 10:1), pch = pch)
> draw(anno, test = "matrix, pch is a matrix with NA values")
> 
> 
> ####### test anno_empty ######
> anno = anno_empty()
> draw(anno, test = "anno_empty")
> anno = anno_empty(border = FALSE)
> draw(anno, test = "anno_empty without border")
> 
> if(0) {
+ ###### test anno_image #####
+ image1 = sample(dir("~/Downloads/IcoMoon-Free-master/PNG/64px", full.names = TRUE), 10)
+ anno = anno_image(image1)
+ draw(anno, test = "png")
+ draw(anno[1:5], test = "subset of png")
+ anno = anno_image(image1, which = "row")
+ draw(anno, test = "png on rows")
+ image2 = sample(dir("~/Downloads/IcoMoon-Free-master/SVG/", full.names = TRUE), 10)
+ anno = anno_image(image2)
+ draw(anno, test = "svg")
+ image3 = sample(dir("~/Downloads/IcoMoon-Free-master/EPS/", full.names = TRUE), 10)
+ anno = anno_image(image3)
+ draw(anno, test = "eps")
+ image4 = sample(dir("~/Downloads/IcoMoon-Free-master/PDF/", full.names = TRUE), 10)
+ anno = anno_image(image4)
+ draw(anno, test = "pdf")
+ 
+ anno = anno_image(c(image1[1:3], image2[1:3], image3[1:3], image4[1:3]))
+ draw(anno, test = "png+svg+eps+pdf")
+ 
+ anno = anno_image(image1, gp = gpar(fill = 1:10, col = "black"))
+ draw(anno, test = "png + gp")
+ draw(anno[1:5], test = "png + gp")
+ 
+ anno = anno_image(image1, space = unit(3, "mm"))
+ draw(anno, test = "space")
+ 
+ image1[1] = ""
+ anno = anno_image(image1)
+ draw(anno, test = "png")
+ }
> 
> ######## test anno_points #####
> anno = anno_points(runif(10))
> draw(anno, test = "anno_points")
> anno = anno_points(matrix(runif(20), nc = 2), pch = 1:2)
> draw(anno, test = "matrix")
> anno = anno_points(c(1:5, 1:5))
> draw(anno, test = "anno_points")
> anno = anno_points(cbind(c(1:5, 1:5), c(5:1, 5:1)), gp = gpar(col = 2:3))
> draw(anno, test = "matrix")
> 
> anno = anno_points(1:10, gp = gpar(col = rep(2:3, each = 5)), pch = rep(2:3, each = 5))
> draw(anno, test = "anno_points")
> draw(anno, index = c(1, 3, 5, 7, 9, 2, 4, 6, 8, 10), test = "anno_points")
> 
> anno = anno_points(c(1:5, NA, 7:10))
> draw(anno, test = "anno_points")
> 
> 
> anno = anno_points(runif(10), axis_param = list(direction = "reverse"), ylim = c(0, 1))
> draw(anno, test = "anno_points")
> 
> anno = anno_points(runif(10), axis_param = list(direction = "reverse"), ylim = c(0, 1), which = "row")
> draw(anno, test = "anno_points")
> 
> # pch as image
> if(0) {
+ image1 = sample(dir("/desktop-home/guz/Downloads/IcoMoon-Free-master/PNG/64px", full.names = TRUE), 10)
+ x = runif(10)
+ anno1 = anno_points(x, pch = image1, pch_as_image = TRUE, size = unit(5, "mm"), height = unit(4, "cm"))
+ anno2 = anno_points(x, height = unit(4, "cm"))
+ draw(anno1, test = "anno_points")
+ draw(anno2, test = "anno_points")
+ }
> 
> ##### test anno_lines ###
> anno = anno_lines(runif(10))
> draw(anno, test = "anno_lines")
> anno = anno_lines(cbind(c(1:5, 1:5), c(5:1, 5:1)), gp = gpar(col = 2:3))
> draw(anno, test = "matrix")
> anno = anno_lines(cbind(c(1:5, 1:5), c(5:1, 5:1)), gp = gpar(col = 2:3),
+ 	add_points = TRUE, pt_gp = gpar(col = 5:6), pch = c(1, 16))
> draw(anno, test = "matrix")
> anno = anno_lines(sort(rnorm(10)), height = unit(2, "cm"), smooth = TRUE, add_points = TRUE)
> draw(anno, test = "anno_lines, smooth")
> anno = anno_lines(cbind(sort(rnorm(10)), sort(rnorm(10), decreasing = TRUE)), 
+ 	height = unit(2, "cm"), smooth = TRUE, add_points = TRUE, gp = gpar(col = 2:3))
> draw(anno, test = "anno_lines, smooth, matrix")
> 
> anno = anno_lines(sort(rnorm(10)), width = unit(2, "cm"), smooth = TRUE, add_points = TRUE, which = "row")
> draw(anno, test = "anno_lines, smooth, by row")
> anno = anno_lines(cbind(sort(rnorm(10)), sort(rnorm(10), decreasing = TRUE)), 
+ 	width = unit(2, "cm"), smooth = TRUE, add_points = TRUE, gp = gpar(col = 2:3), which = "row")
> draw(anno, test = "anno_lines, smooth, matrix, by row")
> 
> anno = anno_lines(c(1:5, NA, 7:10))
> draw(anno, test = "anno_lines")
> 
> anno = anno_lines(runif(10), axis_param = list(direction = "reverse"))
> draw(anno, test = "anno_lines")
> 
> ###### test anno_text #######
> anno = anno_text(month.name)
> draw(anno, test = "month names")
> anno = anno_text(month.name, gp = gpar(fontsize = 16))
> draw(anno, test = "month names with fontsize")
> anno = anno_text(month.name, gp = gpar(fontsize = 1:12+4))
> draw(anno, test = "month names with changing fontsize")
> anno = anno_text(month.name, which = "row")
> draw(anno, test = "month names on rows")
> anno = anno_text(month.name, location = 0, rot = 45, just = "left", gp = gpar(col = 1:12))
> draw(anno, test = "with rotations")
> anno = anno_text(month.name, location = 1, rot = 45, just = "right", gp = gpar(fontsize = 1:12+4))
> draw(anno, test = "with rotations")
> 
> 
> for(rot in seq(0, 360, by = 45)) {
+ 	anno = anno_text(month.name, which = "row", location = 0, rot = rot, 
+ 		just = "left")
+ 	draw(anno, test = paste0("rot =", rot))
+ }
> 
> 
> ##### test anno_barplot #####
> anno = anno_barplot(1:10)
> draw(anno, test = "a vector")
> draw(anno[1:5], test = "a vector, subset")
> anno = anno_barplot(1:10, which = "row")
> draw(anno, test = "a vector")
> anno = anno_barplot(1:10, bar_width = 1)
> draw(anno, test = "bar_width")
> anno = anno_barplot(1:10, gp = gpar(fill = 1:10))
> draw(anno, test = "fill colors")
> 
> anno = anno_barplot(matrix(nc = 2, c(1:10, 10:1)))
> draw(anno, test = "a matrix")
> draw(anno[1:5], test = "a matrix, subset")
> anno = anno_barplot(matrix(nc = 2, c(1:10, 10:1)), which = "row")
> draw(anno, test = "a matrix, on rows")
> anno = anno_barplot(matrix(nc = 2, c(1:10, 10:1)), gp = gpar(fill = 2:3, col = 2:3))
> draw(anno, test = "a matrix with fill")
> 
> m = matrix(runif(4*10), nc = 4)
> m = t(apply(m, 1, function(x) x/sum(x)))
> anno = anno_barplot(m)
> draw(anno, test = "proportion matrix")
> anno = anno_barplot(m, gp = gpar(fill = 2:5), bar_width = 1, height = unit(6, "cm"))
> draw(anno, test = "proportion matrix")
> 
> anno = anno_barplot(c(1:5, NA, 7:10))
> draw(anno, test = "a vector")
> 
> anno = anno_barplot(1:10, which = "row", axis_param = list(direction = "reverse"))
> draw(anno, test = "a vector")
> 
> anno = anno_barplot(1:10, baseline = 5, which = "row", axis_param = list(direction = "reverse"))
> draw(anno, test = "a vector")
> 
> anno = anno_barplot(matrix(nc = 2, c(1:10, 10:1)), which = "row", axis_param = list(direction = "reverse"))
> draw(anno, test = "a vector")
> 
> 
> anno = anno_barplot(matrix(nc = 2, c(1:10, 10:1)), beside = TRUE)
> draw(anno, test = "a matrix")
> draw(anno[1:5], test = "a matrix, subset")
> anno = anno_barplot(matrix(nc = 2, c(1:10, 10:1)), beside = TRUE, which = "row")
> draw(anno, test = "a matrix, on rows")
> anno = anno_barplot(matrix(nc = 2, c(1:10, 10:1)), beside = TRUE, gp = gpar(fill = 2:3, col = 2:3))
> draw(anno, test = "a matrix with fill")
> 
> 
> ##### test anno_boxplot #####
> set.seed(123)
> m = matrix(rnorm(100), 10)
> anno = anno_boxplot(m, height = unit(4, "cm"))
> draw(anno, test = "anno_boxplot")
> draw(anno[1:5], test = "subset")
> anno = anno_boxplot(m, height = unit(4, "cm"), gp = gpar(fill = 1:10))
> draw(anno, test = "anno_boxplot with gp")
> anno = anno_boxplot(m, height = unit(4, "cm"), box_width = 0.9)
> draw(anno, test = "anno_boxplot with box_width")
> 
> m = matrix(rnorm(100), 10)
> m[1, ] = NA
> anno = anno_boxplot(m, height = unit(4, "cm"))
> draw(anno, test = "anno_boxplot")
> 
> 
> ####### test anno_joyplot ####
> m = matrix(rnorm(1000), nc = 10)
> lt = apply(m, 2, function(x) data.frame(density(x)[c("x", "y")]))
> anno = anno_joyplot(lt, width = unit(4, "cm"), which = "row")
> draw(anno, test = "joyplot")
> anno = anno_joyplot(lt, width = unit(4, "cm"), which = "row", gp = gpar(fill = 1:10))
> draw(anno, test = "joyplot + col")
> anno = anno_joyplot(lt, width = unit(4, "cm"), which = "row", scale = 1)
> draw(anno, test = "joyplot + scale")
> 
> m = matrix(rnorm(5000), nc = 50)
> lt = apply(m, 2, function(x) data.frame(density(x)[c("x", "y")]))
> anno = anno_joyplot(lt, width = unit(4, "cm"), which = "row", gp = gpar(fill = NA), scale = 4)
> draw(anno, test = "joyplot")
> 
> ######## test anno_horizon ######
> lt = lapply(1:20, function(x) cumprod(1 + runif(1000, -x/100, x/100)) - 1)
> anno = anno_horizon(lt, which = "row")
> draw(anno, test = "horizon chart")
> anno = anno_horizon(lt, which = "row", gp = gpar(pos_fill = "orange", neg_fill = "darkgreen"))
> draw(anno, test = "horizon chart, col")
> anno = anno_horizon(lt, which = "row", negative_from_top = TRUE)
> draw(anno, test = "horizon chart + negative_from_top")
> anno = anno_horizon(lt, which = "row", gap = unit(1, "mm"))
> draw(anno, test = "horizon chart + gap")
> anno = anno_horizon(lt, which = "row", gp = gpar(pos_fill = rep(c("orange", "red"), each = 10),
+ 	neg_fill = rep(c("darkgreen", "blue"), each = 10)))
> draw(anno, test = "horizon chart, col")
> 
> ####### test anno_histogram ####
> m = matrix(rnorm(1000), nc = 10)
> anno = anno_histogram(t(m), which = "row")
> draw(anno, test = "row histogram")
> draw(anno[1:5], test = "subset row histogram")
> anno = anno_histogram(t(m), which = "row", gp = gpar(fill = 1:10))
> draw(anno, test = "row histogram with color")
> anno = anno_histogram(t(m), which = "row", n_breaks = 20)
> draw(anno, test = "row histogram with color")
> m[1, ] = NA
> anno = anno_histogram(t(m), which = "row")
> draw(anno, test = "row histogram")
> 
> 
> ####### test anno_density ######
> anno = anno_density(t(m), which = "row")
> draw(anno, test = "normal density")
> draw(anno[1:5], test = "normal density, subset")
> anno = anno_density(t(m), which = "row", type = "violin")
> draw(anno, test = "violin")
> anno = anno_density(t(m), which = "row", type = "heatmap")
> draw(anno, test = "heatmap")
> anno = anno_density(t(m), which = "row", type = "heatmap", heatmap_colors = c("white", "orange"))
> draw(anno, test = "heatmap, colors")
> 
> anno = anno_density(t(m), which = "row", xlim = c(-2, 2))
> draw(anno, test = "normal density")
> anno = anno_density(t(m), which = "row", type = "violin", xlim = c(-2, 2))
> draw(anno, test = "violin")
> anno = anno_density(t(m), which = "row", type = "heatmap", xlim = c(-2, 2))
> draw(anno, test = "heatmap")
> 
> ###### anno_mark ###
> if(0) {
+ library(gridtext)
+ grid.text = function(text, x = 0.5, y = 0.5, gp = gpar(), rot = 0, default.units = "npc", just = "center") {
+ 	if(length(just) == 1) {
+ 		if(just == "center") {
+ 			just = c("center", "center")
+ 		} else if(just == "bottom") {
+ 			just = c("center", "bottom")
+ 		} else if (just == "top") {
+ 			just = c("center", "top")
+ 		} else if(just == "left") {
+ 			just = c("left", "center")
+ 		} else if(just == "right") {
+ 			just = c("right", "center")
+ 		}
+ 	}
+ 	just2 = c(0.5, 0.5)
+ 	if(is.character(just)) {
+ 		just2[1] = switch(just[1], "center" = 0.5, "left" = 0, "right" = 1)
+ 		just2[2] = switch(just[2], "center" = 0.5, "bottom" = 0, "top" = 1)
+ 	}
+ 	gb = richtext_grob(text, x = x, y = y, gp = gpar(fontsize = 10), box_gp = gpar(col = "black"),
+ 		default.units = default.units, hjust = just2[1], vjust = just2[2], rot = rot)
+ 	grid.draw(gb)
+ }
+ }
> anno = anno_mark(at = c(1:4, 20, 60, 97:100), labels = month.name[1:10], which = "row")
> draw(anno, index = 1:100, test = "anno_mark")
> 
> anno = anno_mark(at = c(1:4, 20, 60, 97:100), labels = month.name[1:10], labels_rot = 30, which = "column")
> draw(anno, index = 1:100, test = "anno_mark")
> 
> m = matrix(1:1000, byrow = TRUE, nr = 100)
> anno = anno_mark(at = c(1:4, 20, 60, 97:100), labels = month.name[1:10], which = "row", labels_rot = 30)
> Heatmap(m, cluster_rows = F, cluster_columns = F) + rowAnnotation(mark = anno)
> Heatmap(m) + rowAnnotation(mark = anno)
> 
> ht_list = Heatmap(m, cluster_rows = F, cluster_columns = F) + rowAnnotation(mark = anno)
> draw(ht_list, row_split = c(rep("a", 95), rep("b", 5)))
> 
> 
> grid.newpage()
> pushViewport(viewport(x = 0.45, w = 0.7, h = 0.95))
> h = unit(0, "mm")
> for(rot in seq(0, 360, by = 30)[-13]) {
+ 	anno = anno_mark(at = c(1:4, 20, 60, 97:100), labels = strrep(letters[1:10], 4), labels_rot = rot, which = "column", side = "bottom")
+ 	h = h + height(anno)
+ 	pushViewport(viewport(y = h, height = height(anno), just = "top"))
+ 	grid.rect()
+ 	draw(anno, index = 1:100)
+ 	grid::grid.text(qq("labels_rot = @{rot}"), unit(1, "npc") + unit(2, "mm"), just = "left")
+ 	popViewport()
+ }
> 
> 
> grid.newpage()
> pushViewport(viewport(w = 0.9, h = 0.9))
> w = unit(0, "mm")
> for(rot in seq(0, 360, by = 30)) {
+ 	anno = anno_mark(at = c(1:4, 20, 60, 97:100), labels = strrep(letters[1:10], 4), labels_rot = rot, which = "row", side = "left")
+ 	w = w + width(anno)
+ 	pushViewport(viewport(x = w, width = width(anno), just = "right"))
+ 	grid.rect()
+ 	draw(anno, index = 1:100)
+ 	popViewport()
+ }
> 
> 
> 
> ### graphic parameters after reordering
> index = c(1, 3, 5, 7, 9, 2, 4, 6, 8, 10)
> anno = anno_simple(1:10, pch = 1:10, pt_gp = gpar(col = rep(c(1, 2), each = 5)),
+ 	pt_size = unit(1:10, "mm"))
> draw(anno, index, test = "a numeric vector")
> anno = anno_simple(1:10, pch = 1:10, pt_gp = gpar(col = rep(c(1, 2), each = 5)),
+ 	pt_size = unit(1:10, "mm"), which = "row")
> draw(anno, index, test = "a numeric vector")
> 
> 
> anno = anno_points(1:10, pch = 1:10, gp = gpar(col = rep(c(1, 2), each = 5)),
+ 	size = unit(1:10, "mm"))
> draw(anno, index, test = "a numeric vector")
> anno = anno_points(1:10, pch = 1:10, gp = gpar(col = rep(c(1, 2), each = 5)),
+ 	size = unit(1:10, "mm"), which = "row")
> draw(anno, index, test = "a numeric vector")
> 
> 
> anno = anno_lines(sort(runif(10)), pch = 1:10, pt_gp = gpar(col = rep(c(1, 2), each = 5)),
+ 	size = unit(1:10, "mm"), add_points = TRUE)
> draw(anno, index, test = "a numeric vector")
> anno = anno_lines(sort(runif(10)), pch = 1:10, pt_gp = gpar(col = rep(c(1, 2), each = 5)),
+ 	size = unit(1:10, "mm"), add_points = TRUE, which = "row")
> draw(anno, index, test = "a numeric vector")
> 
> 
> anno = anno_barplot(1:10, gp = gpar(fill = rep(c(1, 2), each = 5)))
> draw(anno, index, test = "a numeric vector")
> anno = anno_barplot(1:10, gp = gpar(fill = rep(c(1, 2), each = 5)), which = "row")
> draw(anno, index, test = "a numeric vector")
> 
> anno = anno_barplot(cbind(1:10, 10:1), gp = gpar(fill = 1:2))
> draw(anno, index, test = "a numeric vector")
> anno = anno_barplot(cbind(1:10, 10:1), gp = gpar(fill = 1:2), which = "row")
> draw(anno, index, test = "a numeric vector")
> 
> 
> m = matrix(rnorm(100), 10)
> m = m[, order(apply(m, 2, median))]
> anno = anno_boxplot(m, pch = 1:10, gp = gpar(fill = rep(c(1, 2), each = 5)),
+ 	size = unit(1:10, "mm"), height = unit(4, "cm"))
> draw(anno, index, test = "a numeric vector")
> anno = anno_boxplot(t(m), pch = 1:10, gp = gpar(fill = rep(c(1, 2), each = 5)),
+ 	size = unit(1:10, "mm"), which = "row", width = unit(4, "cm"))
> draw(anno, index, test = "a numeric vector")
> 
> anno = anno_histogram(m, gp = gpar(fill = rep(c(1, 2), each = 5)))
> draw(anno, index, test = "a numeric vector")
> anno = anno_histogram(t(m), gp = gpar(fill = rep(c(1, 2), each = 5)), which = "row")
> draw(anno, index, test = "a numeric vector")
> 
> anno = anno_density(m, gp = gpar(fill = rep(c(1, 2), each = 5)))
> draw(anno, index, test = "a numeric vector")
> anno = anno_density(t(m), gp = gpar(fill = rep(c(1, 2), each = 5)), which = "row")
> draw(anno, index, test = "a numeric vector")
> 
> 
> anno = anno_density(m, type = "violin", gp = gpar(fill = rep(c(1, 2), each = 5)))
> draw(anno, index, test = "a numeric vector")
> anno = anno_density(t(m), type = "violin", gp = gpar(fill = rep(c(1, 2), each = 5)), which = "row")
> draw(anno, index, test = "a numeric vector")
> 
> 
> anno = anno_text(month.name, gp = gpar(col = rep(c(1, 2), each = 5)))
> draw(anno, index, test = "a numeric vector")
> anno = anno_text(month.name, gp = gpar(col = rep(c(1, 2), each = 5)), which= "row")
> draw(anno, index, test = "a numeric vector")
> 
> lt = lapply(1:10, function(x) cumprod(1 + runif(1000, -x/100, x/100)) - 1)
> anno = anno_horizon(lt, gp = gpar(pos_fill = rep(c(1, 2), each = 5), neg_fill = rep(c(3, 4), each = 5)), which = "row")
> draw(anno, index, test = "a numeric vector")
> 
> m = matrix(rnorm(1000), nc = 10)
> lt = apply(m, 2, function(x) data.frame(density(x)[c("x", "y")]))
> anno = anno_joyplot(lt, gp = gpar(fill = rep(c(1, 2), each = 5)), 
+ 	width = unit(4, "cm"), which = "row")
> draw(anno, index, test = "joyplot")
> 
> 
> anno = anno_block(gp = gpar(fill = 1:4))
> draw(anno, index = 1:10, k = 1, n = 4, test = "anno_block")
> draw(anno, index = 1:10, k = 2, n = 4, test = "anno_block")
> 
> anno = anno_block(gp = gpar(fill = 1:4), labels = letters[1:4], labels_gp = gpar(col = "white"))
> draw(anno, index = 1:10, k = 2, n = 4, test = "anno_block")
> draw(anno, index = 1:10, k = 4, n = 4, test = "anno_block")
> # draw(anno, index = 1:10, k = 2, n = 2, test = "anno_block")
> 
> anno = anno_block(gp = gpar(fill = 1:4), labels = letters[1:4], labels_gp = gpar(col = "white"), which = "row")
> draw(anno, index = 1:10, k = 2, n = 4, test = "anno_block")
> 
> 
> ### anno_zoom
> fa = sort(sample(letters[1:3], 100, replace = TRUE, prob = c(1, 2, 3)))
> panel_fun = function(index, nm) {
+ 	grid.rect()
+ 	grid.text(nm)
+ }
> anno = anno_zoom(align_to = fa, which = "row", panel_fun = panel_fun)
> draw(anno, index = 1:100, test = "anno_zoom")
> 
> anno = anno_zoom(align_to = list(a = which(fa == "a")), which = "row", panel_fun = panel_fun)
> draw(anno, index = 1:100, test = "anno_zoom")
> 
> 
> panel_fun = function(index, nm) {
+ 	grid.rect(gp = gpar(fill = "grey", col = NA))
+ 	grid.text(nm)
+ }
> 
> anno = anno_zoom(align_to = fa, which = "row", panel_fun = panel_fun, link_gp = gpar(fill = "grey", col = "black"), internal_line = FALSE)
> draw(anno, index = 1:100, test = "anno_zoom")
> 
> 
> anno = anno_zoom(align_to = fa, which = "row", panel_fun = panel_fun,
+ 	gap = unit(1, "cm"))
> draw(anno, index = 1:100, test = "anno_zoom, set gap")
> 
> anno = anno_zoom(align_to = fa, which = "row", panel_fun = panel_fun,
+ 	size = 1:3)
> draw(anno, index = 1:100, test = "anno_zoom, size set as relative values")
> 
> anno = anno_zoom(align_to = fa, which = "row", panel_fun = panel_fun,
+ 	size = 1:3, extend = unit(1, "cm"))
> draw(anno, index = 1:100, test = "anno_zoom, extend")
> 
> anno = anno_zoom(align_to = fa, which = "row", panel_fun = panel_fun,
+ 	size = unit(1:3, "cm"))
> draw(anno, index = 1:100, test = "anno_zoom, size set as absolute values")
> 
> anno = anno_zoom(align_to = fa, which = "row", panel_fun = panel_fun,
+ 	size = unit(c(2, 20, 40), "cm"))
> draw(anno, index = 1:100, test = "anno_zoom, big size")
> 
> anno = anno_zoom(align_to = fa, which = "row", panel_fun = panel_fun,
+ 	size = 1:3, gap = unit(1, "cm"))
> draw(anno, index = 1:100, test = "anno_zoom, size set as relative values, gap")
> 
> anno = anno_zoom(align_to = fa, which = "row", panel_fun = panel_fun,
+ 	size = unit(1:3, "cm"), gap = unit(1, "cm"))
> draw(anno, index = 1:100, test = "anno_zoom, size set as absolute values, gap")
> 
> 
> anno = anno_zoom(align_to = fa, which = "row", panel_fun = panel_fun,
+ 	size = unit(1:3, "cm"), side = "left")
> draw(anno, index = 1:100, test = "anno_zoom, side")
> 
> 
> anno = anno_zoom(align_to = fa, which = "row", panel_fun = panel_fun,
+ 	size = unit(1:3, "cm"), link_gp = gpar(fill = 1:3))
> draw(anno, index = 1:100, test = "anno_zoom, link_gp")
> 
> anno = anno_zoom(align_to = fa, which = "row", panel_fun = panel_fun,
+ 	size = unit(1:3, "cm"), link_gp = gpar(fill = 1:3),
+ 	link_width = unit(2, "cm"), width = unit(4, "cm"))
> draw(anno, index = 1:100, test = "anno_zoom, width")
> 
> anno = anno_zoom(align_to = list(a = 1:10, b = 30:45, c = 70:90), 
+ 	which = "row", panel_fun = panel_fun, size = unit(1:3, "cm"))
> draw(anno, index = 1:100, test = "anno_zoom, a list of indices")
> 
> anno = anno_zoom(align_to = fa, which = "column", panel_fun = panel_fun,
+ 	size = unit(1:3, "cm"))
> draw(anno, index = 1:100, test = "anno_zoom, column annotation")
> 
> 
> m = matrix(rnorm(100*10), nrow = 100)
> hc = hclust(dist(m))
> fa2 = cutree(hc, k = 4)
> anno = anno_zoom(align_to = fa2, which = "row", panel_fun = panel_fun)
> draw(anno, index = hc$order, test = "anno_zoom, column annotation")
> 
> anno = anno_zoom(align_to = fa2, which = "column", panel_fun = panel_fun)
> draw(anno, index = hc$order, test = "anno_zoom, column annotation")
> 
> 
> anno = anno_zoom(align_to = fa2, which = "row", panel_fun = panel_fun)
> draw(Heatmap(m, cluster_rows = hc, right_annotation = rowAnnotation(foo = anno)))
> draw(Heatmap(m, cluster_rows = hc, right_annotation = rowAnnotation(foo = anno), row_split = 2))
> 
> 
> anno = anno_zoom(align_to = fa2, which = "row", panel_fun = panel_fun, size = unit(1:4, "cm"))
> draw(Heatmap(m, cluster_rows = hc, right_annotation = rowAnnotation(foo = anno)))
> 
> set.seed(123)
> m = matrix(rnorm(100*10), nrow = 100)
> subgroup = sample(letters[1:3], 100, replace = TRUE, prob = c(1, 5, 10))
> rg = range(m)
> panel_fun = function(index, nm) {
+ 	pushViewport(viewport(xscale = rg, yscale = c(0, 2)))
+ 	grid.rect()
+ 	grid.xaxis(gp = gpar(fontsize = 8))
+ 	grid.boxplot(m[index, ], pos = 1, direction = "horizontal")
+ 	grid.text(paste("distribution of group", nm), mean(rg), y = 1.9, 
+ 		just = "top", default.units = "native", gp = gpar(fontsize = 10))
+ 	popViewport()
+ }
> anno = anno_zoom(align_to = subgroup, which = "row", panel_fun = panel_fun, 
+ 	size = unit(2, "cm"), gap = unit(1, "cm"), width = unit(4, "cm"))
> draw(Heatmap(m, right_annotation = rowAnnotation(foo = anno), row_split = subgroup))
> 
> panel_fun2 = function(index, nm) {
+ 	pushViewport(viewport())
+ 	grid.rect()
+ 	n = floor(length(index)/4)
+ 	txt = paste("gene function", 1:n, collapse = "\n")
+ 	grid.text(txt, 0.95, 0.5, default.units = "npc", just = "right", gp = gpar(fontsize = 8))
+ 	popViewport()
+ }
> anno2 = anno_zoom(align_to = subgroup, which = "row", panel_fun = panel_fun2, 
+ 	gap = unit(1, "cm"), width = unit(3, "cm"), side = "left")
> 
> draw(Heatmap(m, right_annotation = rowAnnotation(subgroup = subgroup, foo = anno,
+ 	show_annotation_name = FALSE), 
+ 	left_annotation = rowAnnotation(bar = anno2, subgroup = subgroup, show_annotation_name = FALSE),
+ 	show_row_dend = FALSE,
+ 	row_split = subgroup))
> 
> draw(Heatmap(m, right_annotation = rowAnnotation(foo = anno), 
+ 	left_annotation = rowAnnotation(bar = anno2),
+ 	show_row_dend = FALSE,
+ 	row_split = subgroup))
> 
> set.seed(12345)
> mat = matrix(rnorm(30*10), nr = 30)
> row_split = c(rep("a", 10), rep("b", 5), rep("c", 2), rep("d", 3), 
+ 	          rep("e", 2), letters[10:17])
> row_split = factor(row_split)
> 
> panel_fun = function(index, name) {
+ 	pushViewport(viewport())
+ 	grid.rect()
+ 	grid.text(name)
+ 	popViewport()
+ }
> 
> anno = anno_zoom(align_to = row_split, which = "row", panel_fun = panel_fun, 
+ 	size = unit(0.5, "cm"), width = unit(4, "cm"))
> 
> # > dev.size()
> # [1] 3.938326 4.502203
> dev.new(width = 3.938326, height = 4.502203)
dev.new(): using pdf(file="Rplots1.pdf")
> draw(Heatmap(mat, right_annotation = rowAnnotation(foo = anno), 
+ 	row_split = row_split))
> 
> 
> 
> #### anno_customize ###
> x = sort(sample(letters[1:3], 10, replace = TRUE))
> graphics = list(
+ 	"a" = function(x, y, w, h) grid.points(x, y, pch = 16),
+ 	"b" = function(x, y, w, h) grid.rect(x, y, w*0.8, h*0.8, gp = gpar(fill = "red")),
+ 	"c" = function(x, y, w, h) grid.segments(x - 0.5*w, y - 0.5*h, x + 0.5*w, y + 0.5*h, gp = gpar(lty = 2))
+ )
> 
> anno = anno_customize(x, graphics = graphics)
> draw(anno, index = 1:10, test = "")
> 
> anno = anno_customize(c(x, "d"), graphics = graphics)
Note: following levels in `x` have no graphics defined:
    d.
Set `verbose = FALSE` in `anno_customize()` to turn off this message.
> 
> ### anno_numeric ##
> x = runif(10)
> anno = anno_numeric(x)
> draw(anno, 1:10, test = TRUE)
> anno = anno_numeric(x, align_to = "right")
> draw(anno, 1:10, test = TRUE)
> 
> 
> x = 10^(-runif(10, 1, 6))
> anno = anno_numeric(x, x_convert = function(x) -log10(x), labels_format = function(x) sprintf("%.2e", x))
> draw(anno, 1:10, test = TRUE)
> 
> x = runif(10, -1, 1)
> anno = anno_numeric(x)
> draw(anno, 1:10, test = TRUE)
> anno = anno_numeric(x, labels_gp = gpar(col = c("green", "red")))
> draw(anno, 1:10, test = TRUE)
> 
> anno = anno_numeric(x, bg_gp = gpar(col = c("green", "red")))
> draw(anno, 1:10, test = TRUE)
> 
> 
> x = runif(10, 0.5, 1.5)
> anno = anno_numeric(x, align_to = 0)
> draw(anno, 1:10, test = TRUE)
> 
> 
> 
> 
> 
> proc.time()
   user  system elapsed 
 38.466   0.993  42.327


R version 4.3.3 (2024-02-29) -- "Angel Food Cake"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin20 (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(circlize)
========================================
circlize version 0.4.16
CRAN page: https://cran.r-project.org/package=circlize
Github page: https://github.com/jokergoo/circlize
Documentation: https://jokergoo.github.io/circlize_book/book/

If you use it in published research, please cite:
Gu, Z. circlize implements and enhances circular visualization
  in R. Bioinformatics 2014.

This message can be suppressed by:
  suppressPackageStartupMessages(library(circlize))
========================================

> library(ComplexHeatmap)
Loading required package: grid
========================================
ComplexHeatmap version 2.18.0
Bioconductor page: http://bioconductor.org/packages/ComplexHeatmap/
Github page: https://github.com/jokergoo/ComplexHeatmap
Documentation: http://jokergoo.github.io/ComplexHeatmap-reference

If you use it in published research, please cite either one:
- Gu, Z. Complex Heatmap Visualization. iMeta 2022.
- Gu, Z. Complex heatmaps reveal patterns and correlations in multidimensional 
    genomic data. Bioinformatics 2016.


The new InteractiveComplexHeatmap package can directly export static 
complex heatmaps into an interactive Shiny app with zero effort. Have a try!

This message can be suppressed by:
  suppressPackageStartupMessages(library(ComplexHeatmap))
========================================

> library(GetoptLong)
> 
> cm = ColorMapping(name = "test",
+ 	colors = c("blue", "white", "red"),
+ 	levels = c("a", "b", "c"))
> color_mapping_legend(cm)
> 
> cm = ColorMapping(name = "test",
+ 	col_fun = colorRamp2(c(0, 0.5, 1), c("blue", "white", "red")))
> color_mapping_legend(cm)
> 
> cm = ColorMapping(name = "test",
+ 	colors = c("blue", "white", "red"),
+ 	levels = c(1, 2, 3))
> color_mapping_legend(cm)
> 
> ha = SingleAnnotation(value = rep(NA, 10), name = "foo")
> cm = ha@color_mapping
> color_mapping_legend(cm)
> 
> 
> proc.time()
   user  system elapsed 
  4.816   0.384   5.608


R version 4.3.3 (2024-02-29) -- "Angel Food Cake"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin20 (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(circlize)
========================================
circlize version 0.4.16
CRAN page: https://cran.r-project.org/package=circlize
Github page: https://github.com/jokergoo/circlize
Documentation: https://jokergoo.github.io/circlize_book/book/

If you use it in published research, please cite:
Gu, Z. circlize implements and enhances circular visualization
  in R. Bioinformatics 2014.

This message can be suppressed by:
  suppressPackageStartupMessages(library(circlize))
========================================

> library(ComplexHeatmap)
Loading required package: grid
========================================
ComplexHeatmap version 2.18.0
Bioconductor page: http://bioconductor.org/packages/ComplexHeatmap/
Github page: https://github.com/jokergoo/ComplexHeatmap
Documentation: http://jokergoo.github.io/ComplexHeatmap-reference

If you use it in published research, please cite either one:
- Gu, Z. Complex Heatmap Visualization. iMeta 2022.
- Gu, Z. Complex heatmaps reveal patterns and correlations in multidimensional 
    genomic data. Bioinformatics 2016.


The new InteractiveComplexHeatmap package can directly export static 
complex heatmaps into an interactive Shiny app with zero effort. Have a try!

This message can be suppressed by:
  suppressPackageStartupMessages(library(ComplexHeatmap))
========================================

> library(GetoptLong)
> 
> if(!exists("cut_dendrogram")) {
+ 	cut_dendrogram = ComplexHeatmap:::cut_dendrogram
+ }
> 
> library(dendextend)

---------------------
Welcome to dendextend version 1.17.1
Type citation('dendextend') for how to cite the package.

Type browseVignettes(package = 'dendextend') for the package vignette.
The github page is: https://github.com/talgalili/dendextend/

Suggestions and bug-reports can be submitted at: https://github.com/talgalili/dendextend/issues
You may ask questions at stackoverflow, use the r and dendextend tags: 
	 https://stackoverflow.com/questions/tagged/dendextend

	To suppress this message use:  suppressPackageStartupMessages(library(dendextend))
---------------------


Attaching package: 'dendextend'

The following object is masked from 'package:stats':

    cutree

> 
> m = matrix(rnorm(100), 10)
> dend1 = as.dendrogram(hclust(dist(m)))
> dend1 = adjust_dend_by_x(dend1, sort(runif(10)))
> 
> m = matrix(rnorm(50), nr = 5)
> dend2 = as.dendrogram(hclust(dist(m)))
> 
> dend3 = as.dendrogram(hclust(dist(m[1:2, ])))
> 
> 
> dend_merge = merge_dendrogram(dend3, 
+ 	list(set(dend1, "branches_col", "red"), 
+ 		 set(dend2, "branches_col", "blue"))
+ )
> 
> grid.dendrogram(dend_merge, test = TRUE, facing = "bottom")
> grid.dendrogram(dend_merge, test = TRUE, facing = "top")
> grid.dendrogram(dend_merge, test = TRUE, facing = "left")
> grid.dendrogram(dend_merge, test = TRUE, facing = "right")
> 
> grid.dendrogram(dend_merge, test = TRUE, facing = "bottom", order = "reverse")
> grid.dendrogram(dend_merge, test = TRUE, facing = "top", order = "reverse")
> grid.dendrogram(dend_merge, test = TRUE, facing = "left", order = "reverse")
> grid.dendrogram(dend_merge, test = TRUE, facing = "right", order = "reverse")
> 
> 
> m = matrix(rnorm(100), 10)
> dend1 = as.dendrogram(hclust(dist(m)))
> dend1 = adjust_dend_by_x(dend1, unit(1:10, "cm"))
> grid.dendrogram(dend1, test = TRUE)
> 
> dl = cut_dendrogram(dend1, k = 3)
> grid.dendrogram(dl$upper, test = TRUE)
> 
> 
> m1 = matrix(rnorm(100), nr = 10)
> m2 = matrix(rnorm(80), nr = 8)
> m3 = matrix(rnorm(50), nr = 5)
> dend1 = as.dendrogram(hclust(dist(m1)))
> dend2 = as.dendrogram(hclust(dist(m2)))
> dend3 = as.dendrogram(hclust(dist(m3)))
> dend_p = as.dendrogram(hclust(dist(rbind(colMeans(m1), colMeans(m2), colMeans(m3)))))
> dend_m = merge_dendrogram(dend_p, list(dend1, dend2, dend3))
> grid.dendrogram(dend_m, test = T)
> 
> dend_m = merge_dendrogram(dend_p, list(dend1, dend2, dend3), only_parent = TRUE)
> grid.dendrogram(dend_m, test = T)
> 
> require(dendextend)
> dend1 = color_branches(dend1, k = 1, col = "red")
> dend2 = color_branches(dend2, k = 1, col = "blue")
> dend3 = color_branches(dend3, k = 1, col = "green")
> dend_p = color_branches(dend_p, k = 1, col = "orange")
> dend_m = merge_dendrogram(dend_p, list(dend1, dend2, dend3))
> grid.dendrogram(dend_m, test = T)
> 
> 
> m = matrix(rnorm(120), nc = 12)
> colnames(m) = letters[1:12]
> fa = rep(c("a", "b", "c"), times = c(2, 4, 6))
> dend = cluster_within_group(m, fa)
> grid.dendrogram(dend, test = TRUE)
> 
> 
> # stack overflow problem
> m = matrix(1, nrow = 1000, ncol = 10)
> m[1, 2] = 2
> dend = as.dendrogram(hclust(dist(m)))
> grid.dendrogram(dend, test = T)
> 
> # node attr
> m = matrix(rnorm(100), 10)
> dend = as.dendrogram(hclust(dist(m)))
> require(dendextend)
> dend1 = color_branches(dend, k = 2, col = 1:2)
> grid.dendrogram(dend1, test = T)
> dend1 = dend
> dend1 = dendrapply(dend, function(d) {
+ 	attr(d, "nodePar") = list(pch = sample(20, 1), cex = runif(1, min = 0.3, max = 1.3), col = rand_color(1))
+ 	d
+ })
> grid.dendrogram(dend1, test = T)
> 
> Heatmap(m, cluster_rows = dend1, cluster_columns = dend1)
> 
> d1 = ComplexHeatmap:::dend_edit_node(dend, method = "top-bottom", function(d, index) {
+ 	attr(d, "depth") = length(index)
+ 	d
+ })
> 
> d2 = ComplexHeatmap:::dend_edit_node(dend, method = "bottom-top", function(d, index) {
+ 	attr(d, "depth") = length(index)
+ 	d
+ })
> 
> identical(d1, d2)
[1] TRUE
> 
> proc.time()
   user  system elapsed 
 14.464   0.710  15.818


R version 4.3.3 (2024-02-29) -- "Angel Food Cake"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin20 (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(ComplexHeatmap)
Loading required package: grid
========================================
ComplexHeatmap version 2.18.0
Bioconductor page: http://bioconductor.org/packages/ComplexHeatmap/
Github page: https://github.com/jokergoo/ComplexHeatmap
Documentation: http://jokergoo.github.io/ComplexHeatmap-reference

If you use it in published research, please cite either one:
- Gu, Z. Complex Heatmap Visualization. iMeta 2022.
- Gu, Z. Complex heatmaps reveal patterns and correlations in multidimensional 
    genomic data. Bioinformatics 2016.


The new InteractiveComplexHeatmap package can directly export static 
complex heatmaps into an interactive Shiny app with zero effort. Have a try!

This message can be suppressed by:
  suppressPackageStartupMessages(library(ComplexHeatmap))
========================================

> 
> if(requireNamespace("gridtext")) {
+ ##### test anno_richtext ####
+ mat = matrix(rnorm(100), 10)
+ rownames(mat) = letters[1:10]
+ ht = Heatmap(mat, 
+ 	column_title = gt_render("Some <span style='color:blue'>blue text **in bold.**</span><br>And *italics text.*<br>And some <span style='font-size:18pt; color:black'>large</span> text.", r = unit(2, "pt"), padding = unit(c(2, 2, 2, 2), "pt")),
+ 	column_title_gp = gpar(box_fill = "orange"),
+ 	row_labels = gt_render(letters[1:10], padding = unit(c(2, 10, 2, 10), "pt")),
+ 	row_names_gp = gpar(box_col = rep(2:3, times = 5), box_fill = ifelse(1:10%%2, "yellow", "white")),
+ 	row_km = 2, 
+ 	row_title = gt_render(c("title1", "title2")), 
+ 	row_title_gp = gpar(box_fill = "yellow"),
+ 	heatmap_legend_param = list(
+ 		title = gt_render("<span style='color:orange'>**Legend title**</span>"), 
+ 		title_gp = gpar(box_fill = "grey"),
+ 		at = c(-3, 0, 3), 
+ 		labels = gt_render(c("*negative* three", "zero", "*positive* three"))
+ 	))
+ ht = rowAnnotation(
+ 	foo = anno_text(gt_render(sapply(LETTERS[1:10], strrep, 10), align_widths = TRUE), 
+ 	                gp = gpar(box_col = "blue", box_lwd = 2), 
+ 	                just = "right", 
+ 	                location = unit(1, "npc")
+ 	)) + ht
+ draw(ht)
+ 
+ }
Loading required namespace: gridtext
> 
> proc.time()
   user  system elapsed 
  8.942   0.554   9.502


R version 4.3.3 (2024-02-29) -- "Angel Food Cake"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin20 (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(circlize)
========================================
circlize version 0.4.16
CRAN page: https://cran.r-project.org/package=circlize
Github page: https://github.com/jokergoo/circlize
Documentation: https://jokergoo.github.io/circlize_book/book/

If you use it in published research, please cite:
Gu, Z. circlize implements and enhances circular visualization
  in R. Bioinformatics 2014.

This message can be suppressed by:
  suppressPackageStartupMessages(library(circlize))
========================================

> library(ComplexHeatmap)
Loading required package: grid
========================================
ComplexHeatmap version 2.18.0
Bioconductor page: http://bioconductor.org/packages/ComplexHeatmap/
Github page: https://github.com/jokergoo/ComplexHeatmap
Documentation: http://jokergoo.github.io/ComplexHeatmap-reference

If you use it in published research, please cite either one:
- Gu, Z. Complex Heatmap Visualization. iMeta 2022.
- Gu, Z. Complex heatmaps reveal patterns and correlations in multidimensional 
    genomic data. Bioinformatics 2016.


The new InteractiveComplexHeatmap package can directly export static 
complex heatmaps into an interactive Shiny app with zero effort. Have a try!

This message can be suppressed by:
  suppressPackageStartupMessages(library(ComplexHeatmap))
========================================

> library(GetoptLong)
> 
> set.seed(123)
> nr1 = 10; nr2 = 8; nr3 = 6
> nc1 = 6; nc2 = 8; nc3 = 10
> mat = cbind(rbind(matrix(rnorm(nr1*nc1, mean = 1,   sd = 0.5), nr = nr1),
+           matrix(rnorm(nr2*nc1, mean = 0,   sd = 0.5), nr = nr2),
+           matrix(rnorm(nr3*nc1, mean = 0,   sd = 0.5), nr = nr3)),
+     rbind(matrix(rnorm(nr1*nc2, mean = 0,   sd = 0.5), nr = nr1),
+           matrix(rnorm(nr2*nc2, mean = 1,   sd = 0.5), nr = nr2),
+           matrix(rnorm(nr3*nc2, mean = 0,   sd = 0.5), nr = nr3)),
+     rbind(matrix(rnorm(nr1*nc3, mean = 0.5, sd = 0.5), nr = nr1),
+           matrix(rnorm(nr2*nc3, mean = 0.5, sd = 0.5), nr = nr2),
+           matrix(rnorm(nr3*nc3, mean = 1,   sd = 0.5), nr = nr3))
+    )
> 
> rownames(mat) = paste0("row", seq_len(nrow(mat)))
> colnames(mat) = paste0("column", seq_len(nrow(mat)))
> 
> ht = Heatmap(mat)
> draw(ht, test = TRUE)
> ht
> 
> 
> ht = Heatmap(mat, col = colorRamp2(c(-3, 0, 3), c("green", "white", "red")))
> draw(ht, test = TRUE)
> 
> ht = Heatmap(mat, name = "test")
> draw(ht, test = TRUE)
> 
> ht = Heatmap(mat, rect_gp = gpar(col = "black"))
> draw(ht, test = TRUE)
> 
> ht = Heatmap(mat, border = "red")
> draw(ht, test = TRUE)
> 
> ######## test title ##########
> ht = Heatmap(mat, row_title = "blablabla")
> draw(ht, test = TRUE)
> 
> ht = Heatmap(mat, row_title = "blablabla", row_title_side = "right")
> draw(ht, test = TRUE)
> 
> ht = Heatmap(mat, row_title = "blablabla", row_title_gp = gpar(fontsize = 20, font = 2))
> draw(ht, test = TRUE)
> 
> # ht = Heatmap(mat, row_title = "blablabla", row_title_rot = 45)
> # draw(ht, test = TRUE)
> 
> ht = Heatmap(mat, row_title = "blablabla", row_title_rot = 0)
> draw(ht, test = TRUE)
> 
> ht = Heatmap(mat, row_title = "blablabla", row_title_gp = gpar(fill = "red", col = "white"))
> draw(ht, test = TRUE)
> 
> ht = Heatmap(mat, column_title = "blablabla")
> draw(ht, test = TRUE)
> 
> ht = Heatmap(mat, column_title = "blablabla", column_title_side = "bottom")
> draw(ht, test = TRUE)
> 
> ht = Heatmap(mat, column_title = "blablabla", column_title_gp = gpar(fontsize = 20, font = 2))
> draw(ht, test = TRUE)
> 
> # ht = Heatmap(mat, column_title = "blablabla", column_title_rot = 45)
> # draw(ht, test = TRUE)
> 
> ht = Heatmap(mat, column_title = "blablabla", column_title_rot = 90)
> draw(ht, test = TRUE)
> 
> 
> ### test clustering ####
> 
> ht = Heatmap(mat, cluster_rows = FALSE)
> draw(ht, test = TRUE)
> 
> ht = Heatmap(mat, clustering_distance_rows = "pearson")
> draw(ht, test = TRUE)
> 
> ht = Heatmap(mat, clustering_distance_rows = function(x) dist(x))
> draw(ht, test = TRUE)
> 
> ht = Heatmap(mat, clustering_distance_rows = function(x, y) 1 - cor(x, y))
> draw(ht, test = TRUE)
> 
> ht = Heatmap(mat, clustering_method_rows = "single")
> draw(ht, test = TRUE)
> 
> ht = Heatmap(mat, row_dend_side = "right")
> draw(ht, test = TRUE)
> 
> ht = Heatmap(mat, row_dend_width = unit(4, "cm"))
> draw(ht, test = TRUE)
> 
> ht = Heatmap(mat, row_dend_gp = gpar(lwd = 2, col = "red"))
> draw(ht, test = TRUE)
> 
> dend = as.dendrogram(hclust(dist(mat)))
> ht = Heatmap(mat, cluster_rows = dend)
> draw(ht, test = TRUE)
> 
> library(dendextend)

---------------------
Welcome to dendextend version 1.17.1
Type citation('dendextend') for how to cite the package.

Type browseVignettes(package = 'dendextend') for the package vignette.
The github page is: https://github.com/talgalili/dendextend/

Suggestions and bug-reports can be submitted at: https://github.com/talgalili/dendextend/issues
You may ask questions at stackoverflow, use the r and dendextend tags: 
	 https://stackoverflow.com/questions/tagged/dendextend

	To suppress this message use:  suppressPackageStartupMessages(library(dendextend))
---------------------


Attaching package: 'dendextend'

The following object is masked from 'package:stats':

    cutree

> dend = color_branches(dend, k = 3)
> ht = Heatmap(mat, cluster_rows = dend)
> draw(ht, test = TRUE)
> 
> 
> ht = Heatmap(mat, cluster_columns = FALSE)
> draw(ht, test = TRUE)
> 
> ht = Heatmap(mat, clustering_distance_columns = "pearson")
> draw(ht, test = TRUE)
> 
> ht = Heatmap(mat, clustering_distance_columns = function(x) dist(x))
> draw(ht, test = TRUE)
> 
> ht = Heatmap(mat, clustering_distance_columns = function(x, y) 1 - cor(x, y))
> draw(ht, test = TRUE)
> 
> ht = Heatmap(mat, clustering_method_columns = "single")
> draw(ht, test = TRUE)
> 
> ht = Heatmap(mat, column_dend_side = "bottom")
> draw(ht, test = TRUE)
> 
> ht = Heatmap(mat, column_dend_height = unit(4, "cm"))
> draw(ht, test = TRUE)
> 
> ht = Heatmap(mat, column_dend_gp = gpar(lwd = 2, col = "red"))
> draw(ht, test = TRUE)
> 
> dend = as.dendrogram(hclust(dist(t(mat))))
> ht = Heatmap(mat, cluster_columns = dend)
> draw(ht, test = TRUE)
> 
> dend = color_branches(dend, k = 3)
> ht = Heatmap(mat, cluster_columns = dend)
> draw(ht, test = TRUE)
> 
> 
> ### test row/column order
> od = c(seq(1, 24, by = 2), seq(2, 24, by = 2))
> ht = Heatmap(mat, row_order = od)
> draw(ht, test = TRUE)
> 
> ht = Heatmap(mat, row_order = od, cluster_rows = TRUE)
> draw(ht, test = TRUE)
> 
> ht = Heatmap(mat, column_order = od)
> draw(ht, test = TRUE)
> 
> ht = Heatmap(mat, column_order = od, cluster_columns = TRUE)
> draw(ht, test = TRUE)
> 
> 
> #### test row/column names #####
> ht = Heatmap(unname(mat))
> draw(ht, test = TRUE)
> 
> ht = Heatmap(mat, show_row_names = FALSE)
> draw(ht, test = TRUE)
> 
> ht = Heatmap(mat, row_names_side = "left")
> draw(ht, test = TRUE)
> 
> random_str2 = function(k) {
+ 	sapply(1:k, function(i) paste(sample(letters, sample(5:10, 1)), collapse = ""))
+ }
> ht = Heatmap(mat, row_labels = random_str2(24))
> draw(ht, test = TRUE)
> 
> ht = Heatmap(mat, row_names_gp = gpar(fontsize = 20))
> draw(ht, test = TRUE)
> 
> ht = Heatmap(mat, row_names_gp = gpar(fontsize = 1:24/2 + 5))
> draw(ht, test = TRUE)
> 
> ht = Heatmap(mat, row_names_rot = 45)
> draw(ht, test = TRUE)
> 
> ht = Heatmap(mat, row_names_rot = 45, row_names_side = "left")
> draw(ht, test = TRUE)
> 
> ht = Heatmap(mat, show_column_names = FALSE)
> draw(ht, test = TRUE)
> 
> ht = Heatmap(mat, column_names_side = "top")
> draw(ht, test = TRUE)
> 
> ht = Heatmap(mat, column_labels = random_str2(24))
> draw(ht, test = TRUE)
> 
> ht = Heatmap(mat, column_names_gp = gpar(fontsize = 20))
> draw(ht, test = TRUE)
> 
> ht = Heatmap(mat, column_names_gp = gpar(fontsize = 1:24/2 + 5))
> draw(ht, test = TRUE)
> 
> ht = Heatmap(mat, column_names_rot = 45)
> draw(ht, test = TRUE)
> 
> ### test annotations ####
> anno = HeatmapAnnotation(
+ 	foo = 1:24,
+ 	df = data.frame(type = c(rep("A", 12), rep("B", 12))),
+ 	bar = anno_barplot(24:1))
> ht = Heatmap(mat, top_annotation = anno)
> draw(ht, test = TRUE)
> 
> ht = Heatmap(mat, bottom_annotation = anno)
> draw(ht, test = TRUE)
> 
> ht = Heatmap(mat, top_annotation = anno, bottom_annotation = anno)
> draw(ht, test = TRUE)
> 
> 
> ### test split ####
> ht = Heatmap(mat, km = 3)
> draw(ht, test = TRUE)
> 
> ht = Heatmap(mat, row_km = 3)
> draw(ht, test = TRUE)
> 
> ht = Heatmap(mat, split = rep(c("A", "B"), times = c(6, 18)))
> draw(ht, test = TRUE)
> 
> ht = Heatmap(mat, row_split = rep(c("A", "B"), times = c(6, 18)))
> draw(ht, test = TRUE)
> 
> ht = Heatmap(mat, row_split = factor(rep(c("A", "B"), times = c(6, 18)), levels = c("B", "A")))
> draw(ht, test = TRUE)
> 
> ht = Heatmap(mat, row_split = rep(c("A", "B"), 12), row_gap = unit(5, "mm"))
> draw(ht, test = TRUE)
> 
> ht = Heatmap(mat, row_split = data.frame(rep(c("A", "B"), 12), rep(c("C", "D"), each = 12)))
> draw(ht, test = TRUE)
> 
> ht = Heatmap(mat, row_split = data.frame(rep(c("A", "B"), 12), rep(c("C", "D"), each = 12)),
+ 	row_gap = unit(c(1, 2, 3), "mm"))
> draw(ht, test = TRUE)
> 
> ht = Heatmap(mat, row_km = 3, row_title = "foo")
> draw(ht, test = TRUE)
> 
> ht = Heatmap(mat, row_km = 3, row_title = "cluster%s")
> draw(ht, test = TRUE)
> 
> ht = Heatmap(mat, row_km = 3, row_title = "cluster%s", row_title_rot = 0)
> draw(ht, test = TRUE)
> 
> ht = Heatmap(mat, row_km = 3, row_title = "cluster%s", row_title_gp = gpar(fill = 2:4, col = "white"))
> draw(ht, test = TRUE)
> 
> ht = Heatmap(mat, row_km = 3, row_title = NULL)
> draw(ht, test = TRUE)
> 
> ht = Heatmap(mat, row_km = 3, row_names_gp = gpar(col = 2:4))
> draw(ht, test = TRUE)
> 
> ht = Heatmap(mat, row_split = rep(c("A", "B"), times = c(6, 18)), row_km = 3)
> draw(ht, test = TRUE)
> 
> ht = Heatmap(mat, row_split = rep(c("A", "B"), times = c(6, 18)), row_km = 3, row_title = "cluster%s,group%s", row_title_rot = 0)
> draw(ht, test = TRUE)
> 
> ht = Heatmap(mat, row_split = 2)
> draw(ht, test = TRUE)
> 
> ht = Heatmap(mat, row_split = 2, row_title = "foo")
> ht = Heatmap(mat, row_split = 2, row_title = "cluster%s")
> 
> 
> dend = as.dendrogram(hclust(dist(mat)))
> ht = Heatmap(mat, cluster_rows = dend, row_split = 2)
> draw(ht, test = TRUE)
> 
> ht = Heatmap(mat, row_split = 2, row_names_gp = gpar(col = 2:3))
> draw(ht, test = TRUE)
> 
> 
> ### column split
> ht = Heatmap(mat, column_km = 2)
> draw(ht, test = TRUE)
> 
> ht = Heatmap(mat, column_km = 2, column_gap = unit(1, "cm"))
> draw(ht, test = TRUE)
> 
> ht = Heatmap(mat, column_split = rep(c("A", "B"), times = c(6, 18)))
> draw(ht, test = TRUE)
> 
> ht = Heatmap(mat, column_split = data.frame(rep(c("A", "B"), 12), rep(c("C", "D"), each = 12)),
+ 	column_gap = unit(c(1, 2, 3), "mm"))
> draw(ht, test = TRUE)
> 
> ht = Heatmap(mat, column_km = 2, column_title = "foo")
> draw(ht, test = TRUE)
> 
> ht = Heatmap(mat, column_km = 2, column_title = "cluster%s")
> draw(ht, test = TRUE)
> 
> ht = Heatmap(mat, column_km = 2, column_title = "cluster%s", column_title_rot = 90)
> draw(ht, test = TRUE)
> 
> ht = Heatmap(mat, column_km = 2, column_title = "cluster%s", column_title_gp = gpar(fill = 2:3, col = "white"))
> draw(ht, test = TRUE)
> 
> ht = Heatmap(mat, column_km = 2, column_title = NULL)
> draw(ht, test = TRUE)
> 
> ht = Heatmap(mat, column_km = 2, column_names_gp = gpar(col = 2:3))
> draw(ht, test = TRUE)
> 
> ht = Heatmap(mat, column_split = factor(rep(c("A", "B"), times = c(6, 18)), levels = c("A", "B")), column_km = 2)
> draw(ht, test = TRUE)
> ht = Heatmap(mat, column_split = factor(rep(c("A", "B"), times = c(6, 18)), levels = c("B", "A")), column_km = 2)
> 
> 
> ht = Heatmap(mat, column_split = rep(c("A", "B"), times = c(6, 18)), column_km = 2, 
+ 	column_title = "cluster%s,group%s", column_title_rot = 90)
> draw(ht, test = TRUE)
> 
> ht = Heatmap(mat, column_split = 3)
> draw(ht, test = TRUE)
> 
> dend = as.dendrogram(hclust(dist(t(mat))))
> ht = Heatmap(mat, cluster_columns = dend, column_split = 3)
> draw(ht, test = TRUE)
> 
> ht = Heatmap(mat, top_annotation = anno, bottom_annotation = anno, column_km = 2)
> draw(ht, test = TRUE)
> 
> ht = Heatmap(mat, top_annotation = anno, bottom_annotation = anno, column_split = 3)
> draw(ht, test = TRUE)
> 
> ### combine row and column split
> ht = Heatmap(mat, row_km = 3, column_km = 3)
> draw(ht, test = TRUE)
> 
> ht = Heatmap(mat, row_split = 3, column_split = 3)
> draw(ht, test = TRUE)
> 
> ht = Heatmap(mat, row_km = 3, column_split = 3)
> draw(ht, test = TRUE)
> 
> ht = Heatmap(mat, row_split = rep(c("A", "B"), 12), 
+ 	column_split = rep(c("C", "D"), 12))
> draw(ht, test = TRUE)
> 
> ht = Heatmap(mat, top_annotation = anno,
+ 	row_split = rep(c("A", "B"), 12), 
+ 	row_names_gp = gpar(col = 2:3), row_gap = unit(2, "mm"),
+ 	column_split = 3,
+ 	column_names_gp = gpar(col = 2:4), column_gap = unit(4, "mm")
+ )
> draw(ht, test = TRUE)
> 
> 
> #### character matrix
> mat3 = matrix(sample(letters[1:6], 100, replace = TRUE), 10, 10)
> rownames(mat3) = {x = letters[1:10]; x[1] = "aaaaaaaaaaaaaaaaaaaaaaa";x}
> ht = Heatmap(mat3, rect_gp = gpar(col = "white"))
> draw(ht, test = TRUE)
> 
> 
> ### cell_fun
> mat = matrix(1:9, 3, 3)
> rownames(mat) = letters[1:3]
> colnames(mat) = letters[1:3]
> 
> ht = Heatmap(mat, rect_gp = gpar(col = "white"), cell_fun = function(j, i, x, y, width, height, fill) grid.text(mat[i, j], x = x, y = y),
+ 	cluster_rows = FALSE, cluster_columns = FALSE, row_names_side = "left", column_names_side = "top",
+ 	column_names_rot = 0)
> draw(ht, test = TRUE)
> 
> 
> ### test the size
> ht = Heatmap(mat)
> ht = prepare(ht)
> ht@heatmap_param[c("width", "height")]
$width
[1] 1npc

$height
[1] 1npc

> ht@matrix_param[c("width", "height")]
$width
[1] 3null

$height
[1] 3null

> 
> ht = Heatmap(mat, width = unit(10, "cm"), height = unit(10, "cm"))
> ht = prepare(ht)
> ht@heatmap_param[c("width", "height")]
$width
[1] 114.853733333333mm

$height
[1] 114.853733333333mm

> ht@matrix_param[c("width", "height")]
$width
[1] 10cm

$height
[1] 10cm

> draw(ht, test = TRUE)
> 
> ht = Heatmap(mat, width = unit(10, "cm"))
> ht = prepare(ht)
> ht@heatmap_param[c("width", "height")]
$width
[1] 114.853733333333mm

$height
[1] 1npc

> ht@matrix_param[c("width", "height")]
$width
[1] 10cm

$height
[1] 3null

> draw(ht, test = TRUE)
> 
> ht = Heatmap(mat, heatmap_width = unit(10, "cm"), heatmap_height = unit(10, "cm"))
> ht = prepare(ht)
> ht@heatmap_param[c("width", "height")]
$width
[1] 10cm

$height
[1] 10cm

> ht@matrix_param[c("width", "height")]
$width
[1] 85.1462666666667mm

$height
[1] 85.1462666666667mm

> draw(ht, test = TRUE)
> 
> ht = Heatmap(mat, heatmap_width = unit(10, "cm"))
> ht = prepare(ht)
> ht@heatmap_param[c("width", "height")]
$width
[1] 10cm

$height
[1] 1npc

> ht@matrix_param[c("width", "height")]
$width
[1] 85.1462666666667mm

$height
[1] 3null

> draw(ht, test = TRUE)
> 
> ht = Heatmap(mat, use_raster = TRUE)
> draw(ht, test = TRUE)
> 
> ht = Heatmap(mat, row_km = 2, use_raster = TRUE)
> draw(ht, test = TRUE)
> 
> ht = Heatmap(mat, row_km = 2, column_km = 2, use_raster = TRUE)
> draw(ht, test = TRUE)
> 
> #### test global padding
> ra = rowAnnotation(foo = 1:3)
> ht = Heatmap(mat, show_column_names = FALSE) + ra
> draw(ht)
> 
> ht = Heatmap(matrix(rnorm(100), 10), row_km = 2, row_title = "")
> draw(ht)
> 
> if(0) {
+ ht = Heatmap(matrix(rnorm(100), 10), heatmap_width = unit(5, "mm"))
+ draw(ht)
+ }
> 
> proc.time()
   user  system elapsed 
 46.653   0.987  51.257


R version 4.3.3 (2024-02-29) -- "Angel Food Cake"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin20 (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(circlize)
========================================
circlize version 0.4.16
CRAN page: https://cran.r-project.org/package=circlize
Github page: https://github.com/jokergoo/circlize
Documentation: https://jokergoo.github.io/circlize_book/book/

If you use it in published research, please cite:
Gu, Z. circlize implements and enhances circular visualization
  in R. Bioinformatics 2014.

This message can be suppressed by:
  suppressPackageStartupMessages(library(circlize))
========================================

> library(ComplexHeatmap)
Loading required package: grid
========================================
ComplexHeatmap version 2.18.0
Bioconductor page: http://bioconductor.org/packages/ComplexHeatmap/
Github page: https://github.com/jokergoo/ComplexHeatmap
Documentation: http://jokergoo.github.io/ComplexHeatmap-reference

If you use it in published research, please cite either one:
- Gu, Z. Complex Heatmap Visualization. iMeta 2022.
- Gu, Z. Complex heatmaps reveal patterns and correlations in multidimensional 
    genomic data. Bioinformatics 2016.


The new InteractiveComplexHeatmap package can directly export static 
complex heatmaps into an interactive Shiny app with zero effort. Have a try!

This message can be suppressed by:
  suppressPackageStartupMessages(library(ComplexHeatmap))
========================================

> library(GetoptLong)
> 
> # ht_opt("verbose" = TRUE)
> m = matrix(rnorm(50), nr = 10)
> 
> ht = Heatmap(m)
> ht = make_row_cluster(ht)
> 
> ht = Heatmap(m, cluster_rows = FALSE)
> ht = make_row_cluster(ht)
> 
> ht = Heatmap(m, row_km = 2)
> ht = make_row_cluster(ht)
> 
> ht = Heatmap(m, row_split = sample(letters[1:2], 10, replace = TRUE))
> ht = make_row_cluster(ht)
> 
> ht = Heatmap(m, cluster_rows = hclust(dist(m)))
> ht = make_row_cluster(ht)
> 
> ht = Heatmap(m, cluster_rows = hclust(dist(m)), row_split = 2)
> ht = make_row_cluster(ht)
> 
> # ht_opt("verbose" = FALSE)
> 
> proc.time()
   user  system elapsed 
  5.106   0.391   5.863


R version 4.3.3 (2024-02-29) -- "Angel Food Cake"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin20 (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(circlize)
========================================
circlize version 0.4.16
CRAN page: https://cran.r-project.org/package=circlize
Github page: https://github.com/jokergoo/circlize
Documentation: https://jokergoo.github.io/circlize_book/book/

If you use it in published research, please cite:
Gu, Z. circlize implements and enhances circular visualization
  in R. Bioinformatics 2014.

This message can be suppressed by:
  suppressPackageStartupMessages(library(circlize))
========================================

> library(ComplexHeatmap)
Loading required package: grid
========================================
ComplexHeatmap version 2.18.0
Bioconductor page: http://bioconductor.org/packages/ComplexHeatmap/
Github page: https://github.com/jokergoo/ComplexHeatmap
Documentation: http://jokergoo.github.io/ComplexHeatmap-reference

If you use it in published research, please cite either one:
- Gu, Z. Complex Heatmap Visualization. iMeta 2022.
- Gu, Z. Complex heatmaps reveal patterns and correlations in multidimensional 
    genomic data. Bioinformatics 2016.


The new InteractiveComplexHeatmap package can directly export static 
complex heatmaps into an interactive Shiny app with zero effort. Have a try!

This message can be suppressed by:
  suppressPackageStartupMessages(library(ComplexHeatmap))
========================================

> library(GetoptLong)
> 
> 
> ha = HeatmapAnnotation(foo = 1:10)
> ha
A HeatmapAnnotation object with 1 annotation
  name: heatmap_annotation_0 
  position: column 
  items: 10 
  width: 1npc 
  height: 5mm 
  this object is subsettable
  6.75733333333333mm extension on the right 

 name   annotation_type color_mapping height
  foo continuous vector        random    5mm
> 
> 
> ha = HeatmapAnnotation(foo = cbind(1:10, 10:1))
> ha
A HeatmapAnnotation object with 1 annotation
  name: heatmap_annotation_1 
  position: column 
  items: 10 
  width: 1npc 
  height: 10mm 
  this object is subsettable
  6.75733333333333mm extension on the right 

 name   annotation_type color_mapping height
  foo continuous matrix        random   10mm
> draw(ha, test = "matrix as column annotation")
> 
> ha = HeatmapAnnotation(foo = 1:10, bar = sample(c("a", "b"), 10, replace = TRUE),
+ 	pt = anno_points(1:10), annotation_name_side = "left")
> draw(ha, test = "complex annotations")
> 
> ha = HeatmapAnnotation(foo = 1:10, bar = sample(c("a", "b"), 10, replace = TRUE),
+ 	pt = anno_points(1:10), annotation_name_side = "left", height = unit(8, "cm"))
> draw(ha, test = "complex annotations")
> 
> 
> ha = HeatmapAnnotation(foo = 1:10, bar = sample(c("a", "b"), 10, replace = TRUE))
> 
> ha = HeatmapAnnotation(foo = 1:10, 
+ 	bar = cbind(1:10, 10:1),
+ 	pt = anno_points(1:10),
+ 	gap = unit(2, "mm"))
> draw(ha, test = "complex annotations")
> 
> ha2 = re_size(ha, annotation_height = unit(1:3, "cm"))
> draw(ha2, test = "complex annotations")
> ha2 = re_size(ha, annotation_height = 1, height = unit(6, "cm"))
> draw(ha2, test = "complex annotations")
> ha2 = re_size(ha, annotation_height = 1:3, height = unit(6, "cm"))
> draw(ha2, test = "complex annotations")
> ha2 = re_size(ha, annotation_height = unit(c(1, 2, 3), c("null", "null", "cm")), height = unit(6, "cm"))
> draw(ha2, test = "complex annotations")
> ha2 = re_size(ha, annotation_height = unit(c(2, 2, 3), c("cm", "null", "cm")), height = unit(6, "cm"))
> draw(ha2, test = "complex annotations")
> ha2 = re_size(ha, annotation_height = unit(c(2, 2, 3), c("cm", "cm", "cm")))
> draw(ha2, test = "complex annotations")
> ha2 = re_size(ha[, 1:2], annotation_height = 1, height = unit(4, "cm"))
> draw(ha2, test = "complex annotations")
> ha2 = re_size(ha[, 1:2], annotation_height = c(1, 4), height = unit(4, "cm"))
> draw(ha2, test = "complex annotations")
> ha2 = re_size(ha[, 1:2], height = unit(6, "cm"))
> draw(ha2, test = "complex annotations")
> 
> ha2 = re_size(ha, height = unit(6, "cm"))
> draw(ha2, test = "complex annotations")
> 
> #### test anno_empty and self-defined anotation function
> ha = HeatmapAnnotation(foo = anno_empty(), height = unit(4, "cm"))
> draw(ha, 1:10, test = "anno_empty")
> ha = HeatmapAnnotation(foo = anno_empty(), bar = 1:10, height = unit(4, "cm"))
> draw(ha, 1:10, test = "anno_empty")
> ha = HeatmapAnnotation(foo = anno_empty(), bar = 1:10, height = unit(4, "cm"))
> draw(ha, 1:10, test = "anno_empty")
> 
> ha = HeatmapAnnotation(foo = function(index) {grid.rect()}, bar = 1:10, height = unit(4, "cm"))
> draw(ha, 1:10, test = "self-defined function")
> 
> 
> lt = lapply(1:10, function(x) cumprod(1 + runif(1000, -x/100, x/100)) - 1)
> ha = HeatmapAnnotation(foo = 1:10, bar = sample(c("a", "b"), 10, replace = TRUE),
+ 	anno = anno_horizon(lt), which = "row")
> draw(ha, test = "complex annotations on row")
> 
> ## test row annotation with no heatmap
> rowAnnotation(foo = 1:10, bar = anno_points(10:1))
A HeatmapAnnotation object with 2 annotations
  name: heatmap_annotation_11 
  position: row 
  items: 10 
  width: 15.3514598035146mm 
  height: 1npc 
  this object is subsettable
  9.17784444444445mm extension on the bottom 

 name   annotation_type color_mapping width
  foo continuous vector        random   5mm
  bar     anno_points()                10mm
> 
> if(0) {
+ HeatmapAnnotation(1:10)
+ 
+ HeatmapAnnotation(data.frame(1:10))
+ }
> 
> 
> ha = HeatmapAnnotation(summary = anno_summary(height = unit(4, "cm")))
> v = sample(letters[1:2], 50, replace = TRUE)
> split = sample(letters[1:2], 50, replace = TRUE)
> 
> ht = Heatmap(v, top_annotation = ha, width = unit(1, "cm"), split = split)
> draw(ht)
> 
> ha = HeatmapAnnotation(summary = anno_summary(gp = gpar(fill = 2:3), height = unit(4, "cm")))
> v = rnorm(50)
> ht = Heatmap(v, top_annotation = ha, width = unit(1, "cm"), split = split)
> draw(ht)
> 
> 
> ### auto adjust
> m = matrix(rnorm(100), 10)
> ht_list = Heatmap(m, top_annotation = HeatmapAnnotation(foo = 1:10), column_dend_height = unit(4, "cm")) +
+ 	Heatmap(m, top_annotation = HeatmapAnnotation(bar = anno_points(1:10)),
+ 		cluster_columns = FALSE)
> draw(ht_list)
> 
> fun = function(index) {
+ 	grid.rect()
+ }
> ha = HeatmapAnnotation(fun = fun, height = unit(4, "cm"))
> draw(ha, 1:10, test = TRUE)
> 
> ha = rowAnnotation(fun = fun, width = unit(4, "cm"))
> draw(ha, 1:10, test = TRUE)
> 
> 
> ## test anno_mark
> m = matrix(rnorm(1000), nrow = 100)
> ha1 = rowAnnotation(foo = anno_mark(at = c(1:4, 20, 60, 97:100), labels = month.name[1:10]))
> ht = Heatmap(m, name = "mat", cluster_rows = FALSE, right_annotation = ha1)
> draw(ht)
> ht = Heatmap(m, name = "mat", cluster_rows = FALSE) + ha1
> draw(ht)
> 
> split = rep("a", 100); split[c(1:4, 20, 60, 98:100)] = "b"
> ht = Heatmap(m, name = "mat", cluster_rows = FALSE, right_annotation = ha1, row_split = split, gap = unit(1, "cm"))
> draw(ht)
> ht = Heatmap(m, name = "mat", cluster_rows = FALSE, row_split = split, gap = unit(1, "cm")) + ha1
> draw(ht)
> 
> # ha has two annotations
> ha2 = rowAnnotation(foo = anno_mark(at = c(1:4, 20, 60, 97:100), labels = month.name[1:10]), bar = 1:100)
> ht = Heatmap(m, name = "mat", cluster_rows = FALSE, right_annotation = ha2)
> draw(ht)
> ht = Heatmap(m, name = "mat", cluster_rows = FALSE) + ha2
> draw(ht)
> 
> ht = Heatmap(m, name = "mat", cluster_rows = FALSE, right_annotation = ha2, row_split = split, gap = unit(1, "cm"))
> draw(ht)
> ht = Heatmap(m, name = "mat", cluster_rows = FALSE, row_split = split, gap = unit(1, "cm")) + ha2
> draw(ht)
> 
> ## test anno_mark as column annotation
> m = matrix(rnorm(1000), ncol = 100)
> ha1 = columnAnnotation(foo = anno_mark(at = c(1:4, 20, 60, 97:100), labels = month.name[1:10]))
> ht = Heatmap(m, name = "mat", cluster_columns = FALSE, top_annotation = ha1)
> draw(ht)
> ht_list = ha1 %v% Heatmap(m, name = "mat", cluster_columns = FALSE)
> draw(ht_list)
> 
> split = rep("a", 100); split[c(1:4, 20, 60, 98:100)] = "b"
> ht = Heatmap(m, name = "mat", cluster_columns = FALSE, top_annotation = ha1, column_split = split, column_gap = unit(1, "cm"))
> draw(ht)
> ht_list = ha1 %v% Heatmap(m, name = "mat", cluster_columns = FALSE, column_split = split, gap = unit(1, "cm"))
> draw(ht_list)
> 
> # ha has two annotations
> ha2 = HeatmapAnnotation(foo = anno_mark(at = c(1:4, 20, 60, 97:100), labels = month.name[1:10]), bar = 1:100)
> ht = Heatmap(m, name = "mat", cluster_columns = FALSE, top_annotation = ha2)
> draw(ht)
> ht_list = ha2 %v% Heatmap(m, name = "mat", cluster_columns = FALSE)
> draw(ht_list)
> 
> ht = Heatmap(m, name = "mat", cluster_columns = FALSE, top_annotation = ha2, column_split = split, column_gap = unit(1, "cm"))
> draw(ht)
> ht_list = ha2 %v% Heatmap(m, name = "mat", cluster_columns = FALSE, column_split = split, column_gap = unit(1, "cm"))
> draw(ht_list)
> 
> 
> ### when there are only simple annotations
> col_fun = colorRamp2(c(0, 10), c("white", "blue"))
> ha = HeatmapAnnotation(
+     foo = cbind(a = 1:10, b = 10:1), 
+     bar = sample(letters[1:3], 10, replace = TRUE),
+     col = list(foo = col_fun,
+                bar = c("a" = "red", "b" = "green", "c" = "blue")
+     ),
+     simple_anno_size = unit(1, "cm")
+ )
> draw(ha, test = TRUE)
> 
> set.seed(123)
> mat1 = matrix(rnorm(80, 2), 8, 10)
> mat1 = rbind(mat1, matrix(rnorm(40, -2), 4, 10))
> rownames(mat1) = paste0("R", 1:12)
> colnames(mat1) = paste0("C", 1:10)
> 
> mat2 = matrix(runif(60, max = 3, min = 1), 6, 10)
> mat2 = rbind(mat2, matrix(runif(60, max = 2, min = 0), 6, 10))
> rownames(mat2) = paste0("R", 1:12)
> colnames(mat2) = paste0("C", 1:10)
> 
> ind = sample(12, 12)
> mat1 = mat1[ind, ]
> mat2 = mat2[ind, ]
> 
> ha1 = HeatmapAnnotation(foo1 = 1:10, 
+ 	                    annotation_height = unit(1, "cm"),
+ 	                    simple_anno_size_adjust = TRUE,
+                         annotation_name_side = "left")
> ha2 = HeatmapAnnotation(df = data.frame(foo1 = 1:10,
+                                         foo2 = 1:10,
+                                         foo4 = 1:10,
+                                         foo5 = 1:10))
> ht1 = Heatmap(mat1, name = "rnorm", top_annotation = ha1)
> ht2 = Heatmap(mat2, name = "runif", top_annotation = ha2)
> 
> draw(ht1 + ht2)
> 
> ##### test size of a single simple annotation
> 
> ha = HeatmapAnnotation(foo1 = 1:10, 
+ 	simple_anno_size = unit(1, "cm")
+ )
> ha = HeatmapAnnotation(foo1 = 1:10, 
+ 	annotation_height = unit(1, "cm"),
+ 	simple_anno_size_adjust = TRUE
+ )
> ha = HeatmapAnnotation(foo1 = 1:10, 
+ 	height = unit(1, "cm"),
+ 	simple_anno_size_adjust = TRUE
+ )
> 
> 
> ## annotation with the same names
> 
> set.seed(123)
> m = matrix(rnorm(100), 10)
> ha1 = HeatmapAnnotation(foo = sample(c("a", "b"), 10, replace = TRUE))
> ha2 = HeatmapAnnotation(foo = sample(c("b", "c"), 10, replace = TRUE))
> 
> ht_list = Heatmap(m, top_annotation = ha1) + 
+ 	Heatmap(m, top_annotation = ha2)
> draw(ht_list)
> 
> ha1 = HeatmapAnnotation(foo = sample(c("a", "b"), 10, replace = TRUE),
+ 	annotation_legend_param = list(
+ 		foo = list(title = "letters", 
+ 			       at = c("a", "b", "c"),
+ 			       labels = c("A", "B", "C")
+ 			  )
+ 	))
> ha2 = HeatmapAnnotation(foo = sample(c("b", "c"), 10, replace = TRUE))
> 
> ht_list = Heatmap(m, top_annotation = ha1) + 
+ 	Heatmap(m, top_annotation = ha2)
> draw(ht_list)
> 
> x = matrix(rnorm(6), ncol=3)
> subtype_col = c("Basal" = "purple","Her2" = "black","Normal" = "blue")
> h1 <- HeatmapAnnotation("Subtype" = c("Basal","Her2", "Normal"),
+                         col = list("Subtype" = subtype_col))
> h2 <- HeatmapAnnotation("Subtype" = c("Normal","Normal", "Basal"),
+                         col = list("Subtype" = subtype_col))
> 
> ht_list = Heatmap(x,top_annotation = h1) + Heatmap(x,top_annotation = h2)
> draw(ht_list)
> 
> 
> ### test annotation_label
> ha = HeatmapAnnotation(foo = 1:10, bar = letters[1:10],
+ 	annotation_label = c("anno1", "anno2"))
> draw(ha, test = TRUE)
> 
> ha = HeatmapAnnotation(foo = 1:10, bar = letters[1:10],
+ 	annotation_label = list(foo = "anno1"))
> draw(ha, test = TRUE)
> 
> 
> ha = HeatmapAnnotation(foo = 1:10, bar = letters[1:10],
+ 	annotation_label = list(
+ 		foo = gt_render("foo", gp = gpar(box_fill = "red"))))
Loading required namespace: gridtext
> draw(ha, test = TRUE)
> 
> ha = HeatmapAnnotation(foo = 1:10, bar = letters[1:10],
+ 	annotation_label = list(
+ 		foo = gt_render("foo", gp = gpar(box_fill = "red")),
+ 		bar = gt_render("bar", gp = gpar(box_fill = "blue"))))
> draw(ha, test = TRUE)
> 
> 
> ### test whether arguments can be captured
> HeatmapAnnotation(a = 1:10)
A HeatmapAnnotation object with 1 annotation
  name: heatmap_annotation_38 
  position: column 
  items: 10 
  width: 1npc 
  height: 5mm 
  this object is subsettable
  3.35373333333333mm extension on the right 

 name   annotation_type color_mapping height
    a continuous vector        random    5mm
> rowAnnotation(a = 1:10)
A HeatmapAnnotation object with 1 annotation
  name: heatmap_annotation_39 
  position: row 
  items: 10 
  width: 5mm 
  height: 1npc 
  this object is subsettable
  3.35373333333333mm extension on the bottom 

 name   annotation_type color_mapping width
    a continuous vector        random   5mm
> columnAnnotation(a = 1:10)
A HeatmapAnnotation object with 1 annotation
  name: heatmap_annotation_40 
  position: column 
  items: 10 
  width: 1npc 
  height: 5mm 
  this object is subsettable
  3.35373333333333mm extension on the right 

 name   annotation_type color_mapping height
    a continuous vector        random    5mm
> do.call(HeatmapAnnotation, list(a = 1:10))
A HeatmapAnnotation object with 1 annotation
  name: heatmap_annotation_41 
  position: column 
  items: 10 
  width: 1npc 
  height: 5mm 
  this object is subsettable
  3.35373333333333mm extension on the right 

 name   annotation_type color_mapping height
    a continuous vector        random    5mm
> do.call(rowAnnotation, list(a = 1:10))
A HeatmapAnnotation object with 1 annotation
  name: heatmap_annotation_42 
  position: row 
  items: 10 
  width: 5mm 
  height: 1npc 
  this object is subsettable
  3.35373333333333mm extension on the bottom 

 name   annotation_type color_mapping width
    a continuous vector        random   5mm
> do.call(columnAnnotation, list(a = 1:10))
A HeatmapAnnotation object with 1 annotation
  name: heatmap_annotation_43 
  position: column 
  items: 10 
  width: 1npc 
  height: 5mm 
  this object is subsettable
  3.35373333333333mm extension on the right 

 name   annotation_type color_mapping height
    a continuous vector        random    5mm
> do.call("HeatmapAnnotation", list(a = 1:10))
A HeatmapAnnotation object with 1 annotation
  name: heatmap_annotation_44 
  position: column 
  items: 10 
  width: 1npc 
  height: 5mm 
  this object is subsettable
  3.35373333333333mm extension on the right 

 name   annotation_type color_mapping height
    a continuous vector        random    5mm
> do.call("rowAnnotation", list(a = 1:10))
A HeatmapAnnotation object with 1 annotation
  name: heatmap_annotation_45 
  position: row 
  items: 10 
  width: 5mm 
  height: 1npc 
  this object is subsettable
  3.35373333333333mm extension on the bottom 

 name   annotation_type color_mapping width
    a continuous vector        random   5mm
> do.call("columnAnnotation", list(a = 1:10))
A HeatmapAnnotation object with 1 annotation
  name: heatmap_annotation_46 
  position: column 
  items: 10 
  width: 1npc 
  height: 5mm 
  this object is subsettable
  3.35373333333333mm extension on the right 

 name   annotation_type color_mapping height
    a continuous vector        random    5mm
> 
> f = function() HeatmapAnnotation(a = 1:10)
> f()
A HeatmapAnnotation object with 1 annotation
  name: heatmap_annotation_47 
  position: column 
  items: 10 
  width: 1npc 
  height: 5mm 
  this object is subsettable
  3.35373333333333mm extension on the right 

 name   annotation_type color_mapping height
    a continuous vector        random    5mm
> f = function() rowAnnotation(a = 1:10)
> f()
A HeatmapAnnotation object with 1 annotation
  name: heatmap_annotation_48 
  position: row 
  items: 10 
  width: 5mm 
  height: 1npc 
  this object is subsettable
  3.35373333333333mm extension on the bottom 

 name   annotation_type color_mapping width
    a continuous vector        random   5mm
> f = function() columnAnnotation(a = 1:10)
> f()
A HeatmapAnnotation object with 1 annotation
  name: heatmap_annotation_49 
  position: column 
  items: 10 
  width: 1npc 
  height: 5mm 
  this object is subsettable
  3.35373333333333mm extension on the right 

 name   annotation_type color_mapping height
    a continuous vector        random    5mm
> 
> sapply(1, function(x) HeatmapAnnotation(a = 1:10))
[[1]]
A HeatmapAnnotation object with 1 annotation
  name: heatmap_annotation_50 
  position: column 
  items: 10 
  width: 1npc 
  height: 5mm 
  this object is subsettable
  3.35373333333333mm extension on the right 

 name   annotation_type color_mapping height
    a continuous vector        random    5mm

> sapply(1, function(x) rowAnnotation(a = 1:10))
[[1]]
A HeatmapAnnotation object with 1 annotation
  name: heatmap_annotation_51 
  position: row 
  items: 10 
  width: 5mm 
  height: 1npc 
  this object is subsettable
  3.35373333333333mm extension on the bottom 

 name   annotation_type color_mapping width
    a continuous vector        random   5mm

> sapply(1, function(x) columnAnnotation(a = 1:10))
[[1]]
A HeatmapAnnotation object with 1 annotation
  name: heatmap_annotation_52 
  position: column 
  items: 10 
  width: 1npc 
  height: 5mm 
  this object is subsettable
  3.35373333333333mm extension on the right 

 name   annotation_type color_mapping height
    a continuous vector        random    5mm

> 
> mapply(function(x, y) HeatmapAnnotation(a = 1:10), list(1), list(1))
[[1]]
A HeatmapAnnotation object with 1 annotation
  name: heatmap_annotation_53 
  position: column 
  items: 10 
  width: 1npc 
  height: 5mm 
  this object is subsettable
  3.35373333333333mm extension on the right 

 name   annotation_type color_mapping height
    a continuous vector        random    5mm

> mapply(function(x, y) rowAnnotation(a = 1:10), list(1), list(1))
[[1]]
A HeatmapAnnotation object with 1 annotation
  name: heatmap_annotation_54 
  position: row 
  items: 10 
  width: 5mm 
  height: 1npc 
  this object is subsettable
  3.35373333333333mm extension on the bottom 

 name   annotation_type color_mapping width
    a continuous vector        random   5mm

> mapply(function(x, y) columnAnnotation(a = 1:10), list(1), list(1))
[[1]]
A HeatmapAnnotation object with 1 annotation
  name: heatmap_annotation_55 
  position: column 
  items: 10 
  width: 1npc 
  height: 5mm 
  this object is subsettable
  3.35373333333333mm extension on the right 

 name   annotation_type color_mapping height
    a continuous vector        random    5mm

> 
> 
> try({
+ 	HeatmapAnnotation(1:10)
+ 	HeatmapAnnotation(df = data.frame(a = 1:10), a = 1:10)
+ })
Error : The annotation should be specified as name-value pairs or via argument
`df` with a data frame.
> 
> proc.time()
   user  system elapsed 
 27.850   0.754  30.740


R version 4.3.3 (2024-02-29) -- "Angel Food Cake"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin20 (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(circlize)
========================================
circlize version 0.4.16
CRAN page: https://cran.r-project.org/package=circlize
Github page: https://github.com/jokergoo/circlize
Documentation: https://jokergoo.github.io/circlize_book/book/

If you use it in published research, please cite:
Gu, Z. circlize implements and enhances circular visualization
  in R. Bioinformatics 2014.

This message can be suppressed by:
  suppressPackageStartupMessages(library(circlize))
========================================

> library(ComplexHeatmap)
Loading required package: grid
========================================
ComplexHeatmap version 2.18.0
Bioconductor page: http://bioconductor.org/packages/ComplexHeatmap/
Github page: https://github.com/jokergoo/ComplexHeatmap
Documentation: http://jokergoo.github.io/ComplexHeatmap-reference

If you use it in published research, please cite either one:
- Gu, Z. Complex Heatmap Visualization. iMeta 2022.
- Gu, Z. Complex heatmaps reveal patterns and correlations in multidimensional 
    genomic data. Bioinformatics 2016.


The new InteractiveComplexHeatmap package can directly export static 
complex heatmaps into an interactive Shiny app with zero effort. Have a try!

This message can be suppressed by:
  suppressPackageStartupMessages(library(ComplexHeatmap))
========================================

> library(GetoptLong)
> 
> set.seed(123)
> nr1 = 10; nr2 = 8; nr3 = 6
> nc1 = 6; nc2 = 8; nc3 = 10
> mat1 = cbind(rbind(matrix(rnorm(nr1*nc1, mean = 1,   sd = 0.5), nr = nr1),
+           matrix(rnorm(nr2*nc1, mean = 0,   sd = 0.5), nr = nr2),
+           matrix(rnorm(nr3*nc1, mean = 0,   sd = 0.5), nr = nr3)),
+     rbind(matrix(rnorm(nr1*nc2, mean = 0,   sd = 0.5), nr = nr1),
+           matrix(rnorm(nr2*nc2, mean = 1,   sd = 0.5), nr = nr2),
+           matrix(rnorm(nr3*nc2, mean = 0,   sd = 0.5), nr = nr3)),
+     rbind(matrix(rnorm(nr1*nc3, mean = 0.5, sd = 0.5), nr = nr1),
+           matrix(rnorm(nr2*nc3, mean = 0.5, sd = 0.5), nr = nr2),
+           matrix(rnorm(nr3*nc3, mean = 1,   sd = 0.5), nr = nr3))
+    )
> 
> rownames(mat1) = paste0("row_1_", seq_len(nrow(mat1)))
> colnames(mat1) = paste0("column_1_", seq_len(nrow(mat1)))
> 
> nr3 = 10; nr1 = 8; nr2 = 6
> nc3 = 6; nc1 = 8; nc2 = 10
> mat2 = cbind(rbind(matrix(rnorm(nr1*nc1, mean = 1,   sd = 0.5), nr = nr1),
+           matrix(rnorm(nr2*nc1, mean = 0,   sd = 0.5), nr = nr2),
+           matrix(rnorm(nr3*nc1, mean = 0,   sd = 0.5), nr = nr3)),
+     rbind(matrix(rnorm(nr1*nc2, mean = 0,   sd = 0.5), nr = nr1),
+           matrix(rnorm(nr2*nc2, mean = 1,   sd = 0.5), nr = nr2),
+           matrix(rnorm(nr3*nc2, mean = 0,   sd = 0.5), nr = nr3)),
+     rbind(matrix(rnorm(nr1*nc3, mean = 0.5, sd = 0.5), nr = nr1),
+           matrix(rnorm(nr2*nc3, mean = 0.5, sd = 0.5), nr = nr2),
+           matrix(rnorm(nr3*nc3, mean = 1,   sd = 0.5), nr = nr3))
+    )
> 
> rownames(mat2) = paste0("row_2_", seq_len(nrow(mat2)))
> colnames(mat2) = paste0("column_2_", seq_len(nrow(mat2)))
> 
> 
> ht_list = Heatmap(mat1) + Heatmap(mat2)
> draw(ht_list)
> 
> ######### legend ############
> draw(ht_list, heatmap_legend_side = "bottom")
> draw(ht_list, heatmap_legend_side = "left")
> draw(ht_list, heatmap_legend_side = "top")
> 
> 
> ########## width #############
> ht_list = Heatmap(mat1, width = unit(6, "cm")) + Heatmap(mat2)
> draw(ht_list)
> ht_list = Heatmap(mat1) + Heatmap(mat2, width = unit(8, "cm"))
> draw(ht_list)
> ht_list = Heatmap(mat1, width = unit(12, "cm")) + Heatmap(mat2, width = unit(8, "cm"))
> draw(ht_list)
> 
> ht_list = Heatmap(mat1, width = unit(6, "cm")) + Heatmap(mat2)
> draw(ht_list)
> ht_list = Heatmap(mat1) + Heatmap(mat2, width = unit(6, "cm"))
> draw(ht_list)
> ht_list = Heatmap(mat1, width = unit(6, "cm")) + Heatmap(mat2, width = unit(6, "cm"))
> draw(ht_list)
> ht_list = Heatmap(mat1, width = 4) + Heatmap(mat2)
> draw(ht_list)
> ht_list = Heatmap(mat1, width = 2) + Heatmap(mat2, width = 1)
> draw(ht_list)
> 
> 
> ########### height ###########
> ht_list = Heatmap(mat1, height = unit(6, "cm")) + Heatmap(mat2)
> draw(ht_list)
> ht_list = Heatmap(mat1, heatmap_height = unit(6, "cm")) + Heatmap(mat2)
> draw(ht_list)
> ht_list = Heatmap(mat1, width = unit(6, "cm"), height = unit(6, "cm")) + 
+ 	Heatmap(mat2, width = unit(6, "cm"), height = unit(6, "cm"))
> draw(ht_list, column_title = "foooooooooo", row_title = "baaaaaaaaaaar")
> 
> ##### split #####
> ht_list = Heatmap(mat1, name = "m1", row_km = 2) + Heatmap(mat2, name = "m2", row_km = 3)
> draw(ht_list, main_heatmap = "m1")
> draw(ht_list, main_heatmap = "m2")
> 
> ht_list = Heatmap(mat1, name = "m1", row_km = 2, column_km = 3, width = unit(8, "cm"), height = unit(6, "cm")) + 
+ 	Heatmap(mat2, name = "m2", row_km = 3, column_km = 2, width = unit(8, "cm"), height = unit(10, "cm"))
> draw(ht_list, main_heatmap = "m1", column_title = "foooooooooo", row_title = "baaaaaaaaaaar")
> draw(ht_list, main_heatmap = "m2", column_title = "foooooooooo", row_title = "baaaaaaaaaaar")
> 
> ##### adjust column annotations #####
> ha1 = HeatmapAnnotation(foo = 1:24, bar = anno_points(24:1, height = unit(4, "cm")))
> ha2 = HeatmapAnnotation(bar = anno_points(24:1), foo = 1:24)
> ht_list = Heatmap(mat1, top_annotation = ha1) + Heatmap(mat2, top_annotation = ha2)
> draw(ht_list)
> ha2 = HeatmapAnnotation(foo = 1:24)
> ht_list = Heatmap(mat1, top_annotation = ha1) + Heatmap(mat2, top_annotation = ha2)
> draw(ht_list)
> ht_list = Heatmap(mat1, top_annotation = ha1) + Heatmap(mat2)
> draw(ht_list)
> ht_list = Heatmap(mat1, bottom_annotation = ha1) + Heatmap(mat2)
> draw(ht_list)
> 
> 
> #### row annotations #####
> ha = rowAnnotation(foo = 1:24, bar = anno_points(24:1), width = unit(6, "cm"))
> ht_list = Heatmap(mat1) + ha
> draw(ht_list)
> ht_list = Heatmap(mat1, width = unit(6, "cm")) + ha
> draw(ht_list)
> ht_list = Heatmap(mat1, width = unit(6, "cm"), row_km = 2) + ha
> draw(ht_list)
> 
> ht_list = Heatmap(matrix(rnorm(100), 10), name = "rnorm") +
+   rowAnnotation(foo = 1:10, bar = anno_points(10:1)) + 
+   Heatmap(matrix(runif(100), 10), name = "runif")
> summary(ht_list[1:5, ])
A horizontal heamtap list with 3 heatmap/annotations.
  rnorm: a matrix with 5 rows and 10 columns
  heatmap_annotation_4: a list of 2 annotations
    foo:   a simple annotation.
    bar:   a complex annotation.
  runif: a matrix with 5 rows and 10 columns
> summary(ht_list[1:5, 1])
A horizontal heamtap list with 1 heatmap/annotations.
  rnorm: a matrix with 5 rows and 10 columns
> summary(ht_list[1:5, "rnorm"])
A horizontal heamtap list with 1 heatmap/annotations.
  rnorm: a matrix with 5 rows and 10 columns
> summary(ht_list[1:5, c("rnorm", "foo")])
A horizontal heamtap list with 2 heatmap/annotations.
  rnorm: a matrix with 5 rows and 10 columns
  heatmap_annotation_4: a list of 1 annotations
    foo:   a simple annotation.
> 
> ht_list = Heatmap(matrix(rnorm(100), 10), name = "rnorm") %v%
+   columnAnnotation(foo = 1:10, bar = anno_points(10:1)) %v%
+   Heatmap(matrix(runif(100), 10), name = "runif")
> summary(ht_list[, 1:5])
A vertical heamtap list with 3 heatmap/annotations.
  rnorm: a matrix with 10 rows and 5 columns
  heatmap_annotation_5: a list of 2 annotations
    foo:   a simple annotation.
    bar:   a complex annotation.
  runif: a matrix with 10 rows and 5 columns
> summary(ht_list[1, 1:5])
A vertical heamtap list with 1 heatmap/annotations.
  rnorm: a matrix with 10 rows and 5 columns
> summary(ht_list["rnorm", 1:5])
A vertical heamtap list with 1 heatmap/annotations.
  rnorm: a matrix with 10 rows and 5 columns
> summary(ht_list[c("rnorm", "foo"), 1:5])
A vertical heamtap list with 2 heatmap/annotations.
  rnorm: a matrix with 10 rows and 5 columns
  heatmap_annotation_5: a list of 1 annotations
    foo:   a simple annotation.
> 
> 
> 
> 
> proc.time()
   user  system elapsed 
 33.538   0.673  35.561


R version 4.3.3 (2024-02-29) -- "Angel Food Cake"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin20 (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> 
> if(0) {
+ 
+ m = matrix(rnorm(100), 10)
+ rownames(m) = 1:10
+ colnames(m) = 1:10
+ 
+ ht = Heatmap(m)
+ ht = draw(ht)
+ selectArea(ht)
+ 
+ 
+ 
+ ht = Heatmap(m, row_km = 2, column_km = 2)
+ ht = draw(ht)
+ selectArea(ht)
+ 
+ 
+ ht = Heatmap(m, row_km = 2, column_km = 2) + Heatmap(m, row_km = 2, column_km = 2)
+ ht = draw(ht)
+ selectArea(ht)
+ 
+ pdf("~/test.pdf")
+ ht = Heatmap(m)
+ ht = draw(ht)
+ selectArea(ht, pos1 = unit(c(1, 1), "cm"), pos2 = unit(c(4, 4), "cm"), verbose = TRUE)
+ 
+ set.seed(123)
+ ht = Heatmap(m, row_km = 2, column_km = 2)
+ ht = draw(ht)
+ selectArea(ht, pos1 = unit(c(1, 1), "cm"), pos2 = unit(c(8, 8), "cm"), verbose = TRUE)
+ dev.off()
+ 
+ png("~/test-1.png")
+ ht = Heatmap(m)
+ ht = draw(ht)
+ selectArea(ht, pos1 = unit(c(1, 1), "cm"), pos2 = unit(c(4, 4), "cm"), verbose = TRUE)
+ dev.off()
+ 
+ png("~/test-2.png")
+ set.seed(123)
+ ht = Heatmap(m, row_km = 2, column_km = 2)
+ ht = draw(ht)
+ selectArea(ht, pos1 = unit(c(1, 1), "cm"), pos2 = unit(c(8, 8), "cm"), verbose = TRUE)
+ dev.off()
+ 
+ }
> 
> proc.time()
   user  system elapsed 
  0.352   0.112   0.432


R version 4.3.3 (2024-02-29) -- "Angel Food Cake"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin20 (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(circlize)
========================================
circlize version 0.4.16
CRAN page: https://cran.r-project.org/package=circlize
Github page: https://github.com/jokergoo/circlize
Documentation: https://jokergoo.github.io/circlize_book/book/

If you use it in published research, please cite:
Gu, Z. circlize implements and enhances circular visualization
  in R. Bioinformatics 2014.

This message can be suppressed by:
  suppressPackageStartupMessages(library(circlize))
========================================

> library(ComplexHeatmap)
Loading required package: grid
========================================
ComplexHeatmap version 2.18.0
Bioconductor page: http://bioconductor.org/packages/ComplexHeatmap/
Github page: https://github.com/jokergoo/ComplexHeatmap
Documentation: http://jokergoo.github.io/ComplexHeatmap-reference

If you use it in published research, please cite either one:
- Gu, Z. Complex Heatmap Visualization. iMeta 2022.
- Gu, Z. Complex heatmaps reveal patterns and correlations in multidimensional 
    genomic data. Bioinformatics 2016.


The new InteractiveComplexHeatmap package can directly export static 
complex heatmaps into an interactive Shiny app with zero effort. Have a try!

This message can be suppressed by:
  suppressPackageStartupMessages(library(ComplexHeatmap))
========================================

> library(GetoptLong)
> 
> if(!exists("random_str")) {
+ 	random_str = ComplexHeatmap:::random_str
+ }
> 
> lgd = Legend(at = 1:6, legend_gp = gpar(fill = 1:6))
> draw(lgd, test = "default discrete legends style")
> 
> lgd = Legend(labels = 1:6, legend_gp = gpar(fill = 1:6))
> draw(lgd, test = "only specify labels with no at")
> 
> 
> lgd = Legend(labels = month.name[1:6], title = "foo", legend_gp = gpar(fill = 1:6))
> draw(lgd, test = "add labels and title")
> 
> lgd = Legend(labels = month.name[1:6], title = "foo", legend_gp = gpar(fill = 1:6),
+ 	title_position = "lefttop")
> draw(lgd, test = "title put in the lefttop")
> 
> lgd = Legend(labels = month.name[1:6], title = "foo", legend_gp = gpar(fill = 1:6),
+ 	title_position = "lefttop-rot")
> draw(lgd, test = "title put in the lefttop-rot")
> 
> lgd = Legend(labels = month.name[1:6], title = "foo", legend_gp = gpar(fill = 1:6),
+ 	title_position = "leftcenter-rot")
> draw(lgd, test = "title put in the leftcenter-rot")
> 
> lgd = Legend(labels = 1:6, title = "fooooooo", legend_gp = gpar(fill = 1:6))
> draw(lgd, test = "title is longer than the legend body")
> 
> lgd = Legend(at = 1:6, legend_gp = gpar(fill = 1:6), grid_height = unit(1, "cm"), 
+ 	title = "foo", grid_width = unit(5, "mm"))
> draw(lgd, test = "grid size")
> 
> lgd = Legend(labels = month.name[1:6], legend_gp = gpar(fill = 1:6), title = "foo", 
+ 	labels_gp = gpar(col = "red", fontsize = 14))
> draw(lgd, test = "labels_gp")
> 
> lgd = Legend(labels = month.name[1:6], legend_gp = gpar(fill = 1:6), title = "foo", 
+ 	title_gp = gpar(col = "red", fontsize = 14))
> draw(lgd, test = "title_gp")
> 
> lgd = Legend(labels = month.name[1:6], legend_gp = gpar(fill = 1:6), title = "foo", 
+ 	border = "red")
> draw(lgd, test = "legend border")
> 
> lgd = Legend(labels = month.name[1:10], legend_gp = gpar(fill = 1:10), title = "foo", 
+ 	ncol = 3)
> draw(lgd, test = "in 3 columns")
> 
> lgd = Legend(labels = month.name[1:10], legend_gp = gpar(fill = 1:10), title = "foo", 
+ 	ncol = 3, title_position = "topcenter")
> draw(lgd, test = "in 3 columns, title in the center")
> 
> lgd = Legend(labels = month.name[1:10], legend_gp = gpar(fill = 1:10), title = "foo", 
+ 	ncol = 3, by_row = TRUE)
> draw(lgd, test = "in 3 columns and by rows")
> 
> lgd = Legend(labels = month.name[1:10], legend_gp = gpar(fill = 1:10), title = "foo", 
+ 	ncol = 3, gap = unit(1, "cm"))
> draw(lgd, test = "in 3 columns with gap between columns")
> 
> lgd = Legend(labels = month.name[1:10], legend_gp = gpar(fill = 1:10), title = "foo", 
+ 	nrow = 3)
> draw(lgd, test = "in 3 rows")
> 
> lgd = Legend(labels = month.name[1:6], legend_gp = gpar(fill = 1:6), title = "foooooo", 
+ 	nrow = 1, title_position = "lefttop")
> draw(lgd, test = "1 row and title is on the left")
> 
> lgd = Legend(labels = month.name[1:6], legend_gp = gpar(fill = 1:6), title = "foooooo", 
+ 	nrow = 1, title_position = "lefttop-rot")
> draw(lgd, test = "1 row and title is on the left, 90 rotation")
> 
> lgd = Legend(labels = month.name[1:6], legend_gp = gpar(fill = 1:6), title = "foooooo", 
+ 	nrow = 1, title_position = "leftcenter")
> draw(lgd, test = "1 row and title is on the left, 90 rotation")
> 
> lgd = Legend(labels = month.name[1:6], title = "foo", type = "points", pch = 1:6, 
+ 	legend_gp = gpar(col = 1:6), background = "red")
> draw(lgd, test = "points as legends")
> 
> lgd = Legend(labels = month.name[1:6], title = "foo", type = "points", pch = letters[1:6], 
+ 	legend_gp = gpar(col = 1:6), background = "white")
> draw(lgd, test = "letters as legends")
> 
> lgd = Legend(labels = month.name[1:6], title = "foo", type = "lines", 
+ 	legend_gp = gpar(col = 1:6, lty = 1:6))
> draw(lgd, test = "lines as legends")
> 
> ###### vertical continous legend #######
> col_fun = colorRamp2(c(0, 0.5, 1), c("blue", "white", "red"))
> lgd = Legend(col_fun = col_fun, title = "foo")
> draw(lgd, test = "only col_fun")
> 
> lgd = Legend(col_fun = col_fun, title = "foo", at = c(0, 0.25, 0.5, 0.75, 1))
> draw(lgd, test = "with at")
> 
> lgd = Legend(col_fun = col_fun, title = "foo", at = rev(c(0, 0.25, 0.5, 0.75, 1)))
> draw(lgd, test = "with at")
> 
> 
> lgd = Legend(col_fun = col_fun, title = "foo", at = c(0, 0.5, 1), labels = c("low", "median", "high"))
> draw(lgd, test = "with labels")
> 
> lgd = Legend(col_fun = col_fun, title = "foo", legend_height = unit(6, "cm"))
> draw(lgd, test = "set legend_height")
> 
> lgd = Legend(col_fun = col_fun, title = "foo", labels_gp = gpar(col = "red"))
> draw(lgd, test = "set label color")
> 
> lgd = Legend(col_fun = col_fun, title = "foo", border = "red")
> draw(lgd, test = "legend border")
> 
> lgd = Legend(col_fun = col_fun, title = "foooooooo", title_position = "lefttop-rot")
> draw(lgd, test = "lefttop rot title")
> 
> lgd = Legend(col_fun = col_fun, title = "foooooooo", title_position = "leftcenter-rot")
> draw(lgd, test = "leftcenter top title")
> 
> 
> lgd = Legend(col_fun = col_fun, title = "foo", title_position = "lefttop", direction = "horizontal")
> draw(lgd, test = "lefttop title")
> 
> ###### horizontal continous legend #######
> col_fun = colorRamp2(c(0, 0.5, 1), c("blue", "white", "red"))
> lgd = Legend(col_fun = col_fun, title = "foo", direction = "horizontal")
> draw(lgd, test = "only col_fun")
> 
> lgd = Legend(col_fun = col_fun, title = "foo", at = c(0, 0.25, 0.5, 0.75, 1), direction = "horizontal")
> draw(lgd, test = "with at")
> 
> lgd = Legend(col_fun = col_fun, title = "foo", at = rev(c(0, 0.25, 0.5, 0.75, 1)), direction = "horizontal")
> draw(lgd, test = "with at")
> 
> lgd = Legend(col_fun = col_fun, title = "foo", at = c(0, 0.5, 1), labels = c("low", "median", "high"),
+ 	direction = "horizontal")
> draw(lgd, test = "with labels")
> 
> lgd = Legend(col_fun = col_fun, title = "foo", legend_width = unit(6, "cm"), direction = "horizontal")
> draw(lgd, test = "set legend_width")
> 
> lgd = Legend(col_fun = col_fun, title = "foo", labels_gp = gpar(col = "red"), direction = "horizontal")
> draw(lgd, test = "set label color")
> 
> lgd = Legend(col_fun = col_fun, title = "foo", border = "red", direction = "horizontal")
> draw(lgd, test = "legend border")
> 
> lgd = Legend(col_fun = col_fun, title = "foooooooo", direction = "horizontal", 
+ 	title_position = "topcenter")
> draw(lgd, test = "topcenter title")
> 
> lgd = Legend(col_fun = col_fun, title = "foooooooo", direction = "horizontal", 
+ 	title_position = "lefttop")
> draw(lgd, test = "lefttop title")
> 
> lgd = Legend(col_fun = col_fun, title = "foooooooo", direction = "horizontal", 
+ 	title_position = "leftcenter")
> draw(lgd, test = "leftcenter title")
> 
> 
> ###### pack legend
> lgd1 = Legend(at = 1:6, legend_gp = gpar(fill = 1:6), title = "legend1")
> lgd2 = Legend(col_fun = col_fun, title = "legend2", at = c(0, 0.25, 0.5, 0.75, 1))
> 
> pd = packLegend(lgd1, lgd2)
> draw(pd, test = "two legends")
> 
> pd = packLegend(list = list(lgd1, lgd2))
> draw(pd, test = "two legends specified as a list")
> 
> pd = packLegend(lgd1, lgd2, direction = "horizontal")
> draw(pd, test = "two legends packed horizontally")
> 
> lgd3 = Legend(at = 1:6, legend_gp = gpar(fill = 1:6), title = "legend1")
> lgd4 = Legend(col_fun = col_fun, title = "legend2", at = c(0, 0.25, 0.5, 0.75, 1), direction = "horizontal")
> pd = packLegend(lgd3, lgd4)
> draw(pd, test = "two legends with different directions")
> pd = packLegend(lgd3, lgd4, direction = "horizontal")
> draw(pd, test = "two legends with different directions")
> 
> pd = packLegend(lgd1, lgd2, lgd1, lgd2)
> draw(pd, test = "many legends with same legends")
> 
> lgd3 = Legend(at = 1:6, legend_gp = gpar(fill = 1:6), title = "legend1")
> lgd4 = Legend(col_fun = col_fun, title = "legend2", at = c(0, 0.25, 0.5, 0.75, 1))
> pd = packLegend(lgd1, lgd2, lgd3, lgd4)
> draw(pd, test = "many legends with all different legends")
> 
> pd = packLegend(lgd1, lgd2, lgd1, lgd2, lgd1, lgd2)
> draw(pd, test = "many legends")
> 
> pd = packLegend(lgd1, lgd2, lgd1, lgd2, lgd1, lgd2, max_height = unit(1, "npc"))
> draw(pd, test = "many legends, max_height = unit(1, 'npc')")
> ## reduce the height of the interactive window and rerun draw()
> 
> pd = packLegend(lgd1, lgd2, lgd1, lgd2, lgd1, lgd2, max_height = unit(10, "cm"))
> draw(pd, test = "many legends, max_height = unit(10, 'cm')")
> 
> pd = packLegend(lgd1, lgd2, lgd1, lgd2, lgd1, lgd2, max_height = unit(10, "cm"), gap = unit(1, "cm"))
> draw(pd, test = "many legends, max_height = unit(10, 'cm'), with gap")
> 
> lgd_long = Legend(at = 1:50, legend_gp = gpar(fill = 1:50))
> pd = packLegend(lgd1, lgd2, lgd1, lgd2, lgd1, lgd2, lgd_long, max_height = unit(10, "cm"))
> draw(pd, test = "many legends with a long one, max_height = unit(10, 'cm')")
> 
> lgd1 = Legend(at = 1:6, legend_gp = gpar(fill = 1:6), title = "legend1",
+ 	nr = 1)
> lgd2 = Legend(col_fun = col_fun, title = "legend2", at = c(0, 0.25, 0.5, 0.75, 1),
+ 	direction = "horizontal")
> pd = packLegend(lgd1, lgd2, lgd1, lgd2, lgd1, lgd2, direction = "horizontal")
> draw(pd, test = "many legends")
> 
> pd = packLegend(lgd1, lgd2, lgd1, lgd2, lgd1, lgd2, max_width = unit(1, "npc"), direction = "horizontal")
> draw(pd, test = "many legends, max_width = unit(1, 'npc')")
> ## reduce the height of the interactive window and rerun draw()
> 
> pd = packLegend(lgd1, lgd2, lgd1, lgd2, lgd1, lgd2, max_width = unit(10, "cm"), direction = "horizontal")
> draw(pd, test = "many legends, max_width = unit(10, 'cm')")
> 
> 
> ####### unequal interval breaks
> col_fun = colorRamp2(c(0, 0.5, 1), c("blue", "white", "red"))
> lgd = Legend(col_fun = col_fun, title = "foo", at = c(0, 0.1, 0.15, 0.5, 0.9, 0.95, 1))
> draw(lgd, test = "unequal interval breaks")
> lgd = Legend(col_fun = col_fun, title = "foo", at = c(0, 0.3, 1), legend_height = unit(4, "cm"))
> draw(lgd, test = "unequal interval breaks but not label position adjustment")
> 
> lgd = Legend(col_fun = col_fun, title = "foo", at = c(0, 0.1, 0.15, 0.5, 0.9, 0.95, 1),
+ 	direction = "horizontal")
> draw(lgd, test = "unequal interval breaks")
> 
> lgd = Legend(col_fun = col_fun, title = "foo", at = c(0, 0.1, 0.15, 0.5, 0.9, 0.95, 1),
+ 	direction = "horizontal", title_position = "lefttop")
> draw(lgd, test = "unequal interval breaks")
> 
> 
> lgd = Legend(col_fun = col_fun, title = "foo", at = c(0, 0.1, 0.15, 0.5, 0.9, 0.95, 1),
+ 	direction = "horizontal", title_position = "lefttop", labels_rot = 90)
> draw(lgd, test = "unequal interval breaks, label rot 90")
> 
> lgd = Legend(col_fun = col_fun, title = "foo", at = c(0, 0.1, 0.5, 0.75, 1),
+ 	labels = c("mininal", "q10", "median", "q75", "maximal"),
+ 	direction = "horizontal", title_position = "lefttop")
> draw(lgd, test = "unequal interval breaks with labels")
> 
> 
> lgd = Legend(col_fun = col_fun, title = "foo", at = c(0, 0.1, 0.5, 0.75, 1),
+ 	labels = c("mininal", "q10", "median", "q75", "maximal"),
+ 	direction = "horizontal")
> draw(lgd, test = "unequal interval breaks with labels")
> 
> 
> col_fun = colorRamp2(c(0, 0.05, 0.1, 0.5, 1), c("green", "white", "red", "black", "blue"))
> lgd = Legend(col_fun = col_fun, title = "foo", break_dist = 1:4)
> draw(lgd, test = "unequal interval breaks")
> 
> 
> #### position of legends to heatmaps ##
> if(0) {
+ m = matrix(rnorm(100), 10)
+ rownames(m) = random_str(10, len = 20)
+ colnames(m) = random_str(10, len = 20)
+ Heatmap(m)
+ }
> 
> 
> 
> proc.time()
   user  system elapsed 
  7.832   0.458   9.361


R version 4.3.3 (2024-02-29) -- "Angel Food Cake"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin20 (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(circlize)
========================================
circlize version 0.4.16
CRAN page: https://cran.r-project.org/package=circlize
Github page: https://github.com/jokergoo/circlize
Documentation: https://jokergoo.github.io/circlize_book/book/

If you use it in published research, please cite:
Gu, Z. circlize implements and enhances circular visualization
  in R. Bioinformatics 2014.

This message can be suppressed by:
  suppressPackageStartupMessages(library(circlize))
========================================

> library(ComplexHeatmap)
Loading required package: grid
========================================
ComplexHeatmap version 2.18.0
Bioconductor page: http://bioconductor.org/packages/ComplexHeatmap/
Github page: https://github.com/jokergoo/ComplexHeatmap
Documentation: http://jokergoo.github.io/ComplexHeatmap-reference

If you use it in published research, please cite either one:
- Gu, Z. Complex Heatmap Visualization. iMeta 2022.
- Gu, Z. Complex heatmaps reveal patterns and correlations in multidimensional 
    genomic data. Bioinformatics 2016.


The new InteractiveComplexHeatmap package can directly export static 
complex heatmaps into an interactive Shiny app with zero effort. Have a try!

This message can be suppressed by:
  suppressPackageStartupMessages(library(ComplexHeatmap))
========================================

> library(GetoptLong)
> 
> m = matrix(rnorm(100), 10)
> 
> postscript("test.ps")
> lgd = Legend(labels = c("a", "b", "c"))
> draw(Heatmap(m), heatmap_legend_list = list(lgd))
> dev.off()
null device 
          1 
> 
> check_pages = function() {
+ 	lines = readLines("test.ps")
+ 	print(lines[length(lines)-1])
+ 	invisible(file.remove("test.ps"))
+ }
> 
> check_pages()
[1] "%%Pages: 1"
> 
> postscript("test.ps")
> ha = HeatmapAnnotation(foo = 1:10, bar = anno_points(1:10))
> Heatmap(m, top_annotation = ha)
> dev.off()
null device 
          1 
> 
> check_pages()
[1] "%%Pages: 1"
> 
> proc.time()
   user  system elapsed 
 13.316   0.427  13.876


R version 4.3.3 (2024-02-29) -- "Angel Food Cake"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin20 (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(circlize)
========================================
circlize version 0.4.16
CRAN page: https://cran.r-project.org/package=circlize
Github page: https://github.com/jokergoo/circlize
Documentation: https://jokergoo.github.io/circlize_book/book/

If you use it in published research, please cite:
Gu, Z. circlize implements and enhances circular visualization
  in R. Bioinformatics 2014.

This message can be suppressed by:
  suppressPackageStartupMessages(library(circlize))
========================================

> library(ComplexHeatmap)
Loading required package: grid
========================================
ComplexHeatmap version 2.18.0
Bioconductor page: http://bioconductor.org/packages/ComplexHeatmap/
Github page: https://github.com/jokergoo/ComplexHeatmap
Documentation: http://jokergoo.github.io/ComplexHeatmap-reference

If you use it in published research, please cite either one:
- Gu, Z. Complex Heatmap Visualization. iMeta 2022.
- Gu, Z. Complex heatmaps reveal patterns and correlations in multidimensional 
    genomic data. Bioinformatics 2016.


The new InteractiveComplexHeatmap package can directly export static 
complex heatmaps into an interactive Shiny app with zero effort. Have a try!

This message can be suppressed by:
  suppressPackageStartupMessages(library(ComplexHeatmap))
========================================

> library(GetoptLong)
> 
> mat = read.table(textConnection(
+ "s1,s2,s3
+ g1,snv;indel,snv,indel
+ g2,,snv;indel,snv
+ g3,snv,,indel;snv"), row.names = 1, header = TRUE, sep = ",", stringsAsFactors = FALSE)
> mat = as.matrix(mat)
> 
> get_type_fun = function(x) strsplit(x, ";")[[1]]
> 
> alter_fun = list(
+     snv = function(x, y, w, h) grid.rect(x, y, w*0.9, h*0.9, 
+         gp = gpar(fill = col["snv"], col = NA)),
+     indel = function(x, y, w, h) grid.rect(x, y, w*0.9, h*0.4, 
+         gp = gpar(fill = col["indel"], col = NA))
+ )
> 
> col = c(snv = "red", indel = "blue")
> ht = oncoPrint(mat, get_type = get_type_fun,
+     alter_fun = alter_fun, col = col)
All mutation types: snv, indel.
`alter_fun` is assumed vectorizable. If it does not generate correct
plot, please set `alter_fun_is_vectorized = FALSE` in `oncoPrint()`.
> draw(ht)
> 
> ## turn off row names while turn on column names
> ht = oncoPrint(mat, get_type = get_type_fun,
+     alter_fun = alter_fun, col = col, 
+     show_column_names = TRUE, show_row_names = FALSE, show_pct = FALSE)
All mutation types: snv, indel.
`alter_fun` is assumed vectorizable. If it does not generate correct
plot, please set `alter_fun_is_vectorized = FALSE` in `oncoPrint()`.
> draw(ht)
> 
> ht = oncoPrint(mat, get_type = get_type_fun,
+     alter_fun = alter_fun, col = col, pct_side = "right", 
+     row_names_side = "left")
All mutation types: snv, indel.
`alter_fun` is assumed vectorizable. If it does not generate correct
plot, please set `alter_fun_is_vectorized = FALSE` in `oncoPrint()`.
> draw(ht)
> 
> ht = oncoPrint(mat, get_type = get_type_fun,
+     alter_fun = alter_fun, col = col,
+     top_annotation = HeatmapAnnotation(column_barplot = anno_oncoprint_barplot())
+ )
All mutation types: snv, indel.
`alter_fun` is assumed vectorizable. If it does not generate correct
plot, please set `alter_fun_is_vectorized = FALSE` in `oncoPrint()`.
> draw(ht)
> 
> ht = oncoPrint(mat, get_type = get_type_fun,
+     alter_fun = alter_fun, col = col,
+     top_annotation = HeatmapAnnotation(
+     	column_barplot = anno_oncoprint_barplot(),
+     	foo = 1:3,
+     	annotation_name_side = "left")
+ )
All mutation types: snv, indel.
`alter_fun` is assumed vectorizable. If it does not generate correct
plot, please set `alter_fun_is_vectorized = FALSE` in `oncoPrint()`.
> draw(ht)
> 
> ht = oncoPrint(mat, get_type = get_type_fun,
+     alter_fun = alter_fun, col = col,
+     top_annotation = HeatmapAnnotation(
+     	cbar = anno_oncoprint_barplot(),
+     	foo1 = 1:3,
+     	annotation_name_side = "left"),
+     left_annotation = rowAnnotation(foo2 = 1:3),
+     right_annotation = rowAnnotation(cbar = anno_oncoprint_barplot(), foo3 = 1:3),
+ )
All mutation types: snv, indel.
`alter_fun` is assumed vectorizable. If it does not generate correct
plot, please set `alter_fun_is_vectorized = FALSE` in `oncoPrint()`.
> draw(ht)
> 
> 
> ht = oncoPrint(mat, get_type = get_type_fun,
+     alter_fun = alter_fun, col = col,
+     top_annotation = HeatmapAnnotation(
+         cbar = anno_oncoprint_barplot(border = TRUE),
+         foo1 = 1:3,
+         annotation_name_side = "left"),
+     left_annotation = rowAnnotation(foo2 = 1:3),
+     right_annotation = rowAnnotation(
+         cbar = anno_oncoprint_barplot(border = TRUE), 
+         foo3 = 1:3),
+ )
All mutation types: snv, indel.
`alter_fun` is assumed vectorizable. If it does not generate correct
plot, please set `alter_fun_is_vectorized = FALSE` in `oncoPrint()`.
> draw(ht)
> 
> ht = oncoPrint(mat, get_type = get_type_fun,
+     alter_fun = alter_fun, col = col,
+     right_annotation = rowAnnotation(rbar = anno_oncoprint_barplot(axis_param = list(side = "bottom", labels_rot = 90)))
+ )
All mutation types: snv, indel.
`alter_fun` is assumed vectorizable. If it does not generate correct
plot, please set `alter_fun_is_vectorized = FALSE` in `oncoPrint()`.
> draw(ht)
> 
> 
> proc.time()
   user  system elapsed 
 17.091   0.541  18.233


R version 4.3.3 (2024-02-29) -- "Angel Food Cake"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin20 (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(ComplexHeatmap)
Loading required package: grid
========================================
ComplexHeatmap version 2.18.0
Bioconductor page: http://bioconductor.org/packages/ComplexHeatmap/
Github page: https://github.com/jokergoo/ComplexHeatmap
Documentation: http://jokergoo.github.io/ComplexHeatmap-reference

If you use it in published research, please cite either one:
- Gu, Z. Complex Heatmap Visualization. iMeta 2022.
- Gu, Z. Complex heatmaps reveal patterns and correlations in multidimensional 
    genomic data. Bioinformatics 2016.


The new InteractiveComplexHeatmap package can directly export static 
complex heatmaps into an interactive Shiny app with zero effort. Have a try!

This message can be suppressed by:
  suppressPackageStartupMessages(library(ComplexHeatmap))
========================================

> 
> if(requireNamespace("pheatmap")) {
+ 	mat = matrix(rnorm(100), 10)
+ 
+ 	compare_pheatmap(mat)
+ 
+ 	pheatmap(mat)
+ 	pheatmap(mat, col = rev(RColorBrewer::brewer.pal(n = 7, name = "RdYlBu")))
+ 
+ 	test = matrix(rnorm(200), 20, 10)
+ 	test[1:10, seq(1, 10, 2)] = test[1:10, seq(1, 10, 2)] + 3
+ 	test[11:20, seq(2, 10, 2)] = test[11:20, seq(2, 10, 2)] + 2
+ 	test[15:20, seq(2, 10, 2)] = test[15:20, seq(2, 10, 2)] + 4
+ 	colnames(test) = paste("Test", 1:10, sep = "")
+ 	rownames(test) = paste("Gene", 1:20, sep = "")
+ 
+ 	# Draw heatmaps
+ 	compare_pheatmap(test)
+ 	compare_pheatmap(test, kmeans_k = 2)
+ 	compare_pheatmap(test, scale = "row", clustering_distance_rows = "correlation")
+ 	compare_pheatmap(test, color = colorRampPalette(c("navy", "white", "firebrick3"))(50))
+ 	compare_pheatmap(test, cluster_row = FALSE)
+ 	compare_pheatmap(test, legend = FALSE)
+ 
+ 	# Show text within cells
+ 	compare_pheatmap(test, display_numbers = TRUE)
+ 	compare_pheatmap(test, display_numbers = TRUE, number_format = "%.1e")
+ 	compare_pheatmap(test, display_numbers = matrix(ifelse(test > 5, "*", ""), nrow(test)))
+ 	compare_pheatmap(test, cluster_row = FALSE, legend_breaks = -1:4, legend_labels = c("0",
+ 		"1e-4", "1e-3", "1e-2", "1e-1", "1"))
+ 
+ 	# Fix cell sizes and save to file with correct size
+ 	compare_pheatmap(test, cellwidth = 15, cellheight = 12, main = "Example heatmap")
+ 
+ 	# Generate annotations for rows and columns
+ 	annotation_col = data.frame(
+ 	    CellType = factor(rep(c("CT1", "CT2"), 5)), 
+ 	    Time = 1:5
+ 	)
+ 	rownames(annotation_col) = paste("Test", 1:10, sep = "")
+ 
+ 	annotation_row = data.frame(
+ 	    GeneClass = factor(rep(c("Path1", "Path2", "Path3"), c(10, 4, 6)))
+ 	)
+ 	rownames(annotation_row) = paste("Gene", 1:20, sep = "")
+ 
+ 	# Display row and color annotations
+ 	compare_pheatmap(test, annotation_col = annotation_col)
+ 	compare_pheatmap(test, annotation_col = annotation_col, annotation_legend = FALSE)
+ 	compare_pheatmap(test, annotation_col = annotation_col, annotation_row = annotation_row)
+ 
+ 	# Change angle of text in the columns
+ 	compare_pheatmap(test, annotation_col = annotation_col, annotation_row = annotation_row, angle_col = "45")
+ 	compare_pheatmap(test, annotation_col = annotation_col, angle_col = "0")
+ 
+ 	# Specify colors
+ 	ann_colors = list(
+ 	    Time = c("white", "firebrick"),
+ 	    CellType = c(CT1 = "#1B9E77", CT2 = "#D95F02"),
+ 	    GeneClass = c(Path1 = "#7570B3", Path2 = "#E7298A", Path3 = "#66A61E")
+ 	)
+ 
+ 	compare_pheatmap(test, annotation_col = annotation_col, annotation_colors = ann_colors, main = "Title")
+ 	compare_pheatmap(test, annotation_col = annotation_col, annotation_row = annotation_row, 
+ 	         annotation_colors = ann_colors)
+ 	compare_pheatmap(test, annotation_col = annotation_col, annotation_colors = ann_colors[2]) 
+ 
+ 	# Gaps in heatmaps
+ 	compare_pheatmap(test, annotation_col = annotation_col, cluster_rows = FALSE, gaps_row = c(10, 14))
+ 	compare_pheatmap(test, annotation_col = annotation_col, cluster_rows = FALSE, gaps_row = c(10, 14), 
+ 	         cutree_col = 2)
+ 
+ 	# Show custom strings as row/col names
+ 	labels_row = c("", "", "", "", "", "", "", "", "", "", "", "", "", "", "", 
+ 		"", "", "Il10", "Il15", "Il1b")
+ 
+ 	compare_pheatmap(test, annotation_col = annotation_col, labels_row = labels_row)
+ 
+ 	# Specifying clustering from distance matrix
+ 	drows = dist(test, method = "minkowski")
+ 	dcols = dist(t(test), method = "minkowski")
+ 	compare_pheatmap(test, clustering_distance_rows = drows, clustering_distance_cols = dcols)
+ 
+ 	library(dendsort)
+ 
+ 	callback = function(hc, ...){dendsort(hc)}
+ 	compare_pheatmap(test, clustering_callback = callback)
+ }
Loading required namespace: pheatmap
Warning message:
argument `kmeans_k` is not suggested to use in pheatmap -> Heatmap
translation because it changes the input matrix. You might check
`row_km` and `column_km` arguments in Heatmap(). 
> 
> 
> set.seed(42)
> nsamples <- 10
> 
> mat <- matrix(rpois(20*nsamples, 20), ncol=nsamples)
> colnames(mat) <- paste0("sample", seq_len(ncol(mat)))
> rownames(mat) <- paste0("gene", seq_len(nrow(mat)))
> 
> annot <- data.frame(
+   labs = sample(c("A","B","C","D"), size = ncol(mat), replace = TRUE),
+   row.names = colnames(mat)
+ )
> ins <- list(mat = mat, annotation_col = annot)
> do.call(ComplexHeatmap::pheatmap, ins[1])
> do.call(ComplexHeatmap::pheatmap, ins)
> 
> proc.time()
   user  system elapsed 
 56.806   0.856  60.994


R version 4.3.3 (2024-02-29) -- "Angel Food Cake"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin20 (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(circlize)
========================================
circlize version 0.4.16
CRAN page: https://cran.r-project.org/package=circlize
Github page: https://github.com/jokergoo/circlize
Documentation: https://jokergoo.github.io/circlize_book/book/

If you use it in published research, please cite:
Gu, Z. circlize implements and enhances circular visualization
  in R. Bioinformatics 2014.

This message can be suppressed by:
  suppressPackageStartupMessages(library(circlize))
========================================

> library(ComplexHeatmap)
Loading required package: grid
========================================
ComplexHeatmap version 2.18.0
Bioconductor page: http://bioconductor.org/packages/ComplexHeatmap/
Github page: https://github.com/jokergoo/ComplexHeatmap
Documentation: http://jokergoo.github.io/ComplexHeatmap-reference

If you use it in published research, please cite either one:
- Gu, Z. Complex Heatmap Visualization. iMeta 2022.
- Gu, Z. Complex heatmaps reveal patterns and correlations in multidimensional 
    genomic data. Bioinformatics 2016.


The new InteractiveComplexHeatmap package can directly export static 
complex heatmaps into an interactive Shiny app with zero effort. Have a try!

This message can be suppressed by:
  suppressPackageStartupMessages(library(ComplexHeatmap))
========================================

> library(GetoptLong)
> 
> ha = SingleAnnotation(value = 1:10)
> draw(ha, test = "single column annotation")
> ha = SingleAnnotation(value = 1:10, which = "row")
> draw(ha, test = "single row annotation")
> ha = SingleAnnotation(value = 1:10)
> draw(ha, index = 6:10, test = "single column annotation, subset")
> draw(ha, index = 6:10, k = 1, n = 2, test = "single column annotation, subset, k=1 n=2")
> draw(ha, index = 6:10, k = 2, n = 2, test = "single column annotation, subset, k=1 n=2")
> 
> x = 1:10
> ha = SingleAnnotation(value = x)
> draw(ha, test = "single column annotation")
> 
> m = cbind(1:10, 10:1)
> colnames(m) = c("a", "b")
> ha = SingleAnnotation(value = m)
> draw(ha, test = "matrix as column annotation")
> 
> ha = SingleAnnotation(value = 1:10, col = colorRamp2(c(1, 10), c("blue", "red")))
> draw(ha, test = "color mapping function")
> 
> ha = SingleAnnotation(value = c(rep(c("a", "b"), 5)))
> draw(ha, test = "discrete annotation")
> ha = SingleAnnotation(value = c(rep(c("a", "b"), 5)), col = c("a" = "red", "b" = "blue"))
> draw(ha, test = "discrete annotation with defined colors")
> 
> anno = anno_simple(1:10)
> ha = SingleAnnotation(fun = anno)
> draw(ha, test = "AnnotationFunction as input")
> 
> anno = anno_barplot(matrix(nc = 2, c(1:10, 10:1)))
> ha = SingleAnnotation(fun = anno)
> draw(ha, test = "anno_barplot as input")
> draw(ha, index = 1:5, test = "anno_barplot as input, 1:5")
> draw(ha, index = 1:5, k = 1, n = 2, test = "anno_barplot as input, 1:5, k = 1, n = 2")
> draw(ha, index = 1:5, k = 2, n = 2, test = "anno_barplot as input, 1:5, k = 2, n = 2")
> 
> lt = lapply(1:20, function(x) cumprod(1 + runif(1000, -x/100, x/100)) - 1)
> anno = anno_horizon(lt, which = "row")
> ha = SingleAnnotation(fun = anno, which = "row")
> draw(ha, test = "anno_horizon as input")
> 
> fun = local({
+ 	value = 1:10
+ 	function(index, k = 1, n = 1) {
+ 		pushViewport(viewport(xscale = c(0.5, length(index) + 0.5), yscale = range(value)))
+ 		grid.points(seq_along(index), value[index])
+ 		grid.rect()
+ 		if(k == 1) grid.yaxis()
+ 		popViewport()
+ 	}
+ })
> ha = SingleAnnotation(fun = fun, height = unit(4, "cm"))
> # ha[1:5]
> draw(ha, index = c(1, 4, 2, 6), test = "self-defined function")
> draw(ha, index = c(1, 4, 2, 6), k = 1, n = 2, test = "self-defined function, k = 1, n = 2")
> draw(ha, index = c(1, 4, 2, 6), k = 2, n = 2, test = "self-defined function, k = 2, n = 2")
> 
> 
> # test gridtext
> ha = SingleAnnotation(value = 1:10, label = gt_render("foo", r = unit(2, "pt")), name_gp = gpar(box_fill = "red"))
Loading required namespace: gridtext
> draw(ha, test = "single column annotation")
> 
> 
> 
> proc.time()
   user  system elapsed 
  8.302   0.479   9.024


R version 4.3.3 (2024-02-29) -- "Angel Food Cake"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin20 (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> 
> library(ComplexHeatmap)
Loading required package: grid
========================================
ComplexHeatmap version 2.18.0
Bioconductor page: http://bioconductor.org/packages/ComplexHeatmap/
Github page: https://github.com/jokergoo/ComplexHeatmap
Documentation: http://jokergoo.github.io/ComplexHeatmap-reference

If you use it in published research, please cite either one:
- Gu, Z. Complex Heatmap Visualization. iMeta 2022.
- Gu, Z. Complex heatmaps reveal patterns and correlations in multidimensional 
    genomic data. Bioinformatics 2016.


The new InteractiveComplexHeatmap package can directly export static 
complex heatmaps into an interactive Shiny app with zero effort. Have a try!

This message can be suppressed by:
  suppressPackageStartupMessages(library(ComplexHeatmap))
========================================

> 
> words = sapply(1:30, function(x) strrep(sample(letters, 1), sample(3:10, 1)))
> grid.newpage()
> grid.textbox(words, gp = gpar(fontsize = runif(30, min = 5, max = 30)))
> 
> sentenses = c("This is sentense 1", "This is a long long long long long long long sentense.")
> grid.newpage()
> grid.textbox(sentenses)
> grid.textbox(sentenses, word_wrap = TRUE)
> grid.textbox(sentenses, word_wrap = TRUE, add_new_line = TRUE)
> 
> 
> require(circlize)
Loading required package: circlize
========================================
circlize version 0.4.16
CRAN page: https://cran.r-project.org/package=circlize
Github page: https://github.com/jokergoo/circlize
Documentation: https://jokergoo.github.io/circlize_book/book/

If you use it in published research, please cite:
Gu, Z. circlize implements and enhances circular visualization
  in R. Bioinformatics 2014.

This message can be suppressed by:
  suppressPackageStartupMessages(library(circlize))
========================================

> mat = matrix(rnorm(100*10), nrow = 100)
> 
> split = sample(letters[1:10], 100, replace = TRUE)
> text = lapply(unique(split), function(x) {
+ 	data.frame(month.name, col = rand_color(12, friendly = TRUE), fontsize = runif(12, 6, 14))
+ })
> names(text) = unique(split)
> 
> Heatmap(mat, cluster_rows = FALSE, row_split = split,
+     right_annotation = rowAnnotation(wc = anno_textbox(split, text))
+ )
> 
> proc.time()
   user  system elapsed 
  7.809   0.474   8.553


R version 4.3.3 (2024-02-29) -- "Angel Food Cake"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin20 (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(circlize)
========================================
circlize version 0.4.16
CRAN page: https://cran.r-project.org/package=circlize
Github page: https://github.com/jokergoo/circlize
Documentation: https://jokergoo.github.io/circlize_book/book/

If you use it in published research, please cite:
Gu, Z. circlize implements and enhances circular visualization
  in R. Bioinformatics 2014.

This message can be suppressed by:
  suppressPackageStartupMessages(library(circlize))
========================================

> library(ComplexHeatmap)
Loading required package: grid
========================================
ComplexHeatmap version 2.18.0
Bioconductor page: http://bioconductor.org/packages/ComplexHeatmap/
Github page: https://github.com/jokergoo/ComplexHeatmap
Documentation: http://jokergoo.github.io/ComplexHeatmap-reference

If you use it in published research, please cite either one:
- Gu, Z. Complex Heatmap Visualization. iMeta 2022.
- Gu, Z. Complex heatmaps reveal patterns and correlations in multidimensional 
    genomic data. Bioinformatics 2016.


The new InteractiveComplexHeatmap package can directly export static 
complex heatmaps into an interactive Shiny app with zero effort. Have a try!

This message can be suppressed by:
  suppressPackageStartupMessages(library(ComplexHeatmap))
========================================

> library(GetoptLong)
> 
> set.seed(123)
> lt = list(a = sample(letters, 10),
+ 	      b = sample(letters, 15),
+ 	      c = sample(letters, 20))
> 
> m = make_comb_mat(lt)
> t(m)
A combination matrix with 3 sets and 6 combinations.
  ranges of combination set size: c(1, 8).
  mode for the combination size: distinct.
  sets are on columns

Combination sets are:
  a b c code size
  x x x  111    4
  x x    110    4
  x   x  101    2
    x x  011    6
    x    010    1
      x  001    8

Sets are:
  set size
    a   10
    b   15
    c   20
> set_name(m)
[1] "a" "b" "c"
> comb_name(m)
[1] "111" "110" "101" "011" "010" "001"
> set_size(m)
 a  b  c 
10 15 20 
> comb_size(m)
111 110 101 011 010 001 
  4   4   2   6   1   8 
> lapply(comb_name(m), function(x) extract_comb(m, x))
[[1]]
[1] "e" "j" "x" "y"

[[2]]
[1] "c" "k" "n" "s"

[[3]]
[1] "o" "r"

[[4]]
[1] "a" "g" "h" "i" "l" "u"

[[5]]
[1] "d"

[[6]]
[1] "b" "f" "m" "q" "t" "v" "w" "z"

> draw(UpSet(m))
> draw(UpSet(m, comb_col = c(rep(2, 3), rep(3, 3), 1)))
> draw(UpSet(t(m)))
> 
> set_name(t(m))
[1] "a" "b" "c"
> comb_name(t(m))
[1] "111" "110" "101" "011" "010" "001"
> set_size(t(m))
 a  b  c 
10 15 20 
> comb_size(t(m))
111 110 101 011 010 001 
  4   4   2   6   1   8 
> lapply(comb_name(t(m)), function(x) extract_comb(t(m), x))
[[1]]
[1] "e" "j" "x" "y"

[[2]]
[1] "c" "k" "n" "s"

[[3]]
[1] "o" "r"

[[4]]
[1] "a" "g" "h" "i" "l" "u"

[[5]]
[1] "d"

[[6]]
[1] "b" "f" "m" "q" "t" "v" "w" "z"

> 
> m = make_comb_mat(lt, mode = "intersect")
> lapply(comb_name(m), function(x) extract_comb(m, x))
[[1]]
[1] "e" "j" "x" "y"

[[2]]
[1] "c" "e" "j" "k" "n" "s" "x" "y"

[[3]]
[1] "e" "j" "o" "r" "x" "y"

[[4]]
 [1] "a" "e" "g" "h" "i" "j" "l" "u" "x" "y"

[[5]]
 [1] "c" "e" "j" "k" "n" "o" "r" "s" "x" "y"

[[6]]
 [1] "a" "c" "d" "e" "g" "h" "i" "j" "k" "l" "n" "s" "u" "x" "y"

[[7]]
 [1] "a" "b" "e" "f" "g" "h" "i" "j" "l" "m" "o" "q" "r" "t" "u" "v" "w" "x" "y"
[20] "z"

> draw(UpSet(m))
> 
> m = make_comb_mat(lt, mode = "union")
> lapply(comb_name(m), function(x) extract_comb(m, x))
[[1]]
 [1] "a" "b" "c" "d" "e" "f" "g" "h" "i" "j" "k" "l" "m" "n" "o" "q" "r" "s" "t"
[20] "u" "v" "w" "x" "y" "z"

[[2]]
 [1] "a" "c" "d" "e" "g" "h" "i" "j" "k" "l" "n" "o" "r" "s" "u" "x" "y"

[[3]]
 [1] "a" "b" "c" "e" "f" "g" "h" "i" "j" "k" "l" "m" "n" "o" "q" "r" "s" "t" "u"
[20] "v" "w" "x" "y" "z"

[[4]]
 [1] "a" "b" "c" "d" "e" "f" "g" "h" "i" "j" "k" "l" "m" "n" "o" "q" "r" "s" "t"
[20] "u" "v" "w" "x" "y" "z"

[[5]]
 [1] "c" "e" "j" "k" "n" "o" "r" "s" "x" "y"

[[6]]
 [1] "a" "c" "d" "e" "g" "h" "i" "j" "k" "l" "n" "s" "u" "x" "y"

[[7]]
 [1] "a" "b" "e" "f" "g" "h" "i" "j" "l" "m" "o" "q" "r" "t" "u" "v" "w" "x" "y"
[20] "z"

> draw(UpSet(m))
> 
> f = system.file("extdata", "movies.csv", package = "UpSetR")
> if(file.exists(f)) {
+ 	movies <- read.csv(system.file("extdata", "movies.csv", package = "UpSetR"), header = T, sep = ";")
+ 	m = make_comb_mat(movies, top_n_sets = 6)
+ 	t(m)
+ 	set_name(m)
+ 	comb_name(m)
+ 	set_size(m)
+ 	comb_size(m)
+ 	lapply(comb_name(m), function(x) extract_comb(m, x))
+ 
+ 	set_name(t(m))
+ 	comb_name(t(m))
+ 	set_size(t(m))
+ 	comb_size(t(m))
+ 	lapply(comb_name(t(m)), function(x) extract_comb(t(m), x))
+ 
+ 	draw(UpSet(m))
+ 	draw(UpSet(t(m)))
+ 
+ 	m = make_comb_mat(movies, top_n_sets = 6, mode = "intersect")
+ 	m = make_comb_mat(movies, top_n_sets = 6, mode = "union")
+ }
> 
> library(circlize)
> library(GenomicRanges)
Loading required package: stats4
Loading required package: BiocGenerics

Attaching package: 'BiocGenerics'

The following objects are masked from 'package:stats':

    IQR, mad, sd, var, xtabs

The following objects are masked from 'package:base':

    Filter, Find, Map, Position, Reduce, anyDuplicated, aperm, append,
    as.data.frame, basename, cbind, colnames, dirname, do.call,
    duplicated, eval, evalq, get, grep, grepl, intersect, is.unsorted,
    lapply, mapply, match, mget, order, paste, pmax, pmax.int, pmin,
    pmin.int, rank, rbind, rownames, sapply, setdiff, sort, table,
    tapply, union, unique, unsplit, which.max, which.min

Loading required package: S4Vectors

Attaching package: 'S4Vectors'

The following object is masked from 'package:utils':

    findMatches

The following objects are masked from 'package:base':

    I, expand.grid, unname

Loading required package: IRanges
Loading required package: GenomeInfoDb
> lt = lapply(1:4, function(i) generateRandomBed())
> lt = lapply(lt, function(df) GRanges(seqnames = df[, 1], ranges = IRanges(df[, 2], df[, 3])))
> names(lt) = letters[1:4]
> m = make_comb_mat(lt)
> 
> # if(0) {
> # set.seed(123)
> # lt = list(a = sample(letters, 10),
> # 	      b = sample(letters, 15),
> # 	      c = sample(letters, 20))
> # v = gplots::venn(lt, show.plot = FALSE)
> # rownames(v) = apply(v[, -1], 1, paste, collapse = "")
> # m = make_comb_mat(lt)
> # cs = structure(comb_size(m), names = comb_name(m))
> # }
> 
> if(file.exists(f)) {
+ 	movies <- read.csv(f, header = T, sep = ";")
+ 	genre = c("Action", "Romance", "Horror", "Children", "SciFi", "Documentary")
+ 	rate = cut(movies$AvgRating, c(0, 1, 2, 3, 4, 5))
+ 	m_list = tapply(seq_len(nrow(movies)), rate, function(ind) {
+ 		make_comb_mat(movies[ind, genre, drop = FALSE])
+ 	})
+ 	m_list2 = normalize_comb_mat(m_list)
+ 
+ 	lapply(m_list2, set_name)
+ 	lapply(m_list2, set_size)
+ 	lapply(m_list2, comb_name)
+ 	lapply(m_list2, comb_size)
+ 
+ 	lapply(1:length(m_list), function(i) {
+ 		n1 = comb_name(m_list[[i]])
+ 		x1 = comb_size(m_list[[i]])
+ 		n2 = comb_name(m_list2[[i]])
+ 		x2 = comb_size(m_list2[[i]])
+ 		l = n2 %in% n1
+ 		x2[!l]
+ 	})
+ }
[[1]]
110001 100101 100011 110000 100100 100010 100001 010100 010010 010001 000110 
     0      0      0      0      0      0      0      0      0      0      0 
000101 000011 100000 000010 
     0      0      0      1 

[[2]]
110001 100101 100011 100001 010100 010010 010001 000110 000101 000011 
     1      1      0      5      0      0      0      0      8      0 

[[3]]
110001 100101 100011 100001 010001 000101 000011 
     0      4      0     35      7     27      1 

[[4]]
110001 100101 100011 100100 100001 010001 000101 000011 
     1      6      1      6     45      5     11      4 

[[5]]
110001 100101 100011 100100 100001 010100 010010 010001 000110 000101 000011 
     0      1      1      1      6      0      0      0      0      0      0 

> 
> 
> proc.time()
   user  system elapsed 
 38.781   0.844  41.199


R version 4.3.3 (2024-02-29) -- "Angel Food Cake"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin20 (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> library(circlize)
========================================
circlize version 0.4.16
CRAN page: https://cran.r-project.org/package=circlize
Github page: https://github.com/jokergoo/circlize
Documentation: https://jokergoo.github.io/circlize_book/book/

If you use it in published research, please cite:
Gu, Z. circlize implements and enhances circular visualization
  in R. Bioinformatics 2014.

This message can be suppressed by:
  suppressPackageStartupMessages(library(circlize))
========================================

> library(ComplexHeatmap)
Loading required package: grid
========================================
ComplexHeatmap version 2.18.0
Bioconductor page: http://bioconductor.org/packages/ComplexHeatmap/
Github page: https://github.com/jokergoo/ComplexHeatmap
Documentation: http://jokergoo.github.io/ComplexHeatmap-reference

If you use it in published research, please cite either one:
- Gu, Z. Complex Heatmap Visualization. iMeta 2022.
- Gu, Z. Complex heatmaps reveal patterns and correlations in multidimensional 
    genomic data. Bioinformatics 2016.


The new InteractiveComplexHeatmap package can directly export static 
complex heatmaps into an interactive Shiny app with zero effort. Have a try!

This message can be suppressed by:
  suppressPackageStartupMessages(library(ComplexHeatmap))
========================================

> library(GetoptLong)
> 
> # things needed to be tested
> # 1. the order
> # 2. if the sum of sizes are larger than xlim
> 
> make_plot = function(pos1, pos2, range) {
+ 	oxpd = par("xpd")
+ 	par(xpd = NA)
+ 	plot(NULL, xlim = c(0, 4), ylim = range, ann = FALSE)
+ 	col = rand_color(nrow(pos1), transparency = 0.5)
+ 	rect(0.5, pos1[, 1], 1.5, pos1[, 2], col = col)
+ 	rect(2.5, pos2[, 1], 3.5, pos2[, 2], col = col)
+ 	segments(1.5, rowMeans(pos1), 2.5, rowMeans(pos2))
+ 	par(xpd = oxpd)
+ }
> 
> range = c(0, 10)
> pos1 = rbind(c(1, 2), c(5, 7))
> make_plot(pos1, smartAlign2(pos1, range = range), range)
> 
> range = c(0, 10)
> pos1 = rbind(c(-0.5, 2), c(5, 7))
> make_plot(pos1, smartAlign2(pos1, range = range), range)
> 
> pos1 = rbind(c(-1, 2), c(3, 4), c(5, 6), c(7, 11))
> pos1 = pos1 + runif(length(pos1), max = 0.3, min = -0.3)
> par(mfrow = c(3, 3))
> for(i in 1:9) {
+ 	ind = sample(4, 4)
+ 	make_plot(pos1[ind, ], smartAlign2(pos1[ind, ], range = range), range)
+ }
> par(mfrow = c(1, 1))
> 
> pos1 = rbind(c(3, 6), c(4, 7))
> make_plot(pos1, smartAlign2(pos1, range = range), range)
> 
> pos1 = rbind(c(1, 8), c(3, 10))
> make_plot(pos1, smartAlign2(pos1, range = range), range)
> 
> ########## new version of smartAlign2() ############
> 
> start = c(0.0400972528391016, 0.0491583597430212, 0.0424302664385027, 0.0547524243812509, 0.0820937279769642, 0.126861283282835, 0.178503822565168, 0.327742831447437, 0.570671411156898, 0.81775868755151)
> end = c(0.0921142856224367, 0.107091640256979, 0.137858195099959, 0.159189883311057, 0.177521656638421, 0.20727333210178, 0.304669254357909, 0.463122553167947, 0.676924742689255, 0.929837466294643)
> range = c(0, 1)
> smartAlign2(start, end, range, plot = TRUE)
enter to continue
             [,1]       [,2]
 [1,] 0.002200888 0.05421792
 [2,] 0.054217921 0.11215120
 [3,] 0.112151202 0.20757913
 [4,] 0.207579130 0.31201659
 [5,] 0.312016589 0.40744452
 [6,] 0.407444518 0.48785657
 [7,] 0.487856567 0.61402200
 [8,] 0.614021999 0.74940172
 [9,] 0.749401720 0.85565505
[10,] 0.855655052 0.96773383
> 
> 
> start <- c(0.722121284290678, 0.701851666769472, 0.284795592003117, 0.335674695572052, 0.246977082249377, 0.767289857630785, 0.728198060058033, 0.299241440370817, -0.0149946764559372, 0.85294351791166, 0.126216621670218, 0.478169948493225)
> end <- c(0.766196472718668, 0.763101604258565, 0.34604552949221, 0.421334650222341, 0.344144413077725, 0.847196123677626, 0.813858014708322, 0.392347344675911, 0.108452620381171, 0.969486388630396, 0.249951602628847, 0.584914163656308)
> od = order(start)
> start = start[od]; end = end[od]
> range = c(0, 1)
> pos = smartAlign2(start, end, range)
> n = nrow(pos)
> pos[1:(n-1), 2] > pos[2:n, 1]
 [1] TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE TRUE
> 
> 
> if(0) {
+ 	go_id = random_GO(500)
+ 	mat = GO_similarity(go_id)
+ 	invisible(simplify(mat, order_by_size = FALSE))
+ }
> 
> proc.time()
   user  system elapsed 
  5.168   0.374   5.653


R version 4.3.3 (2024-02-29) -- "Angel Food Cake"
Copyright (C) 2024 The R Foundation for Statistical Computing
Platform: x86_64-apple-darwin20 (64-bit)

R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.

R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.

Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.

> 
> 
> suppressWarnings(suppressPackageStartupMessages(library(ComplexHeatmap)))
> library(testthat)
> 
> test_check("ComplexHeatmap")
[ FAIL 0 | WARN 0 | SKIP 0 | PASS 181 ]
> 
> proc.time()
   user  system elapsed 
 41.092   0.945  63.270

Example timings

name	user	system	elapsed
AdditiveUnit-class	0.000	0.000	0.001
AdditiveUnit	0.000	0.001	0.001
AnnotationFunction-class	0.000	0.001	0.001
AnnotationFunction	9.129	0.190	10.081
ColorMapping-class	0.001	0.000	0.001
ColorMapping	0.020	0.002	0.023
ComplexHeatmap-package	0	0	0
Extract.AnnotationFunction	0.045	0.003	0.050
Extract.Heatmap	1.174	0.016	1.476
Extract.HeatmapAnnotation	0.095	0.004	0.104
Extract.HeatmapList	0.312	0.005	0.338
Extract.SingleAnnotation	0.033	0.002	0.036
Extract.comb_mat	0.016	0.002	0.019
Extract.gridtext	0.000	0.000	0.001
Heatmap-class	0.000	0.000	0.001
Heatmap	0.000	0.000	0.001
Heatmap3D	0.353	0.004	0.378
HeatmapAnnotation-class	0.000	0.001	0.000
HeatmapAnnotation	0.000	0.001	0.001
HeatmapList-class	0	0	0
HeatmapList	0.000	0.001	0.000
Legend	0.159	0.006	0.178
Legends-class	0.017	0.001	0.017
Legends	0.001	0.001	0.000
SingleAnnotation-class	0	0	0
SingleAnnotation	0.141	0.005	0.149
UpSet	1.080	0.011	1.155
add.AdditiveUnit	0.001	0.000	0.000
add_heatmap-Heatmap-method	0.001	0.000	0.000
add_heatmap-HeatmapAnnotation-method	0.001	0.000	0.000
add_heatmap-HeatmapList-method	0.000	0.001	0.001
add_heatmap-dispatch	0.000	0.001	0.001
adjust_dend_by_x	0.033	0.007	0.047
adjust_heatmap_list-HeatmapList-method	0.000	0.000	0.001
alter_graphic	0.353	0.004	0.385
anno_barplot	0.050	0.002	0.054
anno_block	2.179	0.020	2.420
anno_boxplot	0.063	0.003	0.068
anno_customize	1.416	0.009	1.581
anno_density	1.235	0.034	1.321
anno_empty	0.028	0.002	0.031
anno_histogram	0.174	0.005	0.190
anno_horizon	9.108	0.133	9.968
anno_image	0.000	0.001	0.001
anno_joyplot	0.711	0.031	0.773
anno_lines	0.136	0.005	0.149
anno_link	0	0	0
anno_mark	1.070	0.016	1.153
anno_numeric	0.371	0.009	0.403
anno_oncoprint_barplot	0.000	0.001	0.000
anno_points	0.039	0.003	0.047
anno_simple	0.139	0.010	0.159
anno_summary	0.659	0.006	0.707
anno_text	0.150	0.006	0.168
anno_textbox	1.349	0.011	1.451
anno_zoom	0.749	0.006	0.814
annotation_axis_grob	0.125	0.016	0.148
annotation_legend_size-HeatmapList-method	0.000	0.001	0.001
attach_annotation-Heatmap-method	1.264	0.009	1.395
bar3D	0.026	0.001	0.030
bin_genome	0.000	0.001	0.001
c.ColorMapping	0.003	0.001	0.004
c.HeatmapAnnotation	0.080	0.003	0.095
cluster_between_groups	0.058	0.002	0.063
cluster_within_group	0.051	0.002	0.055
color_mapping_legend-ColorMapping-method	0.000	0.000	0.001
columnAnnotation	0.000	0.000	0.001
column_dend-Heatmap-method	0.644	0.006	0.729
column_dend-HeatmapList-method	2.185	0.020	2.366
column_dend-dispatch	0.000	0.000	0.001
column_order-Heatmap-method	0.637	0.007	0.681
column_order-HeatmapList-method	2.147	0.016	2.237
column_order-dispatch	0.000	0.001	0.000
comb_degree	0.004	0.001	0.005
comb_name	0.017	0.001	0.019
comb_size	0.004	0.001	0.005
compare_heatmap.2	2.255	0.021	2.400
compare_heatmap	1.668	0.009	1.834
compare_pheatmap	2.250	0.029	2.409
complement_size	0.001	0.000	0.001
component_height-Heatmap-method	0.001	0.000	0.001
component_height-HeatmapList-method	0.001	0.000	0.001
component_height-dispatch	0.000	0.000	0.001
component_width-Heatmap-method	0	0	0
component_width-HeatmapList-method	0	0	0
component_width-dispatch	0	0	0
copy_all-AnnotationFunction-method	0.001	0.000	0.000
copy_all-SingleAnnotation-method	0.001	0.000	0.000
copy_all-dispatch	0.001	0.000	0.000
decorate_annotation	0.535	0.004	0.576
decorate_column_dend	0.001	0.001	0.000
decorate_column_names	0.001	0.001	0.001
decorate_column_title	0.000	0.001	0.001
decorate_dend	0.321	0.003	0.344
decorate_dimnames	0.357	0.003	0.372
decorate_heatmap_body	0.277	0.003	0.297
decorate_row_dend	0.000	0.001	0.000
decorate_row_names	0.000	0.001	0.001
decorate_row_title	0.000	0.001	0.001
decorate_title	0.308	0.003	0.327
default_axis_param	0.000	0.001	0.001
default_get_type	0.000	0.000	0.001
dend_heights	0.000	0.000	0.001
dend_xy	0.025	0.002	0.030
dendrogramGrob	0.001	0.000	0.000
densityHeatmap	2.424	0.031	2.694
dim.Heatmap	0.001	0.000	0.000
dist2	0.020	0.002	0.025
draw-AnnotationFunction-method	0.000	0.000	0.001
draw-Heatmap-method	0.001	0.000	0.001
draw-HeatmapAnnotation-method	0.000	0.001	0.000
draw-HeatmapList-method	0.000	0.001	0.000
draw-Legends-method	0.030	0.001	0.033
draw-SingleAnnotation-method	0	0	0
draw-dispatch	0	0	0
draw_annotation-Heatmap-method	0	0	0
draw_annotation_legend-HeatmapList-method	0	0	0
draw_dend-Heatmap-method	0.001	0.000	0.000
draw_dimnames-Heatmap-method	0.001	0.000	0.000
draw_heatmap_body-Heatmap-method	0.001	0.000	0.000
draw_heatmap_legend-HeatmapList-method	0.001	0.000	0.000
draw_heatmap_list-HeatmapList-method	0.001	0.000	0.001
draw_title-Heatmap-method	0.001	0.000	0.001
draw_title-HeatmapList-method	0.001	0.000	0.001
draw_title-dispatch	0.001	0.000	0.000
extract_comb	0.005	0.001	0.005
frequencyHeatmap	1.087	0.007	1.189
full_comb_code	0.005	0.001	0.006
getXY_in_parent_vp	0.013	0.002	0.015
get_color_mapping_list-HeatmapAnnotation-method	0.001	0.000	0.000
get_legend_param_list-HeatmapAnnotation-method	0.000	0.000	0.001
grid.annotation_axis	0.000	0.000	0.001
grid.boxplot	0.013	0.001	0.015
grid.dendrogram	0.755	0.032	0.868
grid.draw.Legends	0.025	0.001	0.025
grid.textbox	0.000	0.001	0.001
gt_render	1.688	0.043	1.827
heatmap_legend_size-HeatmapList-method	0.001	0.000	0.001
height.AnnotationFunction	0.013	0.001	0.015
height.Heatmap	0.000	0.001	0.001
height.HeatmapAnnotation	0.000	0.001	0.001
height.HeatmapList	0	0	0
height.Legends	0.037	0.001	0.039
height.SingleAnnotation	0.000	0.000	0.001
heightAssign.AnnotationFunction	0.000	0.001	0.001
heightAssign.HeatmapAnnotation	0.000	0.000	0.001
heightAssign.SingleAnnotation	0.000	0.000	0.001
heightDetails.annotation_axis	0.000	0.000	0.001
heightDetails.legend	0.000	0.000	0.001
heightDetails.legend_body	0.000	0.000	0.001
heightDetails.packed_legends	0.000	0.000	0.001
heightDetails.textbox	0.001	0.000	0.001
ht_global_opt	0.001	0.000	0.001
ht_opt	0.014	0.004	0.018
ht_size	0.000	0.000	0.001
is_abs_unit	0.001	0.000	0.002
length.HeatmapAnnotation	0	0	0
length.HeatmapList	0.000	0.001	0.001
list_components	0.000	0.001	0.001
list_to_matrix	0.003	0.004	0.006
make_column_cluster-Heatmap-method	0	0	0
make_comb_mat	0.007	0.002	0.010
make_layout-Heatmap-method	0	0	0
make_layout-HeatmapList-method	0.000	0.000	0.001
make_layout-dispatch	0.001	0.001	0.000
make_row_cluster-Heatmap-method	0.000	0.001	0.001
map_to_colors-ColorMapping-method	0.029	0.002	0.035
max_text_height	0.003	0.000	0.004
max_text_width	0.003	0.001	0.004
merge_dendrogram	0.189	0.007	0.209
names.HeatmapAnnotation	0.031	0.000	0.031
names.HeatmapList	0.001	0.000	0.000
namesAssign.HeatmapAnnotation	0.031	0.001	0.035
ncol.Heatmap	0.001	0.001	0.001
nobs.AnnotationFunction	0.006	0.001	0.007
nobs.HeatmapAnnotation	0	0	0
nobs.SingleAnnotation	0	0	0
normalize_comb_mat	0	0	0
normalize_genomic_signals_to_bins	0.001	0.002	0.004
nrow.Heatmap	0.000	0.000	0.001
oncoPrint	0	0	0
order.comb_mat	0	0	0
packLegend	0.130	0.005	0.144
pct_v_pct	0.000	0.001	0.002
pheatmap	0.000	0.000	0.001
pindex	0.009	0.002	0.012
plot.Heatmap	0.000	0.000	0.001
plot.HeatmapAnnotation	0	0	0
plot.HeatmapList	0	0	0
prepare-Heatmap-method	0	0	0
print.comb_mat	0.000	0.000	0.001
re_size-HeatmapAnnotation-method	0.000	0.000	0.001
restore_matrix	0.778	0.009	0.850
rowAnnotation	0.000	0.000	0.001
row_anno_barplot	0.000	0.000	0.001
row_anno_boxplot	0.000	0.000	0.001
row_anno_density	0.000	0.000	0.001
row_anno_histogram	0	0	0
row_anno_points	0	0	0
row_anno_text	0	0	0
row_dend-Heatmap-method	0.642	0.007	0.683
row_dend-HeatmapList-method	1.631	0.014	1.758
row_dend-dispatch	0	0	0
row_order-Heatmap-method	0.626	0.006	0.677
row_order-HeatmapList-method	1.610	0.013	1.797
row_order-dispatch	0.000	0.001	0.001
set_component_height-Heatmap-method	0.000	0.001	0.000
set_component_width-Heatmap-method	0	0	0
set_name	0.004	0.000	0.005
set_nameAssign	0.010	0.002	0.013
set_size	0.004	0.000	0.005
show-AnnotationFunction-method	0.000	0.000	0.001
show-ColorMapping-method	0.000	0.000	0.001
show-Heatmap-method	0.000	0.000	0.001
show-HeatmapAnnotation-method	0.000	0.001	0.000
show-HeatmapList-method	0.000	0.001	0.001
show-SingleAnnotation-method	0	0	0
show-dispatch	0.000	0.000	0.001
size.AnnotationFunction	0.013	0.000	0.016
size.HeatmapAnnotation	0.000	0.001	0.001
size.SingleAnnotation	0.000	0.001	0.001
sizeAssign.AnnotationFunction	0.007	0.001	0.008
sizeAssign.HeatmapAnnotation	0.000	0.000	0.001
sizeAssign.SingleAnnotation	0	0	0
smartAlign2	0.467	0.008	0.507
str.comb_mat	0.000	0.000	0.001
subset_gp	0.001	0.000	0.001
subset_matrix_by_row	0.000	0.001	0.000
subset_no	0.000	0.001	0.000
subset_vector	0.000	0.001	0.000
summary.Heatmap	0.000	0.001	0.000
summary.HeatmapList	0.000	0.001	0.000
t.comb_mat	0.009	0.002	0.010
test_alter_fun	0.112	0.002	0.131
textbox_grob	0.214	0.003	0.235
unify_mat_list	0.000	0.001	0.000
upset_left_annotation	0.001	0.001	0.000
upset_right_annotation	0.001	0.001	0.000
upset_top_annotation	0.001	0.000	0.001
width.AnnotationFunction	0.012	0.000	0.019
width.Heatmap	0.000	0.001	0.000
width.HeatmapAnnotation	0.001	0.001	0.001
width.HeatmapList	0	0	0
width.Legends	0.037	0.001	0.038
width.SingleAnnotation	0	0	0
widthAssign.AnnotationFunction	0.000	0.000	0.001
widthAssign.HeatmapAnnotation	0.000	0.000	0.001
widthAssign.SingleAnnotation	0.000	0.000	0.001
widthDetails.annotation_axis	0	0	0
widthDetails.legend	0	0	0
widthDetails.legend_body	0	0	0
widthDetails.packed_legends	0.001	0.000	0.000
widthDetails.textbox	0	0	0

CHECK results for ComplexHeatmap on merida1

Summary

Command output

Installation output

Tests output

Example timings