How to display two categorical variables on one tile of a heatmap - triangle tiles

Question

I have a dataset similar to the below example

df <- structure(list(Species = structure(c(1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L,3L, 
1L, 2L, 3L), .Label = c("setosa", "versicolor", "virginica"), class = 
"factor"), flower_att = c("Sepal.Length", "Sepal.Length", "Sepal.Length", 
"Sepal.Width", "Sepal.Width", "Sepal.Width", "Petal.Length", "Petal.Length", 
"Petal.Length", "Petal.Width", "Petal.Width", "Petal.Width"), measurement = 
c(5.1, 7, 6.3, 3.5, 3.2, 3.3, 1.4, 4.7, 6, 0.2, 1.4, 2.5), month = 
c("January", "February", "January", "February", "January", "February", 
"January", "February", "January", "February", "January", "February")), 
row.names = c(NA,-12L), class = "data.frame")

I want to display both sepal length and width for each species and month side by side. I was hoping to do this using a diagonal split cell in the heatmap with 2 different colour legends i.e. red for length and blue for width. If possible I would like the value to be displayed within the cell segment. My search so far has found this closest example but I am looking for a workable ggplot version.

My own attempt currently looks like the below. I cannot work out how to break up the cells.

ggplot(df, aes(x=month, y=Species)) +   geom_tile(aes(fill=measurement), 
color="black") +   theme(axis.text.x = element_text(angle=45, hjust = .5)) +   
geom_text(aes(label = round(measurement, .1))) +   scale_fill_gradient(low = 
"white", high = "red")

Update

After some serious digging through the internet I have found a potential option using geom_segment and geom_text_repel, see below. Could anyone tell me if this a viable option to pursue? If so how can I get it to meet the requirements above?

I am open to switching scale_fill_gradient to scale_fill_manual or other alternative, my main objective is to have the all data displayed side by side

ggplot(df, aes(x=month, y=Species)) +
geom_tile(aes(fill=measurement), color="black") +
theme(axis.text.x = element_text(angle=45, hjust = .5)) +
geom_text_repel(aes(label = round(measurement, .1))) +
scale_fill_gradient(low = "white", high = "red")

gb <- ggplot_build(p)

p + geom_segment(data=gb$data[[1]],
aes(x=xmin, xend=xmax, y=ymin, yend=ymax), color="black")

Answer 1

This is slightly hacky, but to be honest, without creating a dedicated geom, I don't think you can get it less hacky - and creating a geom can also get somewhat hacky :)

• Creating triangle polygons for each x/y coordinate with sapply. I guess you could use that approach for your compute_group layer in your future StatSplitTile.
• The messing with factors is a necessary evil to get the order right. If you want a specific order in your y axis, you would also need to factorise Species first.
• Using ggnewscale for a very simple way of having several fill scales.
• set limits to the same for better comparability
• coord_equal to make it look nicer

library(tidyverse)

mydat <- structure(list(Species = structure(c(1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L), .Label = c("setosa", "versicolor", "virginica"), class = "factor"), flower_att = c("Sepal.Length", "Sepal.Length", "Sepal.Length", "Sepal.Width", "Sepal.Width", "Sepal.Width", "Petal.Length", "Petal.Length", "Petal.Length", "Petal.Width", "Petal.Width", "Petal.Width"), measurement = c(5.1, 7, 6.3, 3.5, 3.2, 3.3, 1.4, 4.7, 6, 0.2, 1.4, 2.5), month = c("January", "February", "January", "February", "January", "February", "January", "February", "January", "February", "January", "February")),
  row.names = c(NA, -12L), class = "data.frame"
)

make_triangles <- function(x, y, point = "up") {
  x <- as.integer(as.factor((x)))
  y <- as.integer(as.factor((y)))

  if (point == "up") {
    newx <- sapply(x, function(x) {
      c(x - 0.5, x - 0.5, x + 0.5)
    }, simplify = FALSE)
    newy <- sapply(y, function(y) {
      c(y - 0.5, y + 0.5, y + 0.5)
    }, simplify = FALSE)
  } else if (point == "down") {
    newx <- sapply(x, function(x) {
      c(x - 0.5, x + 0.5, x + 0.5)
    }, simplify = FALSE)
    newy <- sapply(y, function(y) {
      c(y - 0.5, y - 0.5, y + 0.5)
    }, simplify = FALSE)
  }
  data.frame(x = unlist(newx), y = unlist(newy))
}

# required, otherwise you cannot use the values as fill
mydat_wide <- mydat %>% pivot_wider(names_from = "flower_att", values_from = "measurement")
# making your ordered months factor
mydat_wide$month <- droplevels(factor(mydat_wide$month, levels = month.name))
# The actual triangle computation
newcoord_up <- make_triangles(mydat_wide$month, mydat_wide$Species)
newcoord_down <- make_triangles(mydat_wide$month, mydat_wide$Species, point = "down")
# just a dirty trick for renaming
newcoord_down <- newcoord_down %>% select(xdown = x, ydown = y)
# you need to repeat each row of your previous data frame 3 times
repdata <- map_df(1:nrow(mydat_wide), function(i) mydat_wide[rep(i, 3), ])
newdata <- bind_cols(repdata, newcoord_up, newcoord_down)

ggplot(newdata) +
  geom_polygon(aes(x = x, y = y, fill = Sepal.Length, group = interaction(Species, month)), color = "black") +
  scale_fill_gradient(low = "white", high = "red", limits = c(0, 10)) +
  ggnewscale::new_scale_fill() +
  geom_polygon(aes(x = xdown, y = ydown, fill = Sepal.Width, group = interaction(Species, month)), color = "black") +
  scale_fill_gradient(low = "white", high = "red", limits = c(0, 10)) +
  scale_x_continuous(breaks = seq_along(unique(mydat_wide$month)), 
                     labels = unique(levels(mydat_wide$month))) +
  scale_y_continuous(breaks = seq_along(unique(mydat_wide$Species)),
                     labels = unique(mydat_wide$Species))+
  coord_equal()

^{Created on 2021-01-27 by the reprex package (v0.3.0)}