Plot background colour in gradient

Question

This code produces the first plot below:

water.height <- seq(0, 5, 1)
y <- seq(0, 1500, length.out = 6)
df <- data.frame(water.height, y)

library(g         


        

Answer 1

The relevant link to the ggplot2 approach was given in the comments. Copied from there:

library(grid) 
g <- rasterGrob(blues9, width=unit(1,"npc"), height = unit(1,"npc"), 
interpolate = TRUE) 
# grid.draw(g) 

library(ggplot2) 
ggplot(mtcars, aes(factor(cyl))) + # add gradient background 
   annotation_custom(g, xmin=-Inf, xmax=Inf, ymin=-Inf, ymax=Inf) + 
   geom_bar() # add data layer 

---

My own approach:

As usual, I cannot compete with the simple elegance of baptiste's solutions for problems with grid graphics, but here is my approach since I went to all that work:

gg.background.fill <- function(gg.plot, cols = "white", which = "x") {
  #does not work with facets

  stopifnot(which %in% c("x", "y"))
  which1 <- if (which == "x") "width" else "height"

  require(gridExtra)

  g <- ggplotGrob(gg.plot)
  #g <- ggplotGrob(p)
  gg <- g$grobs      
  findIt <- vapply(gg, function(x) grepl("GRID.gTree", x$name, fixed = TRUE), TRUE)
  n1 <- getGrob(gg[findIt][[1]], "grill.gTree", grep=TRUE)$name
  n2 <- getGrob(gg[findIt][[1]], "panel.background.rect", grep=TRUE)$name
  gg[findIt][[1]]$children[[n1]]$children[[n2]]$gp$fill <- cols
  x <- gg[findIt][[1]]$children[[n1]]$children[[n2]][[which]]
  w <- gg[findIt][[1]]$children[[n1]]$children[[n2]][[which1]]
  attr <- attributes(x)
  x <- seq(0 + c(w)/length(cols)/2, 1 - c(w)/length(cols)/2, length.out = length(cols))
  attributes(x) <- attr
  gg[findIt][[1]]$children[[n1]]$children[[n2]][[which]] <- x
  w <- c(w)/length(cols) 
  attributes(w) <- attr
  gg[findIt][[1]]$children[[n1]]$children[[n2]][[which1]] <- w
  g$grobs <- gg
  class(g) = c("arrange", "ggplot", class(g)) 
  g
}
p1 <-  gg.background.fill(p, colorRampPalette(c("red", "blue"))(100))
print(p1)

p2 <-  gg.background.fill(p, colorRampPalette(c("red", "blue"))(100), "y")
print(p2)

This modifies the existing background which might be considered an advantage, but in contrast to the annotation_custom approach it doesn't work with faceting. More work would be required for that.

Answer 2

We want to use a linear gradient as the background of a plot.

Let's start by making a matrix with numbers between 0 and 1.

# The angle of our linear gradient
deg <- 45
rad <- deg / (180 / pi)

# A 5x5 matrix
n   <- 5
mat <- matrix(data = 0, ncol = n, nrow = n)

# Let's fill in the matrix.
for (i in 1:n) {
  for (j in 1:n) {
    mat[i, j] <- (i / n) * cos(rad) + (j / n) * sin(rad)
  }
}

What did we get?

mat
#>           [,1]      [,2]      [,3]      [,4]      [,5]
#> [1,] 0.2828427 0.4242641 0.5656854 0.7071068 0.8485281
#> [2,] 0.4242641 0.5656854 0.7071068 0.8485281 0.9899495
#> [3,] 0.5656854 0.7071068 0.8485281 0.9899495 1.1313708
#> [4,] 0.7071068 0.8485281 0.9899495 1.1313708 1.2727922
#> [5,] 0.8485281 0.9899495 1.1313708 1.2727922 1.4142136

That looks pretty close to what we wanted.

Now, let's clamp the values between 0 and 1.

mat <- mat - min(mat)
mat <- mat / max(mat)
mat
#>       [,1]  [,2]  [,3]  [,4]  [,5]
#> [1,] 0.000 0.125 0.250 0.375 0.500
#> [2,] 0.125 0.250 0.375 0.500 0.625
#> [3,] 0.250 0.375 0.500 0.625 0.750
#> [4,] 0.375 0.500 0.625 0.750 0.875
#> [5,] 0.500 0.625 0.750 0.875 1.000

Much better!

Let's use grid::rasterGrob() to make a graphical object and draw it.

library(grid)
g <- rasterGrob(
  image = mat,
  width = unit(1, "npc"),
  height = unit(1, "npc"), 
  interpolate = TRUE
)
grid.newpage()
grid.draw(g)

Since we have a grob, we can add it to a ggplot2 figure with ggplot2::annotation_custom().

library(ggplot2)

ggplot(mtcars, aes(factor(cyl))) +
  annotation_custom(
    grob = g, xmin = -Inf, xmax = Inf, ymin = -Inf, ymax = Inf
  ) + 
  geom_bar()

Hooray! We did it. But we're not done yet.

A few notes:

• It'd be nice to have a function that accepts a few arguments:
  • angle
  • resolution
  • colors to use
• Our code above is easy to read, but slow to execute. We need it to be faster.

Please feel free to copy the make_gradient() function below and improve upon it.

library(ggplot2) 
library(grid)
library(RColorBrewer)

make_gradient <- function(deg = 45, n = 100, cols = blues9) {
  cols <- colorRampPalette(cols)(n + 1)
  rad <- deg / (180 / pi)
  mat <- matrix(
    data = rep(seq(0, 1, length.out = n) * cos(rad), n),
    byrow = TRUE,
    ncol = n
  ) +
  matrix(
    data = rep(seq(0, 1, length.out = n) * sin(rad), n),
    byrow = FALSE,
    ncol = n
  )
  mat <- mat - min(mat)
  mat <- mat / max(mat)
  mat <- 1 + mat * n
  mat <- matrix(data = cols[round(mat)], ncol = n)
  grid::rasterGrob(
    image = mat,
    width = unit(1, "npc"),
    height = unit(1, "npc"), 
    interpolate = TRUE
  )
}

Example 1

g <- make_gradient(
  deg = 45, n = 500, cols = brewer.pal(9, "Spectral")
)

ggplot(mtcars, aes(factor(cyl))) +
  annotation_custom(
    grob = g, xmin = -Inf, xmax = Inf, ymin = -Inf, ymax = Inf
  ) + 
  geom_bar()

Example 2

g <- make_gradient(
  deg = 180, n = 500, cols = brewer.pal(9, "RdBu")
)

ggplot(mtcars, aes(factor(cyl))) +
  annotation_custom(
    grob = g, xmin = -Inf, xmax = Inf, ymin = -Inf, ymax = Inf
  ) + 
  geom_bar()

^{Created on 2019-02-06 by the reprex package (v0.2.1)}

Answer 3

I used Kamil Slowikowski's example to build a simpler function that generates linear gradients depending on a series of values. This can be of use if you have a relationship of some kind between three variables (eg. y~x*z where z also varies over x). Then you just plot y~x and have z~x as a color gradient in the background.

water.height <- seq(0, 5, 1)
y <- seq(0, 1500, length.out = 6)
z <- rnorm(6, 10, 1)
df <- data.frame(water.height, y, z)

grad_by_val <- function(x, y, cols = blues9) {
  require(grid)
  y <- y[order(x)]
  ys <- (y - min(y)) / diff(range(y))
  cols <- colorRamp(cols)(ys) / 256
  colnames(cols) <- c("red", "green", "blue")
  cols <- apply(cols, 1, function(z) do.call(rgb, as.list(z)))
  mat <- matrix(cols, ncol = length(x))
  rasterGrob(
    image = mat,
    width = unit(1, "npc"),
    height = unit(1, "npc"),
    interpolate = TRUE
  )
}

library(ggplot2)
ggplot(df, aes(water.height, y)) + geom_blank() + theme_bw() +
  annotation_custom(
    grob = grad_by_val(df$water.height, df$z),
    xmin = -Inf,
    xmax = Inf,
    ymin = -Inf,
    ymax = Inf
  ) +
  geom_point(
    size = 5,
    color = "#FFFFFF",
    fill = "#000000",
    shape = 21
  )

To add a legend see here.