Gradient Breaks in a Ggplot Stat_Bin2D Plot

gradient breaks in a ggplot stat_bin2d plot

here is an example combining cut and bin2d:

p <- ggplot(df, aes(x, y, fill=cut(..count.., c(0,6,8,9,Inf))))
p <- p + stat_bin2d(bins = 20)
p + scale_fill_hue("count")

As there are many ways to make the breaks arbitrary, if you define clearly what you want, probably you can get a better answer.

Trying to apply color gradient on histogram in ggplot

This is a bit of a hacky answer, but it works:

##Define breaks
co2$brks<- cut(co2$rank, c(seq(0, 100, 5), max(co2$rank)))
#Create a plot object:
g = ggplot(data=co2, aes(x = tons, fill=brks)) +
   geom_dotplot(stackgroups = TRUE, binwidth = 0.05, method = "histodot")

Now we manually specify the colours to use as a palette:

 g + scale_fill_manual(values=colorRampPalette(c("white", "red"))( length(co2$brks) ))

Add a gradient of intensiy to an interference plot

Making use of patchwork this could be achieved like so:

1. For the gradient make a second ggplot of rectangles using e.g. geom_rect where you map intensity on color and/or fill
2. This gradient plot could then be glued to the main plot via patchwork

To get a nice gradient plot

1. I tripled the number of grid points for the gradient plot,
2. mapped the cubic root of intensity on color and
3. get rid of all unnecessary elemnts like y-axis, color guide, ...

BTW:

1. As your functions are vectorized you don't need lapply to compute the intensities.

2. Instead of adjusting the limits via xlim() (which removes rows falling outside of the range), set them using coord_cartesian.

library(ggplot2)
library(tibble)
library(patchwork)

a <- 5*10^(-6)
d <- 0.5*0.005
l <- 500*10^(-9)
n <- pi
theta <- seq(-n,n,length=3500)

I <- function(x){(cos((pi*d*sin(x))/l))^2*(sin((pi*a*sin(x))/l)/((pi*a*sin(x))/l))^2} 
y <- I(theta)
df <- data.frame(theta,y)

I2 <- function(x){(sin((pi*a*sin(x))/l)/((pi*a*sin(x))/l))^2}
y2 <- I2(theta)
df2 <- data.frame(theta,y2)

p1 = ggplot() + 
  geom_line(data = df, aes(theta,y)) + 
  geom_line(data = df2, aes(theta,y2)) +
  coord_cartesian(xlim = c(-0.3,0.3))

g <- tibble(
  xmin = seq(-n, n, length = 3 * 3500),
  xmax = dplyr::lead(xmin),
  y = I(xmin)
)

p2 <- ggplot(g, aes(xmin = xmin, xmax = xmax, ymin = 0, ymax = 1, color = y^(1/3))) +
  geom_rect() +
  coord_cartesian(xlim = c(-0.3,0.3)) +
  guides(color = FALSE) +
  theme_minimal() +
  theme(axis.ticks.y = element_blank(), axis.text.y = element_blank())

p1 / p2 + plot_layout(heights = c(10, 1))
#> Warning: Removed 1 rows containing missing values (geom_rect).

easiest way to discretize continuous scales for ggplot2 color scales?

The solution is slightly complicated, because you want a discrete scale. Otherwise you could probably simply use round.

library(ggplot2)

bincol <- function(x,low,medium,high) {
  breaks <- function(x) pretty(range(x), n = nclass.Sturges(x), min.n = 1)

  colfunc <- colorRampPalette(c(low, medium, high))

  binned <- cut(x,breaks(x))

  res <- colfunc(length(unique(binned)))[as.integer(binned)]
  names(res) <- as.character(binned)
  res
}

labels <- unique(names(bincol(iris$Sepal.Length,"blue","yellow","red")))
breaks <- unique(bincol(iris$Sepal.Length,"blue","yellow","red"))
breaks <- breaks[order(labels,decreasing = TRUE)]
labels <- labels[order(labels,decreasing = TRUE)]

ggplot(iris) + 
  geom_point(aes(x=Sepal.Width, y=Sepal.Length,
                 colour=bincol(Sepal.Length,"blue","yellow","red")), size=4) +
  scale_color_identity("Sepal.Length", labels=labels, 
                       breaks=breaks, guide="legend")

Count and axis labels on stat_bin2d with ggplot

stat_bin2d uses the cut function to create the bins. By default, cut creates bins that are open on the left and closed on the right. stat_bin2d also sets include.lowest=TRUE so that the lowest interval will be closed on the left also. I haven't looked through the code for stat_bin2d to try and figure out exactly what's going wrong, but it seems like it has to do with how the breaks in cut are being chosen. In any case, you can get the desired behavior by setting the bin breaks explicitly to start at -1. For example:

ggplot(data, aes(x = x, y = y)) +
  geom_bin2d(breaks=c(-1:4)) + 
  stat_bin2d(geom = "text", aes(label = ..count..), breaks=c(-1:4)) + 
  scale_fill_gradient(low = "snow3", high = "red", trans = "log10") + 
  xlim(-1, 5) +
  ylim(-1, 5) +
  coord_equal() 

To center the tiles on the integer lattice points, set the breaks to half-integer values:

ggplot(data, aes(x = x, y = y)) +
  geom_bin2d(breaks=seq(-0.5,4.5,1)) + 
  stat_bin2d(geom = "text", aes(label = ..count..), breaks=seq(-0.5,4.5,1)) + 
  scale_fill_gradient(low = "snow3", high = "red", trans = "log10") + 
  scale_x_continuous(breaks=0:4, limits=c(-0.5,4.5)) +
  scale_y_continuous(breaks=0:4, limits=c(-0.5,4.5)) +
  coord_equal()

Or, to emphasize that the values are discrete, set the bins to be half a unit wide:

ggplot(data, aes(x = x, y = y)) +
  geom_bin2d(breaks=seq(-0.25,4.25,0.5)) + 
  stat_bin2d(geom = "text", aes(label = ..count..), breaks=seq(-0.25,4.25,0.5)) + 
  scale_fill_gradient(low = "snow3", high = "red", trans = "log10") + 
  scale_x_continuous(breaks=0:4, limits=c(-0.25,4.25)) +
  scale_y_continuous(breaks=0:4, limits=c(-0.25,4.25)) +
  coord_equal()

stat_bin2d with fill based on success rate

You can use stat_summary2d:

ggplot(sweet, aes(interval, urgency, z = success)) + stat_summary2d()

Create discrete color bar with varying interval widths and no spacing between legend levels

I think the following answer is sufficiently different to merit a second answer. ggplot2 has massively changed in the last 2 years (!), and there are now new functions such as scale_..._binned, and specific gradient creating functions such as scale_..._fermenter

This has made the creation of a discrete gradient bar fairly straight forward.

For a "full separator" instead of ticks, see user teunbrands post.

library(ggplot2)

ggplot(iris, aes(Sepal.Length, y = Sepal.Width, fill = Petal.Length))+
  geom_point(shape = 21) +
  scale_fill_fermenter(breaks = c(1:3,5,7), palette = "Reds") + 
  guides(fill = guide_colorbar(
    ticks = TRUE, 
    even.steps = FALSE,
    frame.linewidth = 0.55, 
    frame.colour = "black", 
    ticks.colour = "black",
    ticks.linewidth = 0.3)) +
  theme(legend.position = "bottom")

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