Set transparency/saturation of palette in ggplot

Question

Let's start with the viridis palette. In my opinion, colours are a bit just too bright for me, and for my purposes they look too artificial. therefore, I would like to apply some sort of transparency or similar to reduce saturation:

library(nord)
library(scales)
library(viridis)
library(nord)

show_col(viridis(5))
show_col(viridis(5, alpha=.5))

Applying alpha transparency internally seems to work. .

However, when run in ggplot, it automatically changes alpha to 1 and plots the original viridis in full intensity:

ggplot(faithfuld, aes(waiting, eruptions)) +
  geom_raster(aes(fill = density)) +
  scale_fill_viridis(5, alpha=.5)

In another example, I found the opposite problem, lack of intensity/saturation. For example, the "aurora" palette from the nord package is great, but it looks a bit faded, lacking some saturation, at least for my purposes.

show_col(nord("aurora",5))

Similarly, I tried to set alpha internally, in this case to 1, but this pruduces a different effect as compared to viridis, changing the palette.

show_col(nord("aurora", alpha=.5))

Alternatively, I have set alpha as alpha(). However, this only changes the color names, but they look the same.

show_col(alpha(nord("aurora",5)), .5)

How can I reduce saturation/intensity in viridisand increase in the nord palettes in ggplot?

Answer 1

You can adjust the viridis colors to reduce their saturation without making them transparent. I was hoping you could do this within the viridis function, but it doesn't look like there's a way to do that. Instead, the example below is a function that converts a vector of hexadecimal input colors (we'll create this vector with the viridis function) to the hsv colorspace, adjusts the saturation and value levels and then converts back to hexadecimal.

The approach below is a bit convoluted. There are probably more direct ways to transform between color systems.

vir_lite = function(cols, ds=0.4, dv=0.7) {
  cols = rgb2hsv(col2rgb(cols))
  cols["v", ] = cols["v", ] + dv*(1 - cols["v", ])
  cols["s", ] = ds*cols["s", ]
  apply(cols, 2, function(x) hsv(x[1], x[2], x[3]))
}

Here are the original viridis colors:

show_col(viridis(5))

And the adjusted colors:

show_col(vir_lite(viridis(5)))

You can change the adjusted colors by changing the ds and dv arguments. Now let's use the adjusted colors in the plot:

p = ggplot(faithfuld, aes(waiting, eruptions)) +
      geom_raster(aes(fill = density))

p + scale_fill_gradientn(colors=vir_lite(viridis(5)))

p + scale_fill_gradientn(colors=vir_lite(viridis(5), ds=0.6, dv=0.5))