Understanding Color Scales in Ggplot2

library(ggplot2)
cont <- ggplot(mtcars, aes(mpg, disp, color=cyl)) + geom_point(size=4)

cont + scale_color_continuous()

cont + scale_color_binned()

Name of Function	Colorspace	Legend	What it does
scale_color_continuous()	default	Colorbar	basic scale (as if you did nothing)
scale_color_gradient()	user-defined	Colorbar	define low and high values
scale_color_gradient2()	user-defined	Colorbar	define low mid and high values
scale_color_gradientn()	user_defined	Colorbar	define any number of incremental val
scale_color_binned()	default	Colorsteps	basic scale, but binned
scale_color_steps()	user-defined	Colorsteps	define low and high values
scale_color_steps2()	user-defined	Colorsteps	define low, mid, and high vals
scale_color_stepsn()	user-defined	Colorsteps	define any number of incremental vals
scale_color_viridis_c()	Viridis	Colorbar	viridis color scale. Change palette via option=.
scale_color_viridis_b()	Viridis	Colorsteps	Viridis color scale, binned. Change palette via option=.
scale_color_distiller()	Brewer	Colorbar	Brewer color scales. Change palette via palette=.
scale_color_fermenter()	Brewer	Colorsteps	Brewer color scale, binned. Change palette via palette=.

ggplot: scale_color_steps()-like color scale for ordered factors

This is one way to do it, though it feels a bit hacky. I'd be interested to see if there's a cleaner solution.

ggplot(df, aes(x, y, col = col)) +
  geom_point(aes(fill = col), key_glyph = draw_key_rect) +
  scale_color_manual(values = colorRampPalette(c("red", "blue"))(3)) +
  scale_fill_manual(values = colorRampPalette(c("red", "blue"))(3))

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Addendum

This version is a bit less hacky (in that you don't need to forge the guides and still use scale_color_steps), but it's still somewhat involved:

ggplot(df, aes(x, y, col = as.numeric(col))) +
  geom_point() +
  scale_color_steps(low = "blue", high = "red", 
                    breaks = seq(nlevels(df$col)), 
                    limits = c(0, nlevels(df$col) + 1),
                    labels = rev(levels(df$col)), name = "col")

Set continuous colour scale in ggplot2

Obviously we don't have your data, but using a simple random example should show the options here.

df <- data.frame(x = rnorm(10000), y = rnorm(10000), z = runif(10000))

Firstly, you could try scale_color_distiller with palette = "Spectral"

ggplot(df, aes(x, y, color = z)) +
  geom_point() +
  scale_color_distiller(palette = 'Spectral')

Another option is to specify a full palette yourself using scale_color_gradientn which allows for arbitrary gradients. This one is a reasonable match for the scale in your example image.

ggplot(df, aes(x, y, color = z)) +
  geom_point() +
  scale_color_gradientn(colours = c('#5749a0', '#0f7ab0', '#00bbb1',
                                    '#bef0b0', '#fdf4af', '#f9b64b',
                                    '#ec840e', '#ca443d', '#a51a49'))

Manual color scale function for ggplot2

You can play around with scale_fill_gradientn.

I think this gets you pretty close as a starting point:

ggplot(coord, aes(x = Re(coord), y = Im(coord), fill = it))+
  geom_raster()+
  theme_void()+
  coord_equal()+
  scale_fill_gradientn(colors = c("red", "orange", "gold", "yellow", "green", 
                                  "lightblue", "purple", "black"),
                       values = c(0, 0.3, 0.35, 0.4, 0.5 ,0.6, 0.99,1))

Using two scale colour gradients ggplot2

First, note that the reason ggplot doesn't encourage this is because the plots tend to be difficult to interpret.

You can get your two color gradient scales, by resorting to a bit of a cheat. In geom_point certain shapes (21 to 25) can have both a fill and a color. You can exploit that to create one layer with a "fill" scale and another with a "color" scale.

# dummy up data
dat1<-data.frame(log2=rnorm(50), p.value= runif(50))
dat2<-data.frame(log2=rnorm(50), p.value= runif(50))

# geom_point with two scales
p <- ggplot() +
       geom_point(data=dat1, aes(x=p.value, y=log2, color=p.value), shape=21, size=3) +
       scale_color_gradient(low="red", high="gray50") +
       geom_point(data= dat2, aes(x=p.value, y=log2, shape=shp, fill=p.value), shape=21, size=2) +
       scale_fill_gradient(low="gray90", high="blue")
p

How to specify manual color scale in ggplot2 of R?

Considering your sample, the mid point splits the data by 25% and 75% approximately.

Instead of having scale_color_gradient2 with three color calls, we can have scale_color_gradientn with four color calls and white as the second color (as the mid pint is just above 25%.

gg <-ggplot(df, aes(x=x, y=y, color=z)) + 
  geom_point() + 
  scale_color_gradientn(colors=c("red","white", "blue", "darkblue"), space ="Lab")

P.S.: You can also try colors=c("red","white", "lightblue", "blue")

ggplot2 custom scale color labels

Just add the breaks and labels argument of scale_color_gradient2:

ggplot(norm.values , aes(x=x, color=col, y=y)) + 
  geom_point(aes(shape=factor(size)), size=3 ) + 
  scale_color_gradient2(low="blue",mid="blue", high="red",
                       breaks=c(2,1,0,-1,-2),
                       labels = c(">2", "1", "0", "-1", "-2"))+
  xlab("chi lab") + 
  ylab("psi lab") +
  labs(color = "Kolor Lab" )+
  labs(shape = "Size Lab", size=20) +
  theme_classic() +
  theme(axis.text=element_text(size=14), axis.title=element_text(size=16), legend.text=element_text(size=18), strip.text.x = element_text(size = 14), strip.text.y = element_text(size = 14),  legend.title =   element_text(size = 18))

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