Non-Linear Color Distribution Over the Range of Values in a Geom_Raster

Non-linear color distribution over the range of values in a geom_raster

Seems that ggplot (0.9.2.1) and scales (0.2.2) bring all you need (for your original m):

library(scales)

qn = quantile(m$fill, c(0.01, 0.99), na.rm = TRUE)
qn01 <- rescale(c(qn, range(m$fill))) 

ggplot(m, aes(x = x, y = y, fill = fill)) + 
   geom_raster() + 
   scale_fill_gradientn (
      colours = colorRampPalette(c("darkblue", "white", "darkred"))(20),
      values = c(0, seq(qn01[1], qn01[2], length.out = 18), 1)) +
   theme(legend.key.height = unit (4.5, "lines"))

Transform color scale to probability-transformed color distribution with scale_fill_gradientn()

This code will make manual breaks with a pnorm transformation. Is this what you are after?

ggplot(dat, aes(x = x, y = y, fill = z)) + 
  geom_tile(width=2, height=30) +
  scale_fill_gradientn(colours=fill.colors, 
                       trans = 'norm', 
                       breaks = quantile(dat$z, probs = c(0, 0.25, 1))
  )

gradient colour scale with gamma parameter?

Here is a possible solution,

set.seed(123)
x <- sort(runif(1e4, min=-20 , max=120))

library(scales) # rescale function

curve_pal <- function (x, colours = rev(blues9), 
                       fun = function(x) x^gamma,
                       n=10, gamma=1) 
{
    # function that maps [0,1] -> colours
    palfun <- colorRamp(colors=colours)

    # now divide the data in n equi-spaced regions, mapped linearly to [0,1]
    xcuts <- cut(x, breaks=seq(min(x), max(x), length=n))
    xnum <- as.numeric(xcuts)

    # need to work around NA values that make colorRamp/rgb choke
    testNA <- is.na(xnum)
    xsanitised <- ifelse(testNA, 0, fun(rescale(xnum))) 

    # non-NA values in [0,1] get assigned their colour
    ifelse(testNA, NA, rgb(palfun(xsanitised), maxColorValue=255))
}

library(gridExtra)
grid.newpage()
grid.arrange(rasterGrob(curve_pal(x, gamma=0.5), wid=1, heig=1, int=F),
             rasterGrob(curve_pal(x, gamma=1), wid=1, heig=1, int=F), 
             rasterGrob(curve_pal(x, gamma=2), wid=1, heig=1, int=F), 
             nrow=1)

ggplot geom_point() with colors based on specific, discrete values

You need to cut your values into intervals:

library(ggplot2)
ggplot(mtcars, aes(wt, mpg)) + 
  geom_point(aes(colour = cut(qsec, c(-Inf, 17, 19, Inf))),
             size = 5) +
  scale_color_manual(name = "qsec",
                     values = c("(-Inf,17]" = "black",
                                  "(17,19]" = "yellow",
                                  "(19, Inf]" = "red"),
                     labels = c("<= 17", "17 < qsec <= 19", "> 19"))

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