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Plotting a raster with the color ramp diverging around zero

I am trying to plot a map with positive and negative values.

All positive values should have red color while negative should have blue color and zero should have white just like in this sample plot with discrete colorsenter image description here

Below is the code I'm using:

library (rasterVis)
ras1 <- raster(nrow=10,ncol=10) 
set.seed(1) 
ras1[] <- rchisq(df=10,n=10*10) 
ras2=ras1*(-1)/2 
s <- stack(ras1,ras2) 
levelplot(s,par.settings=RdBuTheme())

Thanks very much for providing a general solution which can be applied in other mapping exercises as well.

like image 266
code123 Avatar asked Nov 17 '15 06:11

code123


2 Answers

I wrote a gist to do this. It takes a trellis object generated by rasterVis::levelplot, and a colour ramp, and plots the object with the colours diverging around zero.

Using your s, you can use it like this:

devtools::source_gist('306e4b7e69c87b1826db')
p <- levelplot(s)
diverge0(p, ramp='RdBu')

ramp should be the name of a RColorBrewer palette, a vector of colours to be interpolated, or a colorRampPalette.

enter image description here


Here's the source:

diverge0 <- function(p, ramp) {
  # p: a trellis object resulting from rasterVis::levelplot
  # ramp: the name of an RColorBrewer palette (as character), a character 
  #       vector of colour names to interpolate, or a colorRampPalette.
  require(RColorBrewer)
  require(rasterVis)
  if(length(ramp)==1 && is.character(ramp) && ramp %in% 
     row.names(brewer.pal.info)) {
    ramp <- suppressWarnings(colorRampPalette(brewer.pal(11, ramp)))
  } else if(length(ramp) > 1 && is.character(ramp) && all(ramp %in% colors())) {
    ramp <- colorRampPalette(ramp)
  } else if(!is.function(ramp)) 
    stop('ramp should be either the name of a RColorBrewer palette, ', 
         'a vector of colours to be interpolated, or a colorRampPalette.')
  rng <- range(p$legend[[1]]$args$key$at)
  s <- seq(-max(abs(rng)), max(abs(rng)), len=1001)
  i <- findInterval(rng[which.min(abs(rng))], s)
  zlim <- switch(which.min(abs(rng)), `1`=i:(1000+1), `2`=1:(i+1))
  p$legend[[1]]$args$key$at <- s[zlim]
  p$par.settings$regions$col <- ramp(1000)[zlim[-length(zlim)]]
  p
}

Note that, as suggested in @LucasFortini's post, the process is much simpler if you're happy to have the colorkey extend the same distance above and below zero, e.g.: levelplot(s,par.settings=RdBuTheme(), at=seq(-max(abs(cellStats(s, range))), max(abs(cellStats(s, range))), len=100)).

like image 55
jbaums Avatar answered Nov 15 '22 08:11

jbaums


This is something I do frequently with the script below:

library(colorRamps)
col5 <- colorRampPalette(c('blue', 'gray96', 'red'))  #create color ramp starting from blue to red
color_levels=20 #the number of colors to use
max_absolute_value=0.4 #what is the maximum absolute value of raster?
plot(img, col=col5(n=color_levels), breaks=seq(-max_absolute_value,max_absolute_value,length.out=color_levels+1) , axes=FALSE)

Using the data from here, here is an example output and actual script:

library(raster)
library(colorRamps)
mask_data=shapefile("D:/temp/so/Main_Hawaiian_Islands_simple3.shp")
img=raster("D:/temp/so/PPT_wet_minus_dry.tif")
col5 <- colorRampPalette(c('blue', 'gray96', 'red'))  #create color ramp starting from blue to red
color_levels=10 #the number of colors to use
max_absolute_value=max(abs(c(cellStats(img, min), cellStats(img, max)))) #what is the maximum absolute value of raster?
color_sequence=seq(-max_absolute_value,max_absolute_value,length.out=color_levels+1)
plot(img, col=col5(n=color_levels), breaks=color_sequence, axes=FALSE)
plot(mask_data, add=T)

enter image description here This may bother some as there are a lot of color bins on the negative range that are unused (like the example you provided). The modification below allows for the exclusion of the empty colors from the map legend:

n_in_class=hist(img, breaks=color_sequence, plot=F)$counts>0
col_to_include=min(which(n_in_class==T)):max(which(n_in_class==T))
breaks_to_include=min(which(n_in_class==T)):(max(which(n_in_class==T))+1)
plot(img, col=col5(n=color_levels)[col_to_include], breaks=color_sequence[breaks_to_include] , axes=FALSE)
plot(mask_data, add=T)

enter image description here

like image 30
Lucas Fortini Avatar answered Nov 15 '22 10:11

Lucas Fortini