GMT standard color palettes

January 25, 2014
By

(This article was first published on me nugget, and kindly contributed to R-bloggers)

GMT (Generic Mapping Tools) (http://gmt.soest.hawaii.edu/) is a great mapping tool. I’m hoping to use it more in the future, but for the meantime I wanted to recreate some of the it’s standard color palettes in R. Unfortunately, I couldn’t find documentation of the precise rgb color levels used, so I ended up “stealing” them from the .png images on this website: http://www.geos.ed.ac.uk/it/howto/GMT/CPT/palettes.html

Here’s the result:

Here’s how I extracted the color levels from the .png images:

#make palettes
library(png)
 
pal.names <- c(
"cool","copper","gebco","globe",
"gray","haxby","hot","jet",
"no_green","ocean","polar","rainbow",
"red2green","relief","sealand","seis",
"split","topo","wysiwyg"
)
 
png.urls <- paste0("http://www.geos.ed.ac.uk/it/howto/GMT/CPT/cpt-", pal.names, ".png")
 
gmt.pals <- vector(mode="list", length(pal.names))
names(gmt.pals) <- pal.names
for(i in seq(gmt.pals)){
myurl <- png.urls[i]
tmp <- tempfile()
download.file(myurl,tmp,mode="wb")
pic <- readPNG(tmp)
file.remove(tmp) # cleanup
 
Colors <- NA * seq(20)
row <- round(dim(pic)[1]/2)
breaks <- seq(1, dim(pic)[2],,21)
cols <- round(breaks[-1] - ((breaks[2]-breaks[1])/2))
gmt.pals[[i]] <- rev(rgb(pic[row,cols,1], pic[row,cols,2], pic[row,cols,3])) # reverses colors to put low color values first in the vector
 
}
 
#plot of palettes
png("gmt_palettes.png", width=6, height=10, units="in", res=400)
op <- par(mar=c(0.25,0.25,1.25,0.25), mfrow=c(length(gmt.pals), 1), ps=10)
for(i in seq(gmt.pals)){
image(matrix(seq(gmt.pals[[i]]), length(gmt.pals[[i]])), 1, col=gmt.pals[[i]], axes=FALSE)
box()
mtext(names(gmt.pals)[i], side=3, line=0.1)
}
par(op)
dev.off()

Created by Pretty R at inside-R.org

Finally, I created a function (‘gmtColors‘) that allows me to call these color levels by GMT palette name:

#function 'gmtColors' to call color levels.
#palette name `pal.name` is one of the following:
#"cool", "copper", "gebco", "globe", "gray",
#"haxby", "hot", "jet", "no_green", "ocean",
#"polar", "rainbow", "red2green", "relief", "sealand",
#"seis", "split", "topo", "wysiwyg"
gmtColors <- function(pal.name="relief"){
tmp <- structure(list(cool = c("#00FFFF", "#0DF2FF", "#19E6FF", "#26D9FF",
"#33CCFF", "#3FBFFF", "#4CB3FF", "#59A6FF", "#6699FF", "#738CFF",
"#7F7FFF", "#8C73FF", "#9966FF", "#A659FF", "#B24DFF", "#BF3FFF",
"#CC33FF", "#D926FF", "#E619FF", "#F20DFF"), copper = c("#000000",
"#100906", "#1F130D", "#301E13", "#40281A", "#50321F", "#603C26",
"#70462D", "#805033", "#905A3A", "#A06440", "#B06E46", "#C0784D",
"#D08253", "#E08C5A", "#F09660", "#FFA066", "#FFAA6D", "#FFB473",
"#FFBE7A"), gebco = c("#00F0FF", "#00F0FF", "#00F0FF", "#23FFFF",
"#23FFFF", "#23FFFF", "#5AFFFF", "#5AFFFF", "#5AFFFF", "#8CFFE6",
"#8CFFE6", "#8CFFE6", "#A5FFD7", "#A5FFD7", "#A5FFD7", "#C3FFD7",
"#C3FFD7", "#C3FFD7", "#D2FFD7", "#E6FFF0"), globe = c("#9900FF",
"#9900FF", "#7722FF", "#5544FF", "#3366FF", "#1188FF", "#1BA4FF",
"#51BAFF", "#86D0FF", "#BCE6FF", "#336600", "#F3CA89", "#D9A627",
"#A49019", "#9F7B0D", "#996600", "#B27676", "#C2B0B0", "#E5E5E5",
"#FFFFFF"), gray = c("#000000", "#0D0D0D", "#191919", "#262626",
"#333333", "#3F3F3F", "#4C4C4C", "#595959", "#666666", "#737373",
"#7F7F7F", "#8C8C8C", "#999999", "#A6A6A6", "#B2B2B2", "#BFBFBF",
"#CCCCCC", "#D9D9D9", "#E6E6E6", "#F2F2F2"), haxby = c("#090079",
"#280096", "#0009C8", "#0019D4", "#1A66F0", "#19AFFF", "#32BEFF",
"#61E1F0", "#6AECE1", "#8AECAE", "#CDFFA2", "#DFF68D", "#F8D768",
"#FFBD57", "#F4754B", "#FF5A5A", "#FF7C7C", "#F6B3AE", "#FFC4C4",
"#FFECEC"), hot = c("#000000", "#220000", "#440000", "#660000",
"#880000", "#AA0000", "#CC0000", "#EE0000", "#FF1100", "#FF3300",
"#FF5500", "#FF7700", "#FF9900", "#FFBB00", "#FFDD00", "#FFFF00",
"#FFFF33", "#FFFF66", "#FFFF99", "#FFFFCC"), jet = c("#00007F",
"#0000B2", "#0000E5", "#0019FF", "#004DFF", "#007FFF", "#00B2FF",
"#00E5FF", "#FFFFF2", "#FFFFD9", "#FFFFBF", "#FFFFA5", "#FFFF8C",
"#FFE500", "#FFB300", "#FF7F00", "#FF4C00", "#FF1900", "#E50000",
"#B20000"), no_green = c("#1F60FF", "#1F60FF", "#1F9FFF", "#1FBFFF",
"#00CFFF", "#2AFFFF", "#2AFFFF", "#55FFFF", "#7FFFFF", "#AAFFFF",
"#FFFF54", "#FFFF54", "#FFF000", "#FFBF00", "#FFA800", "#FF8A00",
"#FF8A00", "#FF7000", "#FF4D00", "#FF0000"), ocean = c("#000000",
"#000209", "#000413", "#00061E", "#000728", "#000932", "#002650",
"#00426E", "#005E8C", "#007AAA", "#0096C8", "#22A9C2", "#45BCBB",
"#67CFB5", "#8AE2AE", "#ACF6A8", "#BCF8B9", "#CBF9CA", "#DBFBDC",
"#EBFDED"), polar = c("#0000FF", "#1919FF", "#3333FF", "#4C4CFF",
"#6666FF", "#7F7FFF", "#9999FF", "#B2B2FF", "#CCCCFF", "#E6E6FF",
"#FFFFFF", "#FFE5E5", "#FFCCCC", "#FFB2B2", "#FF9999", "#FF7F7F",
"#FF6666", "#FF4C4C", "#FF3333", "#FF1A1A"), rainbow = c("#FF00FF",
"#BF00FF", "#7F00FF", "#3F00FF", "#0000FF", "#003FFF", "#007FFF",
"#00BFFF", "#00FFFF", "#00FFBF", "#00FF7F", "#00FF3F", "#00FF00",
"#3FFF00", "#7FFF00", "#BFFF00", "#FFFF00", "#FFBF00", "#FF7F00",
"#FF3F00"), red2green = c("#FF0000", "#FF1919", "#FF3333", "#FF4C4C",
"#FF6666", "#FF7F7F", "#FF9999", "#FFB2B2", "#FFCCCC", "#FFE6E6",
"#FFFFFF", "#E5FFE5", "#CCFFCC", "#B2FFB2", "#99FF99", "#7FFF7F",
"#66FF66", "#4CFF4C", "#33FF33", "#1AFF1A"), relief = c("#000000",
"#000413", "#000728", "#002650", "#005E8C", "#0096C8", "#45BCBB",
"#8AE2AE", "#BCF8B9", "#DBFBDC", "#467832", "#887438", "#B19D48",
"#DBC758", "#FAE769", "#FAEB7E", "#FCED93", "#FCF1A7", "#FCF6C1",
"#FDFAE0"), sealand = c("#8C66FF", "#6A66FF", "#6684FF", "#66A7FF",
"#66CAFF", "#66ECFF", "#66FFF0", "#66FFCE", "#66FFAB", "#66FF88",
"#66FF66", "#88FF66", "#ABFF66", "#CEFF66", "#FFEEA6", "#FFD3A6",
"#FFB8A6", "#FFAAB0", "#FFB5CB", "#FFC0E1"), seis = c("#AA0000",
"#D00000", "#F70000", "#FF1D00", "#FF4400", "#FF6A00", "#FF9000",
"#FFB700", "#FFDD00", "#FFFF00", "#FFFF00", "#FFFF00", "#BDFF0C",
"#73FF1A", "#3FFA36", "#16F45A", "#00D08B", "#0087CD", "#0048FA",
"#0024E3"), split = c("#7F7FFF", "#6666E6", "#4D4DCC", "#3333B3",
"#1A1A99", "#00007F", "#000066", "#00004D", "#000033", "#00001A",
"#000000", "#1A0000", "#330000", "#4D0000", "#660000", "#7F0000",
"#991A1A", "#B33333", "#CC4D4D", "#E66666"), topo = c("#C977D9",
"#A18AE6", "#8AA2E6", "#8BD1E7", "#8AF3CF", "#85F38E", "#BDF385",
"#EDE485", "#F0B086", "#DE9F8B", "#74A3B3", "#99CC70", "#DCD68E",
"#EDDFAD", "#F7E8CA", "#FFF9F3", "#FFF9F6", "#FFFBF9", "#FFFCFA",
"#FFFEFD"), wysiwyg = c("#3F003F", "#3F003F", "#3F00BF", "#003FFF",
"#00A0FF", "#3FBFFF", "#3FBFFF", "#40E0FF", "#3FFFBF", "#3FFF3F",
"#7FFF3F", "#BFFF3F", "#BFFF3F", "#FFE040", "#FFE040", "#FF6040",
"#FF1F40", "#FF60C0", "#FFA0FF", "#FFA0FF")), .Names = c("cool",
"copper", "gebco", "globe", "gray", "haxby", "hot", "jet", "no_green",
"ocean", "polar", "rainbow", "red2green", "relief", "sealand",
"seis", "split", "topo", "wysiwyg"))
 
tmp[[match(pal.name, names(tmp))]]
}

Created by Pretty R at inside-R.org

To leave a comment for the author, please follow the link and comment on their blog: me nugget.

R-bloggers.com offers daily e-mail updates about R news and tutorials on topics such as: Data science, Big Data, R jobs, visualization (ggplot2, Boxplots, maps, animation), programming (RStudio, Sweave, LaTeX, SQL, Eclipse, git, hadoop, Web Scraping) statistics (regression, PCA, time series, trading) and more...



If you got this far, why not subscribe for updates from the site? Choose your flavor: e-mail, twitter, RSS, or facebook...

Comments are closed.

Sponsors

Mango solutions



plotly webpage

dominolab webpage



Zero Inflated Models and Generalized Linear Mixed Models with R

Quantide: statistical consulting and training

datasociety

http://www.eoda.de







ODSC

ODSC

CRC R books series





Six Sigma Online Training









Contact us if you wish to help support R-bloggers, and place your banner here.

Never miss an update!
Subscribe to R-bloggers to receive
e-mails with the latest R posts.
(You will not see this message again.)

Click here to close (This popup will not appear again)