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R package to generate colors from a list of 44 pre-defined palettes
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bhaskarvk/colormap
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This project is feature complete. There won't be any more development on this project.
This is an R package that allows you to generate colors from color palettes defined in Node.js'scolormap module. In total it provides 44 distinct palettes made from sequential and/or diverging colors. In addition to the pre defined palettes you can also specify your own set of colors.
There are also scale functions that can be used with ggplot2.
- 2016-11-15 0.1.4 With Viridis as default theme.
- 2016-10-21 0.1.3 Now on CRAN.
- 2016-09-06 Ability to generate a custom palette.
- 2016-08-30 Input Validation and ggplot2 scales.
- 2016-08-29 First Release.
- Thecolormap Node.js module which does all the heavylifting.
- TheV8 package which allows R code to call Javascript code.
- Bob Rudis'szoneparser package which I used as a skeleton for this pacakge.
- Simon Garnier'sviridis package for ggplot2 scale functions.
RequiresV8
if(!require("V8")) install.packages("V8")if(!require("devtools")) install.packages("devtools")devtools::install_github("bhaskarvk/colormap")
The main function iscolormap which takes 5 optional arguments
- colormap: A string representing one of the 44 built-in colormaps.You can use the
colormapslist to specify a value. e.g.colormaps$densityOR A vector of colors in hex e.g. c('#000000','#777777','#FFFFFF')OR A list of list e.g. list(list(index=0,rgb=c(255,255,255)),list(index=1,rgb=c(255,0,0))) - nshades: Number of colors to generate.
- format: one of 'hex', 'rgb', 'rgbaString'
- alpha: Between 0 & 1 to specify the transparency.
- reverse: Boolean. Whether to reverse the order of the colors returned or not.
library(colormap)# Defaults to 72 colors from the 'viridis' palette.scales::show_col(colormap(),labels=F)
# Specify a different palette from a list of pre-defined palette.scales::show_col(colormap(colormap=colormaps$temperature,nshades=20))
# Specify opacity value.scales::show_col(colormap(colormap=colormaps$temperature,nshades=20,alpha=0.7))
# Specify colormap as vector of colors.scales::show_col(colormap(colormap=c('#FFFFFF','#FF0000'),nshades=12))
# Specify colormap as list of lists.scales::show_col(colormap(colormap=list(list(index=0,rgb=c(0,255,0)),list(index=1,rgb=c(255,0,255))),nshades=12,alpha=0.65))
You can also get the colors in a 'rgb' matrix and a rgba string vector format
colormap(format='rgb',nshades=5)# As rgb#> [,1] [,2] [,3] [,4]#> [1,] 68 1 84 1#> [2,] 59 81 139 1#> [3,] 33 144 141 1#> [4,] 92 200 99 1#> [5,] 253 231 37 1colormap(format='rgbaString',nshades=10)# As rgba string#> [1] "rgba(68,1,84,1)" "rgba(71,39,117,1)" "rgba(62,72,135,1)"#> [4] "rgba(49,102,141,1)" "rgba(38,130,141,1)" "rgba(36,157,136,1)"#> [7] "rgba(55,181,120,1)" "rgba(109,204,88,1)" "rgba(176,221,49,1)"#> [10] "rgba(253,231,37,1)"
You also getscale_fill_colormap andscale_color_colormap functions for using these palettes in ggplot2 plots. Check?colormap::scale_fill_colormap for details.
ensureCranPkg<-function(pkg) {if(!suppressWarnings(requireNamespace(pkg,quietly=TRUE))) { install.packages(pkg) }}ensureCranPkg('ggplot2')library(ggplot2)# Continuous color scaleggplot(mtcars,aes(x=wt,y=mpg))+ geom_point(aes(color=hp))+ theme_minimal()+ scale_color_colormap('Horse Power',discrete=F,colormap=colormaps$viridis,reverse=T)
ggplot(mtcars,aes(x=wt,y=mpg))+ geom_point(aes(color=as.factor(cyl)))+ theme_minimal()+ scale_color_colormap('Cylinder',discrete=T,colormap=colormaps$warm,reverse=T)
Here are two choroplethes usingscale_fill_colormap.
ensureCranPkg('maptools')ensureCranPkg('scales')ensureCranPkg('ggplot2')ensureCranPkg('ggthemes')ensureCranPkg('devtools')if(!suppressWarnings(requireNamespace('albersusa',quietly=TRUE))) {devtools::install_github('hrbrmstr/albersusa')}library(maptools)#> Loading required package: sp#> Checking rgeos availability: TRUElibrary(scales)library(ggplot2)library(albersusa)library(ggthemes)library(colormap)us<- usa_composite()us_map<- fortify(us,region="fips_state")gg_usa<- ggplot(us@data, aes(map_id=fips_state,fill=pop_2014))+ geom_map(map=us_map,color='#ffffff',size=0.1)+ expand_limits(x=us_map$long,y=us_map$lat)+ theme_map()+ theme(legend.position="right")gg_usa+ coord_map("albers",lat0=30,lat1=40)+ scale_fill_colormap("State Population\n(2014 Estimates)",labels=comma,colormap=colormaps$copper,reverse=T,discrete=F)
counties<- counties_composite()counties_map<- fortify(counties,region="fips")gg_counties<- ggplot(counties@data, aes(map_id=fips,fill=census_area))+ geom_map(map=counties_map,color='#ffffff',size=0.1)+ expand_limits(x=counties_map$long,y=counties_map$lat)+ theme_map()+ theme(legend.position="right")gg_counties+ coord_map("albers",lat0=30,lat1=40)+ scale_fill_colormap("County Area",labels=comma,trans='log10',colormap=colormaps$freesurface_red,reverse=T,discrete=F)+ theme(#panel.border = element_rect(colour = "black", fill=NA, size=1),legend.position='bottom',legend.direction="horizontal")
Here is a plot showing all 44 pre-defined color palettes and the colors they generate.
ensureCranPkg('purrr')par(mfrow=c(44,1))par(mar=rep(0.25,4))purrr::walk(colormaps,function(x) { barplot(rep(1,72),yaxt="n",space=c(0,0),border=NA,col=colormap(colormap=x),main= sprintf("\n\n%s",x)) })
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R package to generate colors from a list of 44 pre-defined palettes
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