The wacolor package contains 28 color palettes taken from the
landscapes and cities of Washington state. Colors were extracted from a
set of photographs, and then combined to form a set of continuous and
discrete palettes. Continuous palettes were designed to be perceptually
uniform, while discrete palettes were chosen to maximize contrast at
several different levels of overall brightness and saturation. Each
palette has been evaluated to ensure colors are distinguishable by
colorblind people.
Discrete palettes contain at most seven colors. Don’t create graphics that use more than seven discrete colors. You can color a map with four. Anything more risks confusion. Consider differentiating through faceting or labels, instead.
You can install the released version of wacolors from
CRAN with:
install.packages("wacolors")You can install the development version of wacolors from GitHub with:
devtools::install_github("CoryMcCartan/wacolors")It’s easy to select a palette. Access palettes through wacolors$...
for autocompletion suggestions.
library(wacolors)
library(ggplot2)
# See all palettes
names(wacolors)
#> [1] "rainier" "washington_pass" "palouse" "forest"
#> [5] "larch" "coast" "san_juan" "uw"
#> [9] "fort_worden" "skagit" "flag" "sound_sunset"
#> [13] "ferries" "forest_fire" "sea" "sea_star"
#> [17] "volcano" "baker" "diablo" "puget"
#> [21] "mountains" "gorge" "foothills" "footbridge"
#> [25] "olympic" "lopez" "vantage" "stuart"
# See one palette
wacolors$rainier
#> lake ragwort lodge trees ground winter_sky paintbrush
#> "#465177" "#E4C22B" "#965127" "#29483A" "#759C44" "#9FB6DA" "#DF3383"The package comes with ggplot2-compatible scales which are easy to
use.
# access by name
ggplot(mtcars, aes(mpg, wt)) +
geom_point(aes(color = factor(cyl), size=hp)) +
scale_color_wa_d("rainier")
# or access using `wacolors$...`
ggplot(diamonds) +
geom_bar(aes(x = cut, fill = clarity)) +
scale_fill_wa_d(wacolors$sound_sunset, reverse=TRUE)
You can use the wa_pal function to directly construct a
discretized/binned color scale.
image(volcano, col=wa_pal("ferries", 12))
image(volcano, col=wa_pal("vantage", 200, reverse=TRUE))
In case you do not wish to have wacolors as a dependency, you may use
the pal_vector() and pal_functions() functions, which generate
self-contained code for using the palettes. When using RStudio, this
code will be loaded, ready to copy, at the console prompt.
pal_vector("sound_sunset", 15)
#> PAL_SOUND_SUNSET = c("#001E35", "#0E2648", "#342C59", "#523368", "#6D3D71",
#> "#804C73", "#925B78", "#A16C7B", "#BB797D", "#D08B79",
#> "#DE9F71", "#E6B465", "#EBCC5B", "#E6E55B", "#DCFF6C")
pal_functions("palouse")
#> scale_color_palouse_d = function(...) {
#> pal_cols = c("#2D3F4A", "#C0A43D", "#8A6172", "#748A52", "#CCBA98",
#> "#69A2E4")
#> n_col = length(pal_cols)
#> ramp = grDevices::colorRampPalette(pal_cols)
#> pal_fun = function(n) if (n <= n_col) pal_cols[1:n] else ramp(n)
#> discrete_scale("color", "palouse", palette=pal_fun, ...)
#> }
#> scale_fill_palouse_d = function(...) {
#> pal_cols = c("#2D3F4A", "#C0A43D", "#8A6172", "#748A52", "#CCBA98",
#> "#69A2E4")
#> n_col = length(pal_cols)
#> ramp = grDevices::colorRampPalette(pal_cols)
#> pal_fun = function(n) if (n <= n_col) pal_cols[1:n] else ramp(n)
#> discrete_scale("fill", "palouse", palette=pal_fun, ...)
#> }
#>
#> scale_color_palouse_c = function(...) {
#> scale_color_gradientn(..., colours=c("#2D3F4A", "#C0A43D", "#8A6172",
#> "#748A52", "#CCBA98", "#69A2E4"))
#> }
#> scale_fill_palouse_c = function(...) {
#> scale_fill_gradientn(..., colours=c("#2D3F4A", "#C0A43D", "#8A6172",
#> "#748A52", "#CCBA98", "#69A2E4"))
#> }
#>
#> 
