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"))
#> }
#>
#> 
