Jamie R. Nuñez, Christopher R. Anderton, and Ryan S. Renslow recently introduced optimized color maps for the scientific community. This so-called "cividis" colormap is generated by optimizing the "viridis" colormap and is optimal for viewing by those with or without color vision deficiency (CVD), a different visual perception of colors that affects 8.5% of the human population. It is designed to be perfectly perceptually-uniform, both in regular form and also when converted to black-and-white, and can be perceived by readers with all forms of color blindness. The cividis colormap was developed as a Python module called "cmaputil".
Because of the high interest of the scientific community in R, we make this new colormap available for R!
This is how it looks like:
... and like this in action (coloring neutral landscape models from NLMR):
To install the developmental version of
cividis, use the following R code:
# install.packages("devtools") devtools::install_github("marcosci/cividis")
This is a basic example which shows you how to solve a common problem:
## basic example code # load packages library(NLMR) library(rasterVis) library(cividis) # simulate NLM x <- nlm_random(ncol = 100, nrow = 100) # plot it gplot(x) + geom_tile(aes(fill = value)) + labs(x = "Easting", y = "Northing") + theme_nlm() + scale_fill_cividis( na.value = "transparent", name = "", guide = ggplot2::guide_colorbar( barheight = ggplot2::unit(40, units = "mm"), barwidth = ggplot2::unit(1, units = "mm"), draw.ulim = FALSE, title.hjust = 0.5, title.vjust = 1.5, label.hjust = 0.5 )) -> p1 #> Scale for 'fill' is already present. Adding another scale for 'fill', #> which will replace the existing scale.