viridis, and its companion package viridisLite
provide a series of color maps that are designed to improve graph readability
for readers with common forms of color blindness and/or color vision deficiency.
The color maps are also perceptually-uniform, both in regular form and also when
converted to black-and-white for printing.
viridisLite provides the base functions for generating the color maps in base
R. The package is meant to be as lightweight and dependency-free as possible
for maximum compatibility with all the R ecosystem. viridis
provides additional functionalities, in particular bindings for ggplot2.
The latest version of viridis comes with 8 different color maps, and they are
all very pretty!!!
You can install viridis from CRAN by typing the following line in your R
console:
install.packages("viridis")
library(viridis)
If you prefer to install the development version from this GitHub repository,
simply copy the following lines of code in your R terminal and it should install
everything you need to use viridisLite on your computer:
if (!require("devtools"))
install.packages("devtools")
devtools::install_github("sjmgarnier/viridis")
library(viridis)
The color maps viridis, magma, inferno, and plasma were created by
Stéfan van der Walt (@stefanv) and Nathaniel Smith (@njsmith). If you want to know more about the
science behind the creation of these color maps, you can watch this
presentation of viridis by their authors at
SciPy 2015.
The color map cividis is a corrected version of 'viridis', developed by
Jamie R. Nuñez, Christopher R. Anderton, and Ryan S. Renslow, and originally
ported to R by Marco Sciaini (@msciain). More
info about cividis can be found in
this paper.
The color maps mako and rocket were originally created for the Seaborn
statistical data visualization package for Python. More info about mako and
rocket can be found on the
Seaborn website.
The color map turbo was developed by Anton Mikhailov to address the
shortcomings of the Jet rainbow color map such as false detail, banding and
color blindness ambiguity. More infor about turbo can be found
here.