scico
Colour Palettes Based on the Scientific Colour-Maps
Colour choice in information visualisation is important in order to avoid being mislead by inherent bias in the used colour palette. The 'scico' package provides access to the perceptually uniform and colour-blindness friendly palettes developed by Fabio Crameri and released under the "Scientific Colour-Maps" moniker. The package contains 24 different palettes and includes both diverging and sequential types.
scico 
This is a small package to provide access to the colour palettes
developed by Fabio Crameri and published at
http://www.fabiocrameri.ch/colourmaps.php. It uses more or less the
same api as viridis and
provides scales for ggplot2
without requiring ggplot2 to be installed.
Installation
scico can be installed from CRAN with install.packages('scico'). If
you want the development version then install directly from GitHub:
# install.packages("devtools")
devtools::install_github("thomasp85/scico")
Palettes
scico provides 39 different palettes, all of which are perceptually
uniform and colourblind safe. An overview can be had with the
scico_palette_show() function:
library(scico)
scico_palette_show()
Once you’ve decided on a palette you can generate colour values using
the scico() function:
scico(30, palette = 'lapaz')
#> [1] "#190C64" "#1C176B" "#202272" "#212B79" "#243580" "#263D86" "#29478B"
#> [8] "#2C5091" "#2F5996" "#33619A" "#37699D" "#3D71A0" "#4479A1" "#4D81A2"
#> [15] "#5688A4" "#608EA2" "#6B94A1" "#77999F" "#839E9C" "#90A198" "#9BA495"
#> [22] "#A9A895" "#B7AD96" "#C7B59C" "#D7BEA6" "#E5C9B3" "#F0D4C3" "#F7DFD3"
#> [29] "#FCE9E3" "#FEF2F2"
ggplot2 support
scico provides relevant scales for use with ggplot2. It only
suggests ggplot2 in order to stay lightweight, but if ggplot2 is
available you’ll have access to the scale_[colour|fill]_scico()
functions:
library(ggplot2)
volcano <- data.frame(
x = rep(seq_len(ncol(volcano)), each = nrow(volcano)),
y = rep(seq_len(nrow(volcano)), ncol(volcano)),
height = as.vector(volcano)
)
ggplot(volcano, aes(x = x, y = y, fill = height)) +
geom_raster() +
scale_fill_scico(palette = 'davos')
References
- Crameri, Fabio. (2018, May 8). Scientific colour maps (Version 3.0.1). Zenodo. doi: 10.5281/zenodo.1243909
- Crameri, Fabio. (2018). Geodynamic diagnostics, scientific visualisation and StagLab 3.0. Geosci. Model Dev. Discuss. doi: 10.5194/gmd-2017-328