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.
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")
scico
provides 17 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] "#190C65" "#1D196C" "#1E2575" "#202F7D" "#223A85" "#25448B" "#274E92"
#> [8] "#2A5898" "#2E629D" "#336CA1" "#3774A3" "#3F7DA5" "#4886A6" "#528EA6"
#> [15] "#5F95A5" "#6C9AA3" "#7A9E9F" "#87A19A" "#95A494" "#A2A58F" "#ADA78B"
#> [22] "#BBA989" "#CAAD8A" "#DBB592" "#EBC0A0" "#F6CCB0" "#FBD7C2" "#FDE0D2"
#> [29] "#FFEAE2" "#FFF2F2"
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')
- 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