Awesome
<!-- README.md is generated from README.Rmd. Please edit that file -->scico <img src="man/figures/logo.png" align="right" />
<!-- badges: start --> <!-- badges: end -->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()
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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')
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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