khroma

R build status codecov

r-universe CRAN Version CRAN checks CRAN Downloads

Project Status: Active – The project has reached a stable, usable state and is being actively developed.

DOI

Overview

Color blindness affects a large number of individuals. When communicating scientific results colour palettes must therefore be carefully chosen to be accessible to all readers.

This R package provides an implementation of Okabe and Ito[1], Paul Tol[2] and Fabio Crameri[3] colour schemes. These schemes are ready for each type of data (qualitative, diverging or sequential), with colours that are distinct for all people, including colour-blind readers. This package also provides tools to simulate colour-blindness and to test how well the colours of any palette are identifiable. To simulate colour-blindness in production-ready R figures you may also be interested in the colorblindr package.

For specific uses, several scientific thematic schemes (geologic timescale, land cover, FAO soils, etc.) are implemented, but these colour schemes may not be colour-blind safe.

All these colour schemes are implemented for use with base R or ggplot2.

Installation

You can install the released version of khroma from CRAN:

install.packages("khroma")

And the development version from GitHub with:

# install.packages("remotes")
remotes::install_github("tesselle/khroma")

Usage

## Load packages
library(khroma)

## Install extra packages (if needed)
# install.packages(c("ggplot2", "spacesXYZ"))

Available palettes (click to expand)

## Get a table of available palettes
info()
#>             palette        type max missing
#> 1              broc   diverging 256    <NA>
#> 2              cork   diverging 256    <NA>
#> 3               vik   diverging 256    <NA>
#> 4            lisbon   diverging 256    <NA>
#> 5            tofino   diverging 256    <NA>
#> 6            berlin   diverging 256    <NA>
#> 7              roma   diverging 256    <NA>
#> 8               bam   diverging 256    <NA>
#> 9            vanimo   diverging 256    <NA>
#> 10           oleron   diverging 256    <NA>
#> 11           bukavu   diverging 256    <NA>
#> 12              fes   diverging 256    <NA>
#> 13            devon  sequential 256    <NA>
#> 14          lajolla  sequential 256    <NA>
#> 15           bamako  sequential 256    <NA>
#> 16            davos  sequential 256    <NA>
#> 17           bilbao  sequential 256    <NA>
#> 18             nuuk  sequential 256    <NA>
#> 19             oslo  sequential 256    <NA>
#> 20            grayC  sequential 256    <NA>
#> 21           hawaii  sequential 256    <NA>
#> 22            lapaz  sequential 256    <NA>
#> 23            tokyo  sequential 256    <NA>
#> 24             buda  sequential 256    <NA>
#> 25            acton  sequential 256    <NA>
#> 26            turku  sequential 256    <NA>
#> 27            imola  sequential 256    <NA>
#> 28           batlow  sequential 256    <NA>
#> 29          batlowW  sequential 256    <NA>
#> 30          batlowK  sequential 256    <NA>
#> 31            brocO  sequential 256    <NA>
#> 32            corkO  sequential 256    <NA>
#> 33             vikO  sequential 256    <NA>
#> 34            romaO  sequential 256    <NA>
#> 35             bamO  sequential 256    <NA>
#> 36           bright qualitative   7    <NA>
#> 37    high contrast qualitative   3    <NA>
#> 38          vibrant qualitative   7    <NA>
#> 39            muted qualitative   9 #DDDDDD
#> 40  medium contrast qualitative   6    <NA>
#> 41             pale qualitative   6    <NA>
#> 42             dark qualitative   6    <NA>
#> 43            light qualitative   9    <NA>
#> 44           sunset   diverging  11 #FFFFFF
#> 45             BuRd   diverging   9 #FFEE99
#> 46             PRGn   diverging   9 #FFEE99
#> 47           YlOrBr  sequential   9 #888888
#> 48       iridescent  sequential  23 #999999
#> 49 discrete rainbow  sequential  23 #777777
#> 50   smooth rainbow  sequential  34 #666666
#> 51        okabe ito qualitative   8    <NA>
#> 52     stratigraphy qualitative 175    <NA>
#> 53             soil qualitative  24    <NA>
#> 54             land qualitative  14    <NA>

Colour palettes and scales

colour() returns a palette function that when called with a single integer argument returns a vector of colours.

If crayon is installed on your machine and if the crayon.enabled option is set to TRUE with options(), colours will be nicely printed in the console. You can disable this feature by setting the crayon.enabled option to FALSE.

## Paul Tol's bright colour scheme
bright <- colour("bright")
bright(7)
#>      blue       red     green    yellow      cyan    purple      grey 
#> "#4477AA" "#EE6677" "#228833" "#CCBB44" "#66CCEE" "#AA3377" "#BBBBBB" 
#> attr(,"missing")
#> [1] NA
## Show the colour palette
plot_scheme(bright(7), colours = TRUE)

## Use with ggplot2
data(mpg, package = "ggplot2")

ggplot2::ggplot(data = mpg) +
  ggplot2::aes(x = displ, y = hwy, colour = class) +
  ggplot2::geom_point() +
  scale_colour_bright()

Diagnostic tools

Test how well the colours are identifiable

## Okabe & Ito's colour scheme
okabe <- colour("okabe ito")

set.seed(12345)
plot_map(okabe(8))

Compute CIELAB distance metric

DeltaE <- compare(okabe(8))
round(DeltaE, 2)
#>                black orange sky blue bluish green yellow  blue vermilion
#> orange         64.74                                                    
#> sky blue       60.95  53.61                                             
#> bluish green   50.51  42.87    34.69                                    
#> yellow         88.42  21.72    57.53        38.04                       
#> blue           39.23  55.35    22.31        38.40  70.37                
#> vermilion      49.36  22.24    52.27        54.36  43.71 49.62          
#> reddish purple 53.11  49.01    45.51        63.45  62.54 41.11     37.02

Simulate colour-blindness

plot_scheme_colourblind(okabe(8))

## ggplot2 default colour scheme
## (equally spaced hues around the colour wheel)
x <- scales::hue_pal()(8)
plot_scheme_colourblind(x)

Colour Schemes

Colour Schemes

Paul Tol and Fabio Crameri offer carefully chosen schemes, ready for each type of data, with colours that are:

See vignette("tol") and vignette("crameri") for a more complete overview.

Scientific colour schemes

The following scientific colour schemes are available:

More will be added in future releases (suggestions are welcome).

Contributing

Please note that the khroma project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.

References

[1] Okabe, M. & Ito, K. (2008). Color Universal Design (CUD): How to Make Figures and Presentations That Are Friendly to Colorblind People. URL: https://jfly.uni-koeln.de/color/.

[2] Tol, P. (2021). Colour Schemes. SRON. Technical Note No. SRON/EPS/TN/09-002. URL: https://personal.sron.nl/~pault/data/colourschemes.pdf.

[3] Crameri, F. (2018). Geodynamic diagnostics, scientific visualisation and StagLab 3.0. Geosci. Model Dev., 11, 2541-2562. https://doi.org/10.5194/gmd-11-2541-2018