Paul Tol’s Colour Schemes

N. Frerebeau

2021-06-14

library(khroma)

1 Introduction

Tol (2018) offers carefully chosen schemes, ready for each type of data, with colours that are:

All the scales presented in Paul Tol’s technical note (issue 3.1, 2018-09-23) are implemented here, for use with base R graphics or ggplot2.

2 Qualitative data

According to Paul Tol’s technical note, the bright, contrast, vibrant and muted colour schemes are colour-blind safe.

The light colour scheme is reasonably distinct for both normal or colour-blind vision and is intended to fill labelled cells.

The pale and dark schemes are not very distinct in either normal or colour-blind vision and should be used as a text background or to highlight a cell in a table.

The qualitative colour schemes must be used as given (no interpolation): colours are picked up to the maximum number of supported values. Refer to the original document for details about the recommended uses (see references).

Scheme Max. colours
bright 7
contrast 3
vibrant 7
muted 9
pale 6
dark 6
light 9

2.1 bright

bright <- colour("bright")
plot_scheme(bright(7), colours = TRUE, names = TRUE, size = 0.9)

2.2 contrast

contrast <- colour("contrast")
plot_scheme(contrast(3), colours = TRUE, names = TRUE, size = 0.9)

2.3 vibrant

vibrant <- colour("vibrant")
plot_scheme(vibrant(7), colours = TRUE, names = TRUE, size = 0.9)

2.4 muted

muted <- colour("muted")
plot_scheme(muted(9), colours = TRUE, names = TRUE, size = 0.9)

2.5 light

light <- colour("light")
plot_scheme(light(9), colours = TRUE, names = TRUE, size = 0.9)

2.6 pale and dark

pale <- colour("pale")
plot_scheme(pale(6), colours = TRUE, names = TRUE, size = 0.9)


dark <- colour("dark")
plot_scheme(dark(6), colours = TRUE, names = TRUE, size = 0.9)

3 Diverging data

If more colours than defined are needed from a given scheme, the colour coordinates are linearly interpolated to provide a continuous version of the scheme.

Scheme Num. of colours Bad data
sunset 11 #FFFFFF
BuRd 9 #FFEE99
PRGn 9 #FFEE99

3.1 sunset

sunset <- colour("sunset")
plot_scheme(sunset(9), colours = TRUE, size = 0.9)

3.2 BuRd

BuRd <- colour("BuRd")
plot_scheme(BuRd(9), colours = TRUE, size = 0.9)

3.3 PRGn

PRGn <- colour("PRGn")
plot_scheme(PRGn(9), colours = TRUE, size = 0.9)

4 Sequential data

If more colours than defined are needed from a given scheme, the colour coordinates are linearly interpolated to provide a continuous version of the scheme, with the exception of the discrete rainbow scheme (see below).

Scheme Num. of colours Bad data
YlOrBr 9 #888888
iridescent 23 #999999
discrete rainbow 23 #777777
smooth rainbow 34 #666666

4.1 YlOrBr

YlOrBr <- colour("YlOrBr")
plot_scheme(YlOrBr(9), colours = TRUE, size = 0.9)

4.2 iridescent

iridescent <- colour("iridescent")
plot_scheme(iridescent(23), colours = TRUE, size = 0.5)

4.3 rainbow

As a general rule, ordered data should not be represented using a rainbow scheme. There are three main arguments against such use (Tol 2018):

If such use cannot be avoided, Paul Tol’s technical note provides two colour schemes that are reasonably clear in colour-blind vision. To remain colour-blind safe, these two schemes must comply with the following conditions:

discrete rainbow
This scheme must not be interpolated.
smooth rainbow
This scheme does not have to be used over the full range (Tol 2018 suggests starting at purple).
discrete_rainbow <- colour("discrete rainbow")
plot_scheme(discrete_rainbow(14), colours = TRUE, size = 0.7)

When using the smooth rainbow scheme:

smooth_rainbow <- colour("smooth rainbow")

# Start at purple instead of off-white
plot(smooth_rainbow(256, range = c(0.25, 1)))

# End at red instead of brown
plot(smooth_rainbow(256, range = c(0, 0.9)))

5 Diagnostic maps

5.1 Qualitative colour schemes

Diagnostic maps for the bright, vibrant, muted and light (from top to bottom) qualitative colour schemes.Diagnostic maps for the bright, vibrant, muted and light (from top to bottom) qualitative colour schemes.