In tesselle/khroma: Colour Schemes for Scientific Data Visualization

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  out.width = "100%"
)

library(khroma)

Introduction

Tol (2021) offers carefully chosen schemes, ready for each type of data, with colors that are:

• Distinct for all people, including color-blind readers,
• Distinct from black and white,
• Distinct on screen and paper,
• Matching well together.

All the scales presented in Paul Tol's technical note (issue 3.2, 2021-08-18) are implemented here, for use with base R graphics, ggplot2 or ggraph.

Qualitative data

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

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

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

The qualitative color schemes must be used as given (no interpolation): colors 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. colors | |:------------------|-------------:| | bright | 7 | | high contrast | 3 | | vibrant | 7 | | muted | 9 | | medium contrast | 3 | | pale | 6 | | dark | 6 | | light | 9 |

bright

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

high contrast

highcontrast <- color("high contrast")
plot_scheme(highcontrast(3), colours = TRUE, names = TRUE, size = 0.9)

vibrant

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

muted

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

medium contrast

mediumcontrast <- color("medium contrast")
plot_scheme(mediumcontrast(6), colours = TRUE, names = TRUE, size = 0.9)

pale and dark

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

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

light

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

Diverging data

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

| Scheme | Num. of colors | Bad data | |:------------|----------------:|---------:| | sunset | 11 | #FFFFFF | | nightfall | 17 | #FFFFFF | | BuRd | 9 | #FFEE99 | | PRGn | 9 | #FFEE99 |

sunset

sunset <- color("sunset")
plot_scheme(sunset(11), colours = TRUE, size = 0.9)

nightfall

nightfall <- color("nightfall")
plot_scheme(nightfall(17), colours = TRUE, size = 0.9)

BuRd

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

PRGn

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

Sequential data

If more colors than defined are needed from a given scheme, the color 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 colors | Bad data | |:-------------------|----------------:|---------:| | YlOrBr | 9 | #888888 | | iridescent | 23 | #999999 | | incandescent | 11 | #888888 | | discrete rainbow | 23 | #777777 | | smooth rainbow | 34 | #666666 |

YlOrBr

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

iridescent

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

incandescent

incandescent <- color("incandescent")
plot_scheme(incandescent(11), colours = TRUE, size = 0.5)

rainbow

As a general rule, ordered data should not be represented using a rainbow scheme. There are three main arguments against such use (Tol 2021):

• The spectral order of visible light carries no inherent magnitude message.
• Some bands of almost constant hue with sharp transitions between them, can be perceived as jumps in the data.
• Color-blind people have difficulty distinguishing some colors of the rainbow.

If such use cannot be avoided, Paul Tol's technical note provides two color schemes that are reasonably clear in color-blind vision. To remain color-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 (2021) suggests starting at purple.

discrete_rainbow <- color("discrete rainbow")
plot_scheme(discrete_rainbow(14), colours = TRUE, size = 0.7)

When using the smooth rainbow scheme:

• Start off-white instead of purple if the lowest data value occurs often;
• End at red instead of brown the highest data value occurs often.

smooth_rainbow <- color("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)))

Diagnostic maps

Qualitative color schemes

set.seed(12345)
plot_map(bright(7))
plot_map(vibrant(7))
plot_map(muted(9))
plot_map(light(9))

Diverging schemes

set.seed(12345)
plot_map(sunset(11))
plot_map(nightfall(17))
plot_map(BuRd(9))
plot_map(PRGn(9))

plot_tiles(color("sunset")(128), n = 256)
plot_tiles(color("nightfall")(128), n = 256)
plot_tiles(color("BuRd")(128), n = 256)
plot_tiles(color("PRGn")(128), n = 256)

Sequential schemes

set.seed(12345)
plot_map(YlOrBr(9))
plot_map(iridescent(23))
plot_map(incandescent(11))
plot_map(discrete_rainbow(14))
plot_map(smooth_rainbow(23))

plot_tiles(color("YlOrBr")(128), n = 256)
plot_tiles(color("iridescent")(128), n = 256)
plot_tiles(color("incandescent")(128), n = 256)
plot_tiles(color("smooth rainbow")(128), n = 256)

References

Tol, P. 2021. "Colour Schemes." Technical note SRON/EPS/TN/09-002 3.2. SRON. URL: https://personal.sron.nl/~pault/data/colourschemes.pdf.

tesselle/khroma documentation built on Jan. 15, 2024, 9:15 p.m.