https://github.com/jolars/qualpalr

Automatic Generation of Qualitative Color Palettes
https://github.com/jolars/qualpalr

color r visualization

Last synced: 2 months ago
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Automatic Generation of Qualitative Color Palettes

• Host: GitHub
• URL: https://github.com/jolars/qualpalr
• Owner: jolars
• License: gpl-3.0
• Created: 2016-08-28T10:28:12.000Z (over 8 years ago)
• Default Branch: main
• Last Pushed: 2024-09-09T12:59:49.000Z (4 months ago)
• Last Synced: 2024-09-09T15:31:32.939Z (4 months ago)
• Topics: color, r, visualization
• Language: C++
• Homepage: https://jolars.github.io/qualpalr/
• Size: 5.56 MB
• Stars: 23
• Watchers: 5
• Forks: 1
• Open Issues: 2
• Metadata Files:
  • Readme: README.md
  • Changelog: NEWS.md
  • License: LICENSE

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README

        


# qualpalr

[![R-CMD-check](https://github.com/jolars/qualpalr/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/jolars/qualpalr/actions/workflows/R-CMD-check.yaml)

[![Codecov test

coverage](https://codecov.io/gh/jolars/qualpalr/branch/master/graph/badge.svg)](https://app.codecov.io/gh/jolars/qualpalr?branch=master)

[![CRAN_Status_Badge](http://www.r-pkg.org/badges/version/qualpalr)](https://cran.r-project.org/package=qualpalr)

`qualpalr` generates distinct qualitative color palettes, primarily for

use in R graphics. Given `n` (the number of colors to generate), along

with a subset in the [hsl color

space](https://en.wikipedia.org/wiki/HSL_and_HSV) (a cylindrical

representation of the RGB color space) `qualpalr` attempts to find the

`n` colors in the provided color subspace that *maximize the smallest

pairwise color difference*. This is done by projecting the color subset

from the HSL color space to the DIN99d space. DIN99d is (approximately)

perceptually uniform, that is, the euclidean distance between two colors

in the space is proportional to their perceived difference.

`qualpalr` was inspired by [i want

hue](http://medialab.github.io/iwanthue/).

## Usage

Let’s create a palette of 4 colors of hues from 0 to 360, saturation

between 0.1 and 0.5, and lightness from 0.6 to 0.85.

``` r

library(qualpalr)

pal <- qualpal(n = 4, list(h = c(0, 360), s = c(0.1, 0.5), l = c(0.6, 0.85)))

```

We can retrieve the generated colors in hex format

``` r

pal$hex

#> [1] "#74C970" "#97B9DB" "#CD9675" "#C96AC1"

```

Alternatively, we can create a palette using one of the predefined color

subspaces and, optionally, adapt it to color deficiency (here

*deuteranomaly*).

``` r

pal2 <- qualpal(

  n = 4,

  colorspace = "pretty",

  cvd = "deutan",

  cvd_severity = 0.5

)

```

We can look at a distance matrix of the pairwise color differences from

the palette we have generated.

``` r

pal2$de_DIN99d

#>          #A07D68  #E6E1B5  #616FC8

#> #E6E1B5 17.90368                  

#> #616FC8 22.32321 27.55999         

#> #CEC9E8 19.65706 18.00590 17.82840

```

The palette may also be plotted with in a multidimensional scaling plot

generated from the distance matrix of the colors in the palette.

``` r

plot(pal2)

```

![](man/figures/README-plot-1.png)

Or it might be plotted in one of the provided color spaces as a

scatterplot matrix.

``` r

pairs(pal2, colorspace = "HSL")

```

![](man/figures/README-pairs-1.png)

## Installation

The current CRAN release can be installed by running

``` r

install.packages("qualpalr")

```

The development version can be installed by running

``` r

devtools::install_github("jolars/qualpalr")

```

## Versioning

Versioning is based on [semantic versioning](https://semver.org/).

## Code of conduct

Please note that this project is released with a [Contributor Code of

Conduct](https://github.com/jolars/qualpalr/blob/master/CONDUCT.md). By

participating in this project you agree to abide by its terms.

## License

`qualpalr` is open source software, licensed under

[GPL-3](https://github.com/jolars/qualpalr/blob/master/LICENSE).