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https://github.com/ronammar/randomcoloR

An R package for generating attractive and distinctive colors.
https://github.com/ronammar/randomcoloR

Last synced: 3 months ago
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An R package for generating attractive and distinctive colors.

Host: GitHub
URL: https://github.com/ronammar/randomcoloR
Owner: ronammar
Created: 2016-02-20T21:10:52.000Z (over 8 years ago)
Default Branch: master
Last Pushed: 2020-05-03T16:56:52.000Z (about 4 years ago)
Last Synced: 2024-03-20T20:23:07.647Z (3 months ago)
Language: JavaScript
Size: 366 KB
Stars: 69
Watchers: 2
Forks: 9
Open Issues: 6
Metadata Files:
- Readme: README.md

Lists

awesome-r-dataviz - randomcoloR - An R package for generating attractive and distinctive colors. (ggplot / Palettes 🎨)

README

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

[![CRAN_Download_Badge](http://cranlogs.r-pkg.org/badges/randomcoloR)](https://CRAN.R-project.org/package=randomcoloR)

# randomcoloR

An [R](https://www.r-project.org/) package for generating attractive and distinctive colors.

The `randomColor()` function is ported from [randomColor.js](https://github.com/davidmerfield/randomColor).

Let's quickly get some pretty random colors.

```r

library(igraph)

library(randomcoloR)

k <- 200

plot(erdos.renyi.game(k, 0.1), vertex.label=NA,

     edge.lty="blank", vertex.color=randomColor(k))

```

![](readme_demo/graph1.png)

We can specify a particular hue, such as red.

```r

plot(erdos.renyi.game(k, 0.1), vertex.label=NA,

     edge.lty="blank", vertex.color=randomColor(k, hue="red"))

```

![](readme_demo/graph2.png)

We can also get random colors with specific luminosity.

```r

plot(erdos.renyi.game(k, 0.1), vertex.label=NA,

     edge.lty="blank", vertex.color=randomColor(k, luminosity="light"))

```

![](readme_demo/graph3.png)

We can also ask for a set of optimally distinct colors so that colors in our plot are not too similar.

If we use `ggplot2` to select the color space for our states in the map below, we get many similar colors.

```r

library(dplyr)

library(ggplot2)

library(maps)

states_map <- map_data("state")

ggplot(states_map, aes(x=long, y=lat, group=group, fill=region)) +

  geom_polygon(color="black") +

  guides(fill=FALSE)

```

*Which states are green?*

![](readme_demo/map1.png)

Instead, let's find the most distinctive set of colors for all states.

```r

ggplot(states_map, aes(x=long, y=lat, group=group, fill=region)) +

  geom_polygon(color="black") +

  scale_fill_manual(values=distinctColorPalette(length(unique(states_map$region)))) +

  guides(fill=FALSE)

```

*Now, which states are green?*

![](readme_demo/map2.png)

When using `ggplot2`, we can specify a custom color palette.

```r

ggplot(mtcars, aes(x=disp, y=mpg, col=as.factor(gear))) +

  geom_point(size=5) +

  scale_colour_manual(values=randomColor(length(unique(mtcars$gear)), luminosity="light")) +

  theme_bw()

```

![](readme_demo/mtcars_custom_palette.png)

You can use the default color space.

```r

set.seed(8675309)

scales::show_col(distinctColorPalette(12), labels=FALSE)

```

![](readme_demo/default_cs_12.png)

Or an alternate color space.

```r

scales::show_col(distinctColorPalette(12, altCol=TRUE), labels=FALSE)

```

![](readme_demo/alt_cs_12.png)

And you can preprocess the color space with t-SNE for improved color separation

in some circumstances

```r

scales::show_col(distinctColorPalette(12, altCol=TRUE, runTsne=TRUE), labels=FALSE)

```

![](readme_demo/alt_cs_tsne_12.png)

## Installation from Github

To install this package from Github via the R console, type:

```r

devtools::install_git("https://github.com/ronammar/randomcoloR")

```

It's also on [CRAN](https://cran.r-project.org/web/packages/randomcoloR/):

```r

install.packages("randomcoloR")

```