https://github.com/thomasp85/scico

Palettes for R based on the Scientific Colour-Maps
https://github.com/thomasp85/scico

color-palette rstats visualization

Last synced: 4 days ago
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Palettes for R based on the Scientific Colour-Maps

• Host: GitHub
• URL: https://github.com/thomasp85/scico
• Owner: thomasp85
• License: other
• Created: 2018-05-29T12:03:27.000Z (over 6 years ago)
• Default Branch: main
• Last Pushed: 2023-12-09T22:10:07.000Z (about 1 year ago)
• Last Synced: 2024-10-14T17:28:27.554Z (about 2 months ago)
• Topics: color-palette, rstats, visualization
• Language: R
• Size: 2.19 MB
• Stars: 412
• Watchers: 8
• Forks: 24
• Open Issues: 4
• Metadata Files:
  • Readme: README.Rmd
  • License: LICENSE

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• jimsghstars - thomasp85/scico - Palettes for R based on the Scientific Colour-Maps (R)

README

        
---

output: github_document

---

```{r, echo = FALSE}

knitr::opts_chunk$set(

  collapse = TRUE,

  comment = "#>",

  fig.path = "man/figures/README-"

)

```

# scico 

[![R-CMD-check](https://github.com/thomasp85/scico/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/thomasp85/scico/actions/workflows/R-CMD-check.yaml)

[![CRAN_Release_Badge](http://www.r-pkg.org/badges/version-ago/scico)](https://CRAN.R-project.org/package=scico)

[![Codecov test coverage](https://codecov.io/gh/thomasp85/scico/branch/main/graph/badge.svg)](https://app.codecov.io/gh/thomasp85/scico?branch=main)

This is a small package to provide access to the colour palettes developed by

Fabio Crameri and published at . It

uses more or less the same api as 

[`viridis`](https://github.com/sjmgarnier/viridis) and provides scales for 

[`ggplot2`](https://github.com/tidyverse/ggplot2) without requiring `ggplot2` to

be installed.

## Installation

`scico` can be installed from CRAN with `install.packages('scico')`. If you want

the development version then install directly from GitHub:

```{r, eval=FALSE}

# install.packages("devtools")

devtools::install_github("thomasp85/scico")

```

## Palettes

`scico` provides 39 different palettes, all of which are perceptually uniform 

and colourblind safe. An overview can be had with the `scico_palette_show()`

function:

```{r}

library(scico)

scico_palette_show()

```

Once you've decided on a palette you can generate colour values using the 

`scico()` function:

```{r}

scico(30, palette = 'lapaz')

```

## ggplot2 support

`scico` provides relevant scales for use with `ggplot2`. It only suggests 

`ggplot2` in order to stay lightweight, but if `ggplot2` is available you'll 

have access to the `scale_[colour|fill]_scico()` functions:

```{r, message=FALSE}

library(ggplot2)

volcano <- data.frame(

  x = rep(seq_len(ncol(volcano)), each = nrow(volcano)),

  y = rep(seq_len(nrow(volcano)), ncol(volcano)),

  height = as.vector(volcano)

)

ggplot(volcano, aes(x = x, y = y, fill = height)) + 

  geom_raster() + 

  scale_fill_scico(palette = 'davos') 

```

## References

- Crameri, Fabio. (2018, May 8). *Scientific colour maps (Version 3.0.1)*. Zenodo. doi: 10.5281/zenodo.1243909

- Crameri, Fabio. (2018). *Geodynamic diagnostics, scientific visualisation and StagLab 3.0*. Geosci. Model Dev. Discuss. doi: 10.5194/gmd-2017-328