https://github.com/rmaia/pavo

tools for the analysis of color data in R
https://github.com/rmaia/pavo

r

Last synced: 3 months ago
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tools for the analysis of color data in R

• Host: GitHub
• URL: https://github.com/rmaia/pavo
• Owner: rmaia
• License: gpl-2.0
• Created: 2012-01-31T01:13:24.000Z (almost 13 years ago)
• Default Branch: master
• Last Pushed: 2024-08-02T14:43:41.000Z (3 months ago)
• Last Synced: 2024-08-03T14:34:57.350Z (3 months ago)
• Topics: r
• Language: R
• Homepage: http://pavo.colrverse.com
• Size: 151 MB
• Stars: 68
• Watchers: 8
• Forks: 17
• Open Issues: 30
• Metadata Files:
  • Readme: README.md
  • Changelog: NEWS.md
  • Contributing: .github/CONTRIBUTING.md
  • License: LICENSE.md
  • Code of conduct: .github/CODE_OF_CONDUCT.md

Awesome Lists containing this project

• awesome-spectra - pavo
• jimsghstars - rmaia/pavo - tools for the analysis of color data in R (R)

README

        
# `pavo`

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

[![cran downloads](https://cranlogs.r-pkg.org/badges/grand-total/pavo)](https://cran.r-project.org/package=pavo/)

[![R build status](https://github.com/rmaia/pavo/workflows/R-CMD-check/badge.svg)](https://github.com/rmaia/pavo/actions)

[![cran checks](https://badges.cranchecks.info/worst/pavo.svg)](https://cran.r-project.org/web/checks/check_results_pavo.html)

## An `R` package for the spectral and spatial analysis of color patterns

### Currently maintained by [Thomas White](https://github.com/thomased) and [Hugo Gruson](https://github.com/bisaloo).

## About

`pavo` is an R package developed with the goal of establishing a flexible and integrated workflow for working with spectral and spatial colour data. It includes functions that take advantage of new data classes to work seamlessly from importing raw spectra and images, to visualisation and analysis. It provides flexible ways to input spectral data from a variety of equipment manufacturers, process these data, extract variables, and produce publication-quality figures.

`pavo` was written with the following workflow in mind:

- **Organise** data by importing and processing spectra and images (e.g., to remove noise, negative values, smooth curves, etc.).

- **Analyse** the resulting files, using spectral analyses of shape (hue, saturation, brightness), visual models based on perceptual data, and/or spatial adjacency and boundary strength analyses.

- **Visualise** the output, with multiple options provided for exploration, presentation, and analysis.

### Need more information, or help with the package?

- Take a look at the [package documentation](https://book.colrverse.com) for detailed examples and discussion.

- Check out the [latest news](http://pavo.colrverse.com/news/index.html) for changes and updates.

- **Need help or advice and can't find what you're looking for?** Head over to the [colRverse discussion board](https://github.com/colrverse/colRverse/discussions) and feel free to post a message.

- **If all else fails** (or you don't have a GitHub account), [email Tom](mailto:[email protected])!

## Citing pavo

The manuscript describing the current iteration of the package has been published and is free to access:

Maia R., Gruson H., Endler J.A., and White T.E. 2019 [pavo 2: New tools for the spectral 

and spatial analysis of colour in R](https://doi.org/10.1111/2041-210X.13174). _Methods in Ecology and Evolution_, 10(7):1097‑1107. 

## Install

This is the development page for `pavo`. The stable release is available from CRAN. Simply use `install.packages("pavo")` to install.

If you want to install the bleeding edge version of `pavo`, you can:

* use the [`remotes`](https://github.com/r-lib/remotes) package:

```r

# install.packages("remotes")

remotes::install_github("rmaia/pavo")

```

* download files from GitHub and install using `$R CMD INSTALL` or, from within R:

```r

install.packages(path, type = "source", repos = NULL)

```