charisma: Reproducible Color Characterization of Digital Images for
Biological Studies
Provides a standardized and reproducible framework for characterizing
and classifying discrete color classes from digital images of biological organisms.
The package automatically determines the presence or absence of 10 human-visible
color categories (black, blue, brown, green, grey, orange, purple, red, white, yellow)
using a biologically-inspired Color Look-Up Table (CLUT) that partitions HSV color space.
Supports both fully automated and semi-automated (interactive) workflows with complete
provenance tracking for reproducibility. Pre-processes images using the 'recolorize'
package (Weller et al. 2024 <doi:10.1111/ele.14378>) for spatial-color binning, and
integrates with 'pavo' (Maia et al. 2019 <doi:10.1111/2041-210X.13174>) for color
pattern geometry statistics. Designed for high-throughput analysis and seamless
integration with downstream evolutionary analyses.
| Version: |
1.0.0 |
| Depends: |
R (≥ 4.0.0) |
| Imports: |
magrittr, plyr, dplyr, tibble, purrr, tidyr, parallel, recolorize, imager, abind, jpeg, png, grDevices, graphics, stats, tools, utils |
| Suggests: |
pavo, testthat (≥ 3.0.0), knitr, rmarkdown, pkgdown |
| Published: |
2025-12-08 |
| DOI: |
10.32614/CRAN.package.charisma |
| Author: |
Shawn Schwartz 
[aut, cre, cph],
Whitney Tsai
[aut],
Elizabeth Karan
[aut],
Mark Juhn [aut],
Allison Shultz
[aut],
John McCormack
[aut],
Thomas Smith
[aut],
Michael Alfaro
[aut] |
| Maintainer: |
Shawn Schwartz <shawn.t.schwartz at gmail.com> |
| BugReports: |
https://github.com/shawntz/charisma/issues |
| License: |
MIT + file LICENSE |
| URL: |
https://github.com/shawntz/charisma,
https://shawnschwartz.com/charisma/ |
| NeedsCompilation: |
no |
| Materials: |
README, NEWS |
| CRAN checks: |
charisma results |
Documentation:
Downloads:
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