charisma: Reproducible Color Characterization of Digital Images forBiological 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 + fileLICENSE |
| URL: | https://github.com/shawntz/charisma,https://shawnschwartz.com/charisma/ |
| NeedsCompilation: | no |
| Materials: | README,NEWS |
| CRAN checks: | charisma results |
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