Package: charisma
Type: Package
Title: Reproducible Color Characterization of Digital Images for
        Biological Studies
Version: 1.0.0
Authors@R: c(
    person("Shawn", "Schwartz", email = "shawn.t.schwartz@gmail.com",
           role = c("aut", "cre", "cph"),
           comment = c(ORCID = "0000-0001-6444-8451")),
    person("Whitney", "Tsai", email = "wtsai@nhm.org",
           role = c("aut"),
           comment = c(ORCID = "0000-0003-3274-2829")),
    person("Elizabeth", "Karan", role = c("aut"), 
           comment = c(ORCID = "0000-0003-1942-0307")),
    person("Mark", "Juhn", role = c("aut")),
    person("Allison", "Shultz", email = "ashultz@nhm.org", 
           role = c("aut"), 
           comment = c(ORCID = "0000-0002-2089-4086")),
    person("John", "McCormack", role = c("aut"), 
           comment = c(ORCID = "0000-0002-0912-1461")),
    person("Thomas", "Smith", role = c("aut"), 
           comment = c(ORCID = "0000-0002-5978-6912")),
    person("Michael", "Alfaro", email = "michaelalfaro@g.ucla.edu", 
           role = c("aut"), 
           comment = c(ORCID = "0000-0002-8898-8230"))
    )
Description: 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.
License: MIT + file LICENSE
URL: https://github.com/shawntz/charisma,
        https://shawnschwartz.com/charisma/
BugReports: https://github.com/shawntz/charisma/issues
Encoding: UTF-8
LazyData: true
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
VignetteBuilder: knitr
RoxygenNote: 7.3.3
Roxygen: list(markdown = TRUE)
Config/testthat/edition: 3
Config/pak/sysreqs: libabsl-dev cmake libfftw3-dev libgdal-dev gdal-bin
        libgeos-dev libglpk-dev libmagick++-dev gsfonts libicu-dev
        libjpeg-dev libpng-dev libtiff-dev libxml2-dev libssl-dev
        libproj-dev libsqlite3-dev libudunits2-dev libx11-dev
Repository: https://shawntz.r-universe.dev
Date/Publication: 2026-04-10 05:56:55 UTC
RemoteUrl: https://github.com/shawntz/charisma
RemoteRef: HEAD
RemoteSha: cbe681c21e73167be001c322d6f6eabd0c6ad482
NeedsCompilation: no
Packaged: 2026-10-07 10:57:57 UTC; root
Author: Shawn Schwartz [aut, cre, cph] (ORCID:
    <https://orcid.org/0000-0001-6444-8451>),
  Whitney Tsai [aut] (ORCID: <https://orcid.org/0000-0003-3274-2829>),
  Elizabeth Karan [aut] (ORCID: <https://orcid.org/0000-0003-1942-0307>),
  Mark Juhn [aut],
  Allison Shultz [aut] (ORCID: <https://orcid.org/0000-0002-2089-4086>),
  John McCormack [aut] (ORCID: <https://orcid.org/0000-0002-0912-1461>),
  Thomas Smith [aut] (ORCID: <https://orcid.org/0000-0002-5978-6912>),
  Michael Alfaro [aut] (ORCID: <https://orcid.org/0000-0002-8898-8230>)
Maintainer: Shawn Schwartz <shawn.t.schwartz@gmail.com>