gtexture: Generalized Application of Co-Occurrence Matrices and Haralick Texture

Generalizes application of gray-level co-occurrence matrix (GLCM) metrics to objects outside of images. The current focus is to apply GLCM metrics to the study of biological networks and fitness landscapes that are used in studying evolutionary medicine and biology, particularly the evolution of cancer resistance. The package was developed as part of the author's publication in Physics in Medicine and Biology Barker-Clarke et al. (2023) <doi:10.1088/1361-6560/ace305>. A general reference to learn more about mathematical oncology can be found at Rockne et al. (2019) <doi:10.1088/1478-3975/ab1a09>.

Version: 1.0.0
Imports: dlookr, dplyr (≥ 1.0), fitscape (≥ 0.1), igraph, magrittr (≥ 2.0), rlang, tidyr
Suggests: stats, testthat
Published: 2024-04-08
DOI: 10.32614/CRAN.package.gtexture
Author: Rowan Barker-Clarke ORCID iD [aut, cre], Raoul Wadhwa ORCID iD [aut], Davis Weaver [aut], Jacob Scott ORCID iD [aut]
Maintainer: Rowan Barker-Clarke <rowanbarkerclarke at>
License: MIT + file LICENSE
URL: <>
NeedsCompilation: no
Materials: NEWS
CRAN checks: gtexture results


Reference manual: gtexture.pdf


Package source: gtexture_1.0.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): gtexture_1.0.0.tgz, r-oldrel (arm64): gtexture_1.0.0.tgz, r-release (x86_64): gtexture_1.0.0.tgz, r-oldrel (x86_64): gtexture_1.0.0.tgz


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