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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
 [aut, cre],
Raoul Wadhwa
[aut],
Davis Weaver [aut],
Jacob Scott [aut] |
| Maintainer: |
Rowan Barker-Clarke <rowanbarkerclarke at gmail.com> |
| BugReports: |
https://github.com/rbarkerclarke/gtexture/issues |
| License: |
MIT + file LICENSE |
| URL: |
<https://rbarkerclarke.github.io/gtexture/> |
| NeedsCompilation: |
no |
| Materials: |
NEWS |
| CRAN checks: |
gtexture results |
Documentation:
Downloads:
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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.