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) . A general reference to learn more about mathematical oncology can be found at Rockne et al. (2019) .


Reference manual

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install.packages("gtexture")

1.0.1 by Rowan Barker-Clarke, a year ago


https://rbarkerclarke.github.io/gtexture/


Report a bug at https://github.com/rbarkerclarke/gtexture/issues


Browse source code at https://github.com/cran/gtexture


Authors: Rowan Barker-Clarke [aut, cre] (ORCID: , Raoul Wadhwa [aut] , Davis Weaver [aut] , Jacob Scott [aut]


Documentation:   PDF Manual  


MIT + file LICENSE license


Imports dlookr, dplyr, fitscape, igraph, magrittr, rlang, tidyr

Suggests stats, testthat


See at CRAN