Package: gtexture 0.1.0
Rowan Barker-Clarke
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 used in our publication, 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>.
Authors:
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gtexture.pdf |gtexture.html✨
gtexture/json (API)
| # Install 'gtexture' in R: |
| install.packages('gtexture', repos = c('https://rbarkerclarke.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/rbarkerclarke/gtexture/issues
Last updated 6 months agofrom:a70421439f. Checks:OK: 1 NOTE: 6. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Sep 06 2024 |
| R-4.5-win | NOTE | Sep 06 2024 |
| R-4.5-linux | NOTE | Sep 06 2024 |
| R-4.4-win | NOTE | Sep 06 2024 |
| R-4.4-mac | NOTE | Sep 06 2024 |
| R-4.3-win | NOTE | Sep 06 2024 |
| R-4.3-mac | NOTE | Sep 06 2024 |
Exports:%>%autocorrelationcluster_promcluster_shadecompute_all_metricscontrastcorrelationdiscretizeenergyentropyequal_discreteeuclideanget_comatrixhomogeneityinv_diffkmeans_discretemanhattanmax_probnormalize_glcmquantile_discretesum_squaresxplusy_k
Dependencies:AsioHeadersbackportsbase64encbitbit64bookdownbootbroombslibcachemclicliprcodetoolscolorspacecommonmarkcpp11crayondigestdlookrdplyrevaluateextrafontextrafontdbfansifarverfastmapfitscapefontawesomefontBitstreamVerafontLiberationfontquiverforcatsforeachfsgdtoolsgenericsggplot2glmnetgluegridExtragtablehavenhighrhmshrbrthemeshtmltoolshtmlwidgetshttpuvigraphisobanditeratorsjomojquerylibjsonlitekableExtraknitrlabelinglaterlatticelifecyclelme4magrittrMASSMatrixmemoisemgcvmicemimeminqamitmlmunsellnlmenloptrnnetnumDerivordinalpagedownpanpillarpkgconfigprettyunitsprocessxprogresspromisespspurrrR6rappdirsRColorBrewerRcppRcppEigenreactablereactRreadrrlangrmarkdownrpartrstudioapiRttf2pt1sassscalesservrshapeshinyshowtextshowtextdbsourcetoolsstringistringrsurvivalsvglitesysfontssystemfontstibbletidyrtidyselecttinytextzdbucminfutf8vctrsviridisLitevroomwebsocketwithrxfunxml2xtableyaml
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Autocorrelation Metric for a GLCM | autocorrelation autocorrelation.default autocorrelation.FitLandDF autocorrelation.matrix |
| Cluster Prominence Metric for a GLCM | cluster_prom cluster_prom.default cluster_prom.FitLandDF cluster_prom.matrix |
| Cluster Shade Metric for a GLCM | cluster_shade cluster_shade.default cluster_shade.FitLandDF cluster_shade.matrix |
| Calculate Co-Occurrence Matrix | comat get_comatrix get_comatrix.default get_comatrix.FitLandDF get_comatrix.igraph |
| Convenience function to compute all haralick texture features for a given comat | compute_all_metrics |
| Contrast Metric for a GLCM | contrast contrast.default contrast.FitLandDF contrast.matrix |
| Correlation Metric for a GLCM | correlation correlation.default correlation.FitLandDF correlation.matrix |
| Discretize Numeric Variable Into Categories | discretize discretize.FitLandDF discretize.integer discretize.list discretize.numeric |
| Energy Metric for a GLCM | energy energy.default energy.FitLandDF energy.matrix |
| Entropy Metric for a GLCM | entropy entropy.default entropy.FitLandDF entropy.matrix |
| Function Factory for Even Discretization Functions | equal_discrete |
| Euclidean Distance Function Factory | euclidean |
| GLCM Metrics | glcm_metrics glcm_variance xplusy_k |
| Homogeneity Metric for a GLCM | homogeneity homogeneity.default homogeneity.FitLandDF homogeneity.matrix |
| Inverse Difference Metric for a GLCM | inv_diff inv_diff.default inv_diff.FitLandDF inv_diff.matrix |
| Kmeans clustering discretization Splitting of a vector of continuous values into k groups function to discretize using kmeans | kmeans_discrete |
| Manhattan Distance Function Factory | manhattan |
| Maximum Probability Metric for a GLCM | max_prob max_prob.default max_prob.FitLandDF max_prob.matrix |
| Normalize a GLCM | normalize_glcm |
| Function to discretize based on quantiles | quantile_discrete |
| Sum of Squares Metric for a GLCM | sum_squares sum_squares.default sum_squares.FitLandDF sum_squares.matrix |