glcm_marginals

xplusy_k

xminusy_k

Functions for the calculation of marginal distributions from the GLCM matrix.
The partial sum of the matrix is used to determine the distribution over
the sum of neighbor pairs, returns a value for a given sum k.
The partial sum of the matrix is used to determine the distribution over
the sum of neighbor pairs, returns a value for a given difference of k.

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>.

Rowan Barker-Clarke

gtexture

Generalized Application of Co-Occurrence Matrices and Haralick
Texture

Raoul Wadhwa

Davis Weaver

Jacob Scott

glcm_marginals function

<dl><dt>glcm</dt>
<dd>square co-occurrence matrix</dd>
<dt>k</dt>
<dd>real integer (given difference)</dd></dl>

Arguments

Marginal distributions of the GLCM — glcm_marginals

<dl>

<dt>glcm</dt>
<dd>square co-occurrence matrix</dd>


<dt>k</dt>
<dd>real integer (given difference)</dd>

</dl>

glcm_marginals: Marginal distributions of the GLCM

Description

Usage

Value

Arguments