cluster_prom {gtexture}R Documentation

Cluster Prominence Metric for a GLCM

Description

Calculate the cluster prominence feature or metric for a gray-level co-occurrence matrix. For definition and application, see Lofstedt et al. (2019) doi:10.1371/journal.pone.0212110.

Usage

cluster_prom(x, ...)

## Default S3 method:
cluster_prom(x, ...)

## S3 method for class 'matrix'
cluster_prom(x, ...)

## S3 method for class 'FitLandDF'
cluster_prom(x, nlevels, ...)

Arguments

x

gray-level co-occurrence matrix

...

additional parameters

nlevels

desired number of discrete gray levels

Value

double

Examples

## calculate cluster prominence of arbitrary GLCM
# define arbitrary GLCM
x <- matrix(1:16, nrow = 4)

# normalize
n_x <- normalize_glcm(x)

# calculate cluster prominence
cluster_prom(n_x)

## calculate cluster prominence of arbitrary fitness landscape
# create fitness landscape using FitLandDF object
vals <- runif(64)
vals <- array(vals, dim = rep(4, 3))
my_landscape <- fitscape::FitLandDF(vals)

# calculate cluster prominence of fitness landscape, assuming 2 discrete gray levels
cluster_prom(my_landscape, nlevels = 2)

## confirm value of cluster prominence for fitness landscape
# extract normalized GLCM from fitness landscape
my_glcm <- get_comatrix(my_landscape, discrete = equal_discrete(2))

# calculate cluster prominence of extracted GLCM
cluster_prom(my_glcm)  # should match value of above cluster_prom function call

[Package gtexture version 1.0.0 Index]