catmssim_2d {catsim}  R Documentation 
The categorical structural similarity index measure for 2D categorical or binary images for multiple scales. The default is to compute over 5 scales.
catmssim_2d(
x,
y,
levels = NULL,
weights = NULL,
window = 11,
method = "Cohen",
...,
random = "random"
)
x , y 
a binary or categorical image 
levels 
how many levels of downsampling to use. By default, 5. If

weights 
a vector of weights for the different scales. By default,
equal to 
window 
by default 11 for 2D and 5 for 3D images,
but can be specified as a
vector if the window sizes differ by dimension.
The vector must have the same number of
dimensions as the inputted 
method 
whether to use Cohen's kappa ( 
... 
additional constants can be passed to internal functions. 
random 
whether to have deterministic PRNG ( 
a value less than 1 indicating the similarity between the images.
set.seed(20181207)
x < matrix(sample(0:3, 128^2, replace = TRUE), nrow = 128)
y < x
for (i in 1:128) y[i, i] < 0
for (i in 1:127) y[i, i + 1] < 0
catmssim_2d(x, y, method = "Cohen", levels = 2) # the default
# now using a different similarity score (Jaccard Index)
catmssim_2d(x, y, method = "NMI")