Visualize the cuts in relation with the distribution of the data for each dimension in the original matrix
the output of the
which cuts to show. This must be one of "all", "fixed" or "combined". Any unambiguous substring can be given.
"fixed" will show
n equally spaced cuts (see
make.cut for the definition of
"combined" will show the cuts after adjustment for local minima and maxima.
"all" will show both. Setting
TRUE will enable the visualization of
local minima and maxima detected by the algorithm in each dimension.
the function returns an invisible 'NULL'.
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# generate a random 3D matrix with 2 peaks mat <- rbind(matrix(rnorm(300),ncol=3), matrix(rnorm(300,5,1),ncol=3)) dimnames(mat)[] <- LETTERS[1:3] # estimate the Hilbert order hilbert.order(mat) # generate 2 bins with a minimum bin size of 5 cuts <- make.cut(mat,n=3,count.lim=5) show.cut(cuts) # Generate the cuts cut.mat <- do.cut(mat,cuts,type='fixed') head(cut.mat)
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