show.cut: Plot the cuts generated through make.cut
In hilbertSimilarity: Hilbert Similarity Index for High Dimensional Data

Description Usage Arguments Details Value Author(s) Examples

Visualize the cuts in relation with the distribution of the data for each dimension in the original matrix

1	show.cut(cuts, type = "all", local = FALSE)

`cuts`	the output of the `make.cut`.
`type`	which cuts to show. This must be one of "all", "fixed" or "combined". Any unambiguous substring can be given.
`local`	defaults to `FALSE`; if `TRUE`, shows the local minima and maxima as a rug plot.

"fixed" will show n equally spaced cuts (see make.cut for the definition of n). "combined" will show the cuts after adjustment for local minima and maxima. "all" will show both. Setting local to TRUE will enable the visualization of local minima and maxima detected by the algorithm in each dimension.

the function returns an invisible 'NULL'.

Yann Abraham

# generate a random 3D matrix with 2 peaks
mat <- rbind(matrix(rnorm(300),ncol=3),
             matrix(rnorm(300,5,1),ncol=3))
dimnames(mat)[[2]] <- 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)