show.cut {hilbertSimilarity}

Plot the cuts generated through make.cut

Description

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

Usage

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

Arguments

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.

Details

"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.

Value

the function returns an invisible 'NULL'.

Author(s)

Yann Abraham

Examples

# 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)