This erosion algorithm removes counts from hexagon cells at a rate proportional to the cells' exposed surface area. When a cell becomes empty, algorithm removes the emptied cell and notes the removal order. Cell removal increases the exposure of any neighboring cells. The last cell removed is a type of bivariate median.
an object of class
number in (0,1) indicating the confidence level for the limits.
The algorithm extracts high count cells with containing a given fraction (cdfcut) of the total counts. The algorithm extracts all cells if cdfcut=0. The algorithm performs gray-level erosion on the extracted cells. Each erosion cycle removes counts from cells. The counts removed for each cell are a multiple of the cell's exposed-face count. The algorithm choses the multiple so at least one cell will be empty or have a count deficit on each erosion cycle. The erode vector contain an erosion number for each cell. The value of erode is
6*erosion\_cycle\_ at\_ cell\_ removal - cell\_deficit\_at\_removal
Cells with low values are eroded first. The cell with the highest erosion number is a candidate bivariate median. A few ties in erode are common.
"erodebin" object (with all the slots from
high count cells and a component
erode that gives the erosion order.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24
set.seed(153) x <- rnorm(10000) y <- rnorm(10000) bin <- hexbin(x,y) smbin <- smooth.hexbin(bin) erodebin <- erode.hexbin(smbin, cdfcut=.5) plot(erodebin) ## bivariate boxplot hboxplot(erodebin, main = "hboxplot(erodebin)") # show erosion order plot(bin,style= "lat", minarea=1, maxarea=1, legend=FALSE, border=gray(.7)) grid.hexagons(erodebin,style= "lat", minarea=1, maxarea=1,pen="green") xy <- hcell2xy(erodebin) library("grid") grid.text(lab = as.character(erodebin@erode), xy$x, xy$y, gp = gpar(col="white", cex=0.65))
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