bdm.merge.s2nr {bigMap}

Merging of clusters based on signal-to-noise-ratio.

Description

Performs a recursive merging of clusters based on minimum loss of signal-to-noise-ratio (S2NR) until reaching the desired number of clusters. The S2NR is the explained/unexplained variance ratio measured in the high dimensional space based on the given low dimensional clustering.

Usage

bdm.merge.s2nr(bdm, k = 10, plot.merge = T, ret.merge = F,
  info = T, layer = 1, ...)

Arguments

bdm

A bdm instance as generated by bdm.init().

k

The number of desired clusters. The clustering will be recursively merged until reaching this number of clusters (default value is k = 10). By setting k < 0 we can specify the number of clusters that we are willing to merge.

plot.merge

Logical value. If TRUE, the merged clustering is plotted (default value is plot.merge = TRUE)

ret.merge

Logical value. If TRUE, the function returns a copy of the input bdm instance with the merged clustering attached as bdm$merge (default value is ret.merge = FALSE)

info

Logical value. If TRUE, all merging steps are shown (default value is info = FALSE).

layer

The bdm$ptsne layer to be used (default value is layer = 1).

...

If plot.merge is TRUE, you can set the bdm.wtt.plot() parameters to control the plot.

Details

See details in bdm.optk.s2nr().

Value

None if ret.merge = FALSE. Else, a copy of the input bdm instance with new element bdm$merge.

Examples

bdm.example()
exMap.labels <- bdm.labels(exMap)