[R] package GeneSOM ?

[Jun Yan]

> But i miss or didn't find the possibility , extract the
> information  from the SOMplot "clusterSize" and "mean" for every cluster as quantitative information ( i.e. the DataFrame with an additional column which
> define the calculate clusters from SOM)?

Within a som object, code is a matrix with nrow = xdim*ydim, each row
corresponding to a code vector of a cell in the map. The mapping from cell
coordinate (x, y) to the row index in the code matrix is:
          rownumber = x + y * xdim
and hence (indexed from 0)
	x = (rownumber - 1) %% xdim
	y = (rownumber - 1) %/% xdim 

The "mean" for each cluster is contained in the row of code.
The "clustersize" could be obtained by the following function

somsum <- function(obj) {
  xdim <- obj$xdim
  ydim <- obj$ydim
  m <- nrow(obj$code)
  x <- (1:m - 1) %% xdim
  y <- (1:m - 1) %/% xdim
  f <- function(ii) {
    x <- (ii - 1) %% xdim 
    y <- (ii - 1) %/% xdim 
    ind <- obj$visual$x == x & obj$visual$y == y
    n <- length(ind[ind])
    n
  }
  nobs <- sapply(1:m, f)
  data.frame(x, y, nobs)
}

The output from this function could be put side by side with code using
cbind.

> My intention  -  compare calculate SOM results with other unsupervised classification results !
> 
> P.S. How i have got qerror to interpret ?

The qerror is calculated as an average of a weighted quantization error
for each sample:
\sum h_{ci} |x - m_i|^2

where the summation is taken over all the coding (mean) vector for the
sample, h_{ci} is the neighbouhood funcion, and m_i is the coding
vector. The default radius of neighbourhood is 1.

I am sorry it's not well documented. I will try to improve this over the
weekend.

Jun
 
> Thanks for advance & regards,
>  Christian

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