Accessing R Self Organizing Map Codebook Vectors - r

Question

I am working to use SOMs to help analyze variability of weather forecast model ensembles. To do so, access a 20 ensemble global weather forecast model over a specific geographic domain. I convert a 20 x Nlat x Nlon matrix to a 20 x Nlat*Nlon matrix, present it to the Kohonen package som function. I then seek to access the som "codebook vector" output and transform it back to the latitude longitude grid. I am, however, receiving an error message at this step.
The error message I recieve is:
'Error in var.som$codes[i, ] : incorrect number of dimensions.' In this case, var.som is the Kohonen object. I loop from N = 1:Nsom, where Nsom is the number of "maps" specified in the call to the som function.
The attribute data for var.som indicates the size of the list var.som$codes is
"num [1:4, 1:500]", suggesting two dimensions, which is why I think my code should work. I have tried different permutations to access the list data but none work. I.e. var.som$codes[1], and var.som$codes[[1]] but they do not solve the problem. var.som$codes[1,1] yields NULL.
In the R script below, I have reduced the process to only the essential steps. A random number generator replaces the accessing of the weather model data. In the code, I indicate the location of where the error occurs and what the error message is.
Help and guidance for how to access the var.som$codes one codebook vector at a time is appreciated.
# An R script that provides an example of using a Self Organizing Map to calucate a SOM from latitude/longitude
# data. An error occurs fails accessing the SOM data vector codes.
library("kohonen")
# Set a few parameters
Nlon <- 20 # Number of longitude points
Nlat <- 25 # Number of latitude points
Nens <- 20 # number of ensemble members
Nsom <- 4 # number of "maps" in SOM
t2m.en <- as.list(rep(0,Nens))
# Generate Nlon * Nlat random numbers for Nens ensembles
for (i in 1:Nens) {
t2m.en[[i]] <- runif(Nlon*Nlat, -5, 5)
}
#array containing ensemble data
t2m.ens <- array(unlist(t2m.en),dim=c(20,Nlon,Nlat))
t2m.vec <- matrix(t2m.ens, nrow=20, ncol=Nlat*Nlon, byrow=TRUE)
# remove the column mean from each column of data (i.e. each grid point)
t2m.scaled <- apply(t2m.vec, 2, scale, scale=FALSE, center=TRUE)
rm(t2m.en)
# LOOP OVER THE VARIABLES TO PLOT
# Conduct the SOM analysis
var.som <- som(t2m.scaled, grid = somgrid(2,2, "rectangular"))#, keep.data=TRUE))
var.vecc = mat.or.vec(Nlat*Nlon, Nsom)
#populate var.vecc with the SOM output maps
for (i in 1:Nsom) {
print(i)
## THIS IS WHERE THE ERROR IS
var.vecc[,i] <- var.som$codes[i,]
## The Error Message is:
## Error in var.som$codes[i, ] : incorrect number of dimensions
}
#var.som$codes[1]
# Plot data from var.vecc on a map

Answer 1

Try: var.vecc[,i]<-var.som$codes[[1]][i,]