function lapply error : subscript out of bounds - r

Question

I have to make a 4*4 Kohonen map for a project.
However, I get the error
Error in win_index[1, ] : subscript out of bounds
In addition: There were 16 warnings (use warnings() to see them)
After testing my code, I guess it's the lapply function (line 77) that doesn't
is not executed correctly because the matrix thus created contains only NA.
And so since this matrix is used later on, the result is not correct because
NA is present throughout the program.
#############################################
##Function for distance calculation (RMSDA)##
#############################################
RMSDA<-function(data_phipsi,Kohonen_matrix)
{
difference<-data_phipsi-Kohonen_matrix
for(j in 1:length(difference)){
if (difference[j]< -180) {difference[j]=difference[j]+360}
if (difference[j]> +180) {difference[j]=difference[j]-360}
}
distance=mean(sqrt(difference^2))
return(distance)
}
##############################
## Program ###
##############################
for(step in 1:iteration)
{
data_phipsi<-data_phipsi[sample(nrow(data_phipsi)),] # Sample vectors of training (samples of lines of the dataframe)
print(step) #Visualize where we are in loops
for(k_row in 1:nrow(data_phipsi))
{
#Update learn_rate and radius at each row of each iteration
learn_rate<-learning(initial_rate,((step-1)*nrow(data_phipsi))+k_row,data_phipsi)
learn_radius<-learning(initial_rate,((step-1)*nrow(data_phipsi))+k_row,data_phipsi)
#Find distance between each vectors of angles of Kohonen Map and the training vector
phipsi_RMSDA<-lapply(random_list, RMSDA, data_phipsi=data_phipsi[k_row,])
}
How is it possible to fix this lapply error?
Thank you. Thank you.
edit : These are the only useful elements for the lapply
For the random list we can use:
random_list <- list(
c(88, 148, 60, 83, -119, -59, -96, 169),
c(104, 101, 174, -48, 18, 10, -159, 158),
c(164, -80, 137, -170, -172, 52, -149, 96),
c(88, 18, -115, 48, -3, -158, -92, -154),
c(170, -107, -109, -14, -142, -77, -120, 76),
c(-121, 15, -46, -145, -128, 74, -166, 44),
c(46, -178, 67, -88, -125, -130, 88, -11),
c(131, 147, -32, 103, -16, 116, 78, -125),
c(75, -95, -137, 133, -97, -134, 126, -105),
c(115, 173, -82, -135, 134, 82, -143, -43),
c(111, 13, -54, -53, 103, 132, -13, -43),
c(-143, 89, -91, -137, -63, 14, -166, 83),
c(-98, 178, 14, -80, -122, -25, 19, 117),
c(-113, -97, 34, -178, -56, 18, -167, 84),
c(49, 82, 50, 168, -157, -154, 51, 78),
c(173, -4, 164, 125, 31, 115, -74, -92)
)
and a exemple for
data_phipsi[1,]
data_phipsi <- read.table(header = TRUE, text = "
phi1 psi2 phy2 psi3 phy3 psi4 phy4 psi5
-24.5 81.9 -155.2 -81.4 127.7 -118 166 -82.1")
data_phipsi
# phi1 psi2 phy2 psi3 phy3 psi4 phy4 psi5
# 1 -24.5 81.9 -155.2 -81.4 127.7 -118 166 -82.1

Answer 1

The main issue was that a follow-on command (check back in the question edits for the win_index line of code, if interested) was failing because the results from lapply were suspect.
Troubleshooting that found the problem:
when the error hits, the value of both random_list and data_phipsi[k_row,] were reasonable and not suspect;
however, the output from lapply was all NA
So diving into the function RMSDA, it was noticed that difference looked fine up until
distance=mean(sqrt(difference^2))
at which point it turned all-NA. The problem is that the data was still in a form of a frame, so mean was failing (just try mean(mtcars) to see). (It should also be noted that I believe sqrt(difference^2) is equivalent to abs(difference).)
Replacing that line of RMSDA with
distance=mean(abs(unlist(difference)))
seems to have fixed the problem (the critical part being unlist).