for inside foreach parallel not populating a dataframe in R - r

Question

I am having an issue populating a foreach. Suppose I have the following dataframe, the consequence of this dataframe is exactly what my real one looks like:
Elec2 <- rep(rep(rep(27:1, each = 81), each = 18), times = 100)
Ind <- rep(1:18, times = 218700)
Cond <- rep(1:3, times = 1312200)
Trial <- rep(rep(1:100, each = 2187), each = 18)
DVAR <- rbeta (3936600, 0.7, 1,5)
data <- cbind(DVAR, Ind, Cond, Trial, Elec1, Elec2)
I am trying the following code of parallelisation:
distinct_pairs <-
data %>%
select(Elec1, Elec2) %>%
distinct()
cl <- makeCluster(2) #values here are adjusted to cores, used 2 for the example
registerDoParallel(cl)
output <- foreach (i = 1:nrow(distinct_pairs), .packages='glmmTMB',
.combine = rbind,
.errorhandling="pass",
.verbose = T) %dopar% {
dep <- distinct_pairs[i,]
dat1 <- subset(data, dep$Elec1 == data$Elec1 & dep$Elec2 == data$Elec2)
df[i,]$Elec1 <- dep[i,]$Elec1
df[i,]$Elec2 <- dep[i,]$Elec2
for (j in 1:18) { #By individual
dat2 <- subset(dat1, dat1$Ind==j)
model <- glmmTMB(DVAR ~ Cond, family=beta_family('logit'), data=dat2)
results <- summary(model)
est <- results$coefficients$cond[2,1]
ste <- results$coefficients$cond[2,2]
df[j,] <- c(est,ste)
}
return(df)
}
output <- as.data.frame(output, row.names = FALSE)
As you can see I am expecting a dataframe with the results of the iterations est & ste plus the identification of the electrodes Elec1 & Elec2. If I run the lines independently one by one it seems to work fine, but i cannot make it work the way I expect.
First loop takes a pair of electrodes, every row in distinct_pairs is a pair of electrodes, numbered from 1 to 27 for Elec1 and for Elec2.
Problem is I am unable to get the data of the for loop written in the final output dataframe.
I am sure the problem is pretty basic, but I appreciate any insight as I seem to be missing something.
Thanks!
[[UPDATE WITH SOLUTION]]
In case anyone is interested, here is the solution.
output <- foreach (i = 1:10, .packages='glmmTMB',
.combine = rbind,
.errorhandling="pass",
.inorder = TRUE,
.verbose = T) %dopar% {
dat1 <- subset(data, distinct_pairs[i,]$Elec1 == data$Elec1 & distinct_pairs[i,]$Elec2 == data$Elec2)
df <- data.frame('Elec1'=rep(distinct_pairs[i,]$Elec1,18),'Elec2'=rep(distinct_pairs[i,]$Elec2,18),'est'=rep(NA,18),'ste'=rep(NA,18))
for (j in 1:18) {
dat2 <- subset(dat1, dat1$Ind==j)
model <- glmmTMB(DVAR ~ Condition, family=beta_family('logit'), data=dat2)
results <- summary(model)
est <- results$coefficients$cond[2,1]
ste <- results$coefficients$cond[2,2]
df[j,c('est','ste')] <- c(est,ste)
}
return(df)
}
Which returns exactly what I was looking for:
> head(output)
Elec1 Elec2 est ste
1 1 1 0.034798615 0.03530296
2 1 1 -0.005363760 0.03392442
3 1 1 -0.017349123 0.03404430
4 1 1 -0.034819068 0.03196078
5 1 1 0.002301062 0.03163825
6 1 1 0.003575131 0.03452420

Answer 1

I am definetly not sure if I got the problem, could you also provide an Elec1 in your data Example?
An idea:
Foreach might not find df, you could create the data frame at the beginning of your loop with something like
df <- data.frame('Elec1'=rep(NA,18),'Elec2'=rep(NA,18),'est'=rep(NA,18),'ste'=rep(NA,18))
maybe add then below in the for loop: df[j,c('est','ste')] <- c(est,ste)