Plotting training and test error rates of knn cross-validation in R

I have performed the following cross-validation knn (using the caret package) on the iris dataset. I am now trying to plot the training and test error rates for the result. Here is my attempt but I cannot get the error rates. Can anyone help me please?

library(caret)
data(iris)
sample <- sample(2, nrow(iris), replace=TRUE, prob=c(0.80, 0.20))

iris.training <- iris[sample == 1, 1:4]
iris.test <- iris[sample == 2, 1:4]

iris.trainLabels <- iris[sample == 1, 5]
iris.testLabels <- iris[sample == 2, 5]

# Combine training data and combine test data.
iris_train <- cbind(iris.trainLabels, iris.training)
iris_test <- cbind(iris.testLabels, iris.test)

trControl <- trainControl(method = "cv", number = 5)

# K values 1 3 5 7 9
k_values <- seq(from=1, to=10, by=2)

fit <- train(iris.trainLabels ~ ., method = "knn", tuneGrid = expand.grid(k = k_values), trControl = trControl, data = iris_train)

# Plot
bestK <- function(iris_train, iris.trainLabels, 
iris.testLabels) {
  ctr <- c(); cts <- c()
  for (k in length(k_values)) {
  fit <- train(iris.trainLabels ~ ., method = "knn", tuneGrid = expand.grid(k = k_values), trControl = trControl, data = iris_train)

  trTable <- prop.table(table(fit, iris.trainLabels))
  tsTable <- prop.table(table(fit, iris.testLabels))

  erTr <- trTable[1,2] + trTable[2,1]
  erTs <- tsTable[1,2] + tsTable[2,1]

  ctr <- c(ctr,erTr)
  cts <- c(cts,erTs)
} 
 err <- data.frame(k=k_values, trER=ctr, tsER=cts)
 return(err)
} 

err <- bestK(iris_train, iris.trainLabels, iris.testLabels)

plot(err$k,err$trER,type='o',ylim=c(0,.5),xlab="k",ylab="Error rate",col="blue")
lines(err$k,err$tsER,type='o',col="red")