Conditional Max/Min values within group_by in R - r

Question

I have been searching for an answer to this for a while without much luck so fingers crossed someone can help me!
I am dealing with cyclical data and I am trying to find the associated value of the two peaks and two troughs - this doesn't necessary equate to the max/min and second max/min values but rather the max/min and then the second max/min values conditional on the value being larger/smaller than the preceding and subsequent values.
This is an example of one cycle
x <- c(3.049, 3.492, 3.503, 3.429, 3.013, 2.881, 2.29, 1.785, 1.211, 0.890, 0.859, 0.903, 1.165, 1.634, 2.073, 2.477, 3.162, 3.207, 3.177, 2.742, 2.24, 1.827, 1.358, 1.111, 1.063, 1.098, 1.287, 1.596, 2.169, 2.292)
I have 1000's of cycles so I am using group_by in dplyr to group the cycles and then hoped to apply the conditional max/min argument within groups.
I would appreciate any advice with this,
Thanks in advance
Edit
I have since used the below function with just a slight edit on the last line
return(data.frame(Data.value=x, Time=y, Date=z,HHT=peak, LLT=trough))
where x is my original x above, y is a time var and z is a date var. This allowed me to do some extra calculations on the results (I needed the time at which the value was min/max as well as the value itself).
So now I have a dataframe with everything I need but it is only for one date - I still can't get this run through the whole dataset using the group_by function. I have tried sub-setting by date using
subsets<-split(data, data$datevar, drop=TRUE)
But still need a way to somehow run the findminmax function (and my few extra lines of code) for each subset. Any ideas?

Answer 1

Consider the following custom function that you can pass in a dplyr group_by() procedure. Essentially, function iterates through list of cyclical values and compares neighbor before and after it. Peaks would have neighbors both lower than itself and troughs with neighbors larger than iteself.
findminmax <- function(x){
peak <- list(NA, NA) # INITIALIZE TEMP LISTS AND ITERATORS
p <- 1
trough <- list(NA, NA)
t <- 1
for (i in 1:length(x)){
if (i != 1 & i != length(x)){ # LEAVES OUT FIRST AND LAST VALUES
if ((x[i] > x[i-1]) & (x[i] > x[i+1])) { # COMPARES IF GREATER THAN NEIGHBORS
peak[p] <- x[i]
p <- p + 1
}
if ((x[i] < x[i-1]) & (x[i] < x[i+1])){ # COMPARES IF LESS THAN NEIGHBORS
trough[t] <- x[i]
t <- t + 1
}
}
}
return(list(peak1=peak[[1]], peak2=peak[[2]],
trough1=trough[[1]], trough2=trough[[2]]))
}
result <- findminmax(x)
#$peak1
#[1] 3.503
#$peak2
#[1] 3.207
#$trough1
#[1] 0.859
#$trough2
#[1] 1.063
For dplyr's group_by:
finaldf <- originaldf %>%
group_by(z) %>%
summarise(Time = mean(y),
HHT1 = findminmax(x)$peak1,
HHT2 = findminmax(x)$peak2,
LLT1 = findminmax(x)$trough1,
LLT2 = findminmax(x)$trough2)