How to include logical checks in a custom function - r

Question

I have written a custom function that performs a mathematical transformation on a column of data with the inputs being the data and one other input (temperature). I would like to have 2 different logical checks. The first one is whether or not any values in the column exceed a certain threshold, because the transformation is different above and below the threshold. The second is a check if the temperature input is above a certain value and in that case, to deliver a warning that values above the threshold are unusual and to check the data.
Right now, I have the function written with a series of if/else statements. However, this a warning that it is only using the first element of the string of T/F statements. A simplified example of my function is as follows:
myfun = function(temp,data) {
if(temp > 34){
warning('Temperature higher than expected')
}
if (data > 50) {
result = temp*data
return(result)
} else if(data <= 50) {
result = temp/data
return(result)
}
}
myfun(temp = c(25,45,23,19,10), data = c(30,40,NA,50,10))
As you can see, because it is only using the first value for the if/else statements, it does not properly calculate the return values because it doesn't switch between the two versions of the transformation. Additionally, it's only checking if the first temp value is above the threshold. How can I get it to properly apply the logical check to every value and not just the first?
-edit-simplified the function per #The_Questioner's suggestion and changed < 50 to <= 50.

Answer 1

The main issue with your code is that you are passing all the values to the functions as vectors, but then are doing single element comparisons. You need to either pass the elements one by one to the function, or put some kind of vectorized comparison or for loop into your function. Below is the for loop approach, which is probably the least elegant way to do this, but at least it's easy to understand what's going on.
Another issue is that NA's apparently need to be handled in the data vector before passing to any of your conditional statements, or you'll get an error.
A final issue is what to do when data = 50. Right now you have conditional tests for greater or less than 50, but as you can see, the 4th point in data is 50, so right now you get an NA.
myfun = function(temp,data) {
result <- rep(NA,length(temp))
for (t in 1:length(temp)) {
if(temp[t] > 34) {
warning('Temperature higher than expected')
if (!is.na(data[t])) {
if (data [t] > 50) {
result[t] <- temp[t]*data[t]
} else if(data[t] < 50) {
result[t] <- temp[t]/data[t]
}
}
} else {
if (!is.na(data[t])) {
if (data[t] > 50) {
result[t] <- temp[t]*data[t]
} else if(data[t] < 50) {
result[t] <- temp[t]/data[t]
}
}
}
}
return(result)
}
Output:
> myfun(temp = c(25,45,23,19,10), data = c(30,40,NA,50,10))
[1] 0.8333333 1.1250000 NA NA 1.0000000