# Aggregating Results from Unreliable Functions in R

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I posted this as a response to a question on R-help. I think the idea of a “collect” function could be useful both in the context of unreliable functions that sometimes error out and also in filtering contexts where currently one creates a list containing good elements and some sort of sentinel, usually NULL, which has itself to be filtered out in a separate subsetting operation after the main filtering loop.

Here’s an example:

d <- runif(20, min=-2, max=8) # test data aFunc <- function(x) { # gives error occasionally if (x > 0) x else stop("encountered bad x") } collect <- function(x, FUN, skip_error=TRUE, args_list=NULL) { if (!is.vector(x)) stop("arg x must be a vector") fname <- deparse(substitute(FUN)) xvar <- deparse(substitute(x)) i <- 1 j <- 1 result <- vector(mode=mode(x), length=length(x)) while (i <= length(x)) { tryCatch({ args <- list(x[i]) if (length(args_list)) args <- c(args, args_list) ans <- do.call(FUN, args) result[j] <- ans j <- j + 1 }, error=function(e) { if (!skip_error) { msg <- paste("collect\n", "call to", fname, "failed at", paste(xvar, "[", i, "]\n", sep=""), "Message:\n", conditionMessage(e)) stop(msg, call.=FALSE) } NULL }, finally={i <- i + 1}) } if (j > 1) result[1:(j-1)] else vector(mode=mode(x), length=0) } ## Example collect(d, aFunc, skip_error=FALSE) Error: collect call to aFunc failed at d[2] Message: encountered bad x collect(d, aFunc, skip_error=TRUE) [1] 7.7380303 0.7554328 1.8352623 0.5136118 4.4231091 2.5368103 1.8656615 [8] 2.9244200 2.1364120 7.6711189 0.2141325 7.8216620 5.8347576 5.3939892

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