[R] [ and setMethod conflict?

[Bartz, Kevin]

I noticed this oddity about [ and setMethod.

First, I define testFunc, which sorts a data frame by the first column and
returns the entries that aren't NAs, and testIt, which runs testFunc
repeatedly on a random large data frame, each time saving the return into a
dummy placeholder (for demonstration's sake).

> require(methods)
Loading required package: methods 
[1] TRUE
> testFunc <- function(cur) {
+   sorted <- cur[order(cur[,1]),]
+   sorted[!is.na(sorted[,1]),]
+ }
> testIt <- function(num)
+   for (i in 1:num) {
+     cat("iteration", i, "...\n")
+     dummy <- testFunc(as.data.frame(matrix(rnorm(5000 * 9),9)))
+   }

Let's test out testIt.

> testIt(10)
iteration 1 ...
iteration 2 ...
iteration 3 ...
iteration 4 ...
iteration 5 ...
iteration 6 ...
iteration 7 ...
iteration 8 ...
iteration 9 ...
iteration 10 ...

So far, no problems. Next, I define myClass.

> setClass("myClass", representation(mySlot = "numeric"))
[1] "myClass"
> setMethod("[", signature(x = "myClass"),
+           function(x, i, j, drop) "[ for myClass")
[1] "["

Again, everything is fine. I've expanded [ to handle objects of class
myClass. But when we attempt to use testIt now, problems emerge:

> testIt(10)
iteration 1 ...
Error in "[.data.frame"(cur, order(cur[, 1]), ) : 
	unused argument(s) (.Method ...)

Maybe that was just a fluke. Trying again, we get:

> testIt(10)
iteration 1 ...
iteration 2 ...
Error in sorted[, 1] : incorrect number of dimensions

A different message every time, and the error seems no bug of mine (a
.Method argument? What is that?). In fact, testIt produces a seemingly
random response from R on each subsequent attempt--everything from
successful execution to similarly ambiguous errors to a process-killing "Bus
Error."

All in all, it seems that once I've defined a new method for [ I can no
longer count on it to operate properly in any context.

Is this the intended behavior? And if so, is there any way I can have one
class present that overloads [ and still use [ to reliably subset data
frames?

Thanks,

Kevin

> R.version
         _                   
platform sparc-sun-solaris2.6
arch     sparc               
os       solaris2.6          
system   sparc, solaris2.6   
status                       
major    1                   
minor    5.1                 
year     2002                
month    06                  
day      17                  
language R         
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