[R-SIG-Mac] Problems with definitions of S4-generics

[Byron Ellis]

This isn't a Mac problem, this is a moving from 2.2 to 2.4. You'll
probably get better answers on R-devel. My guess would be that a cache
used by methods to store frequently used generics isn't getting
flushed by removeGeneric properly, though a brief glance at the code
suggests that it tries. Your best bet is probably to file a bug report
with a simple example.

On 12/21/06, Jörg Beyer <Beyerj at students.uni-marburg.de> wrote:
> Hello all,
>
> I installed R 2.4.1 yesterday (coming from 2.2.1), and made an interesting
> observation today, which may be a simple coincidence, or related to R 2.4.1.
>
> Platform:
> Mac G4/400 PCI (Oct. 1999, PPC-architecture)
> Mac OS 10.4.8
> R 2.4.1 for Mac OS X (CRAN binary, 2006-12-19) w/ R.app 1.18
>
>
> Problem-intro:
> The file "/Volumes/RAMdisk/beyerjoerg/Scripting R/source-0.R" contains code
> that constructs and registers a S4-style generic function, *but only if the
> function does not exist, to avoid unnecessary computations.*
> This is the stub to test whether or not a S4-Generic is present:
>   if ( ! isGeneric( <nameOfS4generic> )) {
>     <setGeneric ...>
>   }
>
> The code itself has worked without problems with R 2.2.1 -- the code is not
> the problem.
> Okay, let's start. The function in this example is "cleanDataset"; to
> demonstrate the problem, I'm using a second S4-generic here, it is named
> "removeFactors".
>
>
> #### Fist the correct part
> ## Source the code and build the S4-generic
> > source( "/Volumes/RAMdisk/beyerjoerg/Scripting R/source-0.R" )
>
>
> ## Do some tests to see if the generic is present,
> ## and have a look at some details
> > isGeneric( "cleanDataset" )
> [1] TRUE
>
>
> > findFunction( "cleanDataset" )
> [[1]]
> <environment: R_GlobalEnv>
>
>
> > cleanDataset
> nonstandardGenericFunction for "cleanDataset" defined from package
> ".GlobalEnv"
>
> function (object)
> {
>     standardGeneric("cleanDataset")
> }
> <environment: 0x293bbb8>
> Methods may be defined for arguments: object
>
>
> > getGeneric( "cleanDataset" )
> ## same result as above
>
>
>
> #### Now what I suspect is a bug
> ## Delete the S4-generic (and all its methods, if any)
> ## and repeat the "forensic" test calls
> > removeGeneric( "cleanDataset" )
> [1] TRUE
>
>
> # The following is as expected...
> ## [I'm trying here to re-translate the message from German back
> ## to English, so please don't be irritated if there are any differences]
> > cleanDataset
> Error: object "cleanDataset" not found
>
>
> # Oops, but what's that?
> > getGeneric( "cleanDataset" )
> nonstandardGenericFunction for "cleanDataset" defined from package
> ".GlobalEnv"
>
> function (object)
> {
>     standardGeneric("cleanDataset")
> }
> <environment: 0x19be228>
> Methods may be defined for arguments: object
>
>
> ## Why not try to remove it a second time?
> > removeGeneric( "cleanDataset" )
> [1] FALSE
> Warning message:
> generic function "cleanDataset" not found for removal in:
> removeGeneric("cleanDataset")
>
>
> # Another test to see if there is a function definition somewhere
> # Weird ...
> > isGeneric( "cleanDataset" )
> [1] TRUE
>
>
> # Okay, let's see, where it is
> # Ah, registered, but nowhere ...
> > findFunction( "cleanDatasets" )
> list()
>
>
> # Just to be sure, test another generic (which I know is *present
> # and working*)   Okay, as expected...
> > findFunction( "removeFactors" )
> [[1]]
> <environment: R_GlobalEnv>
>
>
>
>
> #### Consequence:
> # Because my code first tests whether a generic is present or not
> # (see above), re-sourcing the definition code leads to nothing
> > source( "/Volumes/RAMdisk/beyerjoerg/Scripting R/source-0.R" )
> > cleanDataset
> Error: object "cleanDataset" not found
>
>
>
> When I skip testing the existence of a generic, everything works as
> expected, of course.
> Deleting and redefining generic functions this way never caused problems
> under R 2.2.1 (I'm developing with this code since six months, the helper
> functions have been called over and over again), but I don't have explicit
> results for the above tests and R 2.2.1.
>
> Running the above test case in R.app or from the terminal makes no
> difference. At the moment, I can't see a reason why R should do what it
> obviously does here, but I may have misunderstood something essential.
>
> Some comments may be helpful.
> Thanks for your interest.
>
> Cheers
>
> Jörg
>
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>


-- 
Byron Ellis (byron.ellis at gmail.com)
"Oook" -- The Librarian