Here is a case where the current scheme fails:
> with(datasets::mtcars, xyplot(mpg~wt|gear)$call)
xyplot(substitute(expr), data, enclos = parent.frame())
Bill Dunlap
TIBCO Software
wdunlap tibco.com
On Thu, May 11, 2017 at 1:09 AM, Deepayan Sarkar <deepayan.sar...@gmail.com>
wrote:
> On Wed, May 10, 2017 at 2:36 AM, William Dunlap via R-devel
> <r-devel@r-project.org> wrote:
> > Some formula methods for S3 generic functions use the idiom
> > returnValue$call <- sys.call(sys.parent())
> > to show how to recreate the returned object or to use as a label on a
> > plot. It is often followed by
> > returnValue$call[[1]] <- quote(myName)
> > E.g., I see it in packages "latticeExtra" and "leaps", and I suspect it
> > used in "lattice" as well.
> >
> > This idiom has not done good things for quite a while (ever?) but I
> noticed
> > while running tests that it acts differently in R-3.4.0 than in R-3.3.3.
> > Neither the old or new behavior is nice. E.g., in R-3.3.3 we get
> >
> >> parseEval <- function(text, envir) eval(parse(text=text), envir=envir)
> >> parseEval('lattice::xyplot(mpg~hp, data=datasets::mtcars)$call',
> > envir=new.env())
> > xyplot(expr, envir, enclos)
> >
> > and
> >
> >> evalInEnvir <- function(call, envir) eval(call, envir=envir)
> >> evalInEnvir(quote(lattice::xyplot(mpg~hp, data=datasets::mtcars)$call),
> > envir=new.env())
> > xyplot(expr, envir, enclos)
> >
> > while in R-3.4.0 we get
> >> parseEval <- function(text, envir) eval(parse(text=text), envir=envir)
> >> parseEval('lattice::xyplot(mpg~hp, data=datasets::mtcars)$call',
> > envir=new.env())
> > xyplot(parse(text = text), envir = envir)
> >
> > and
> >
> >> evalInEnvir <- function(call, envir) eval(call, envir=envir)
> >> evalInEnvir(quote(lattice::xyplot(mpg~hp, data=datasets::mtcars)$call),
> > envir=new.env())
> > xyplot(call, envir = envir)
> >
> > Should these packages be be fixed up to use just sys.call()?
>
> I admit to not understanding these things very well, but I'll try to
> explain why I ended up with the usage I have. The main use of the
> $call component within lattice is to use it in the summary method, as
> in:
>
> > summary(xyplot(mpg~hp, data=mtcars))
>
> Call:
> xyplot(mpg ~ hp, data = mtcars)
>
> Number of observations:
> [1] 32
>
> Here is a minimal approximation to what I need: Here foo() and bar()
> are generics producing objects of class "foobar", bar() calls foo()
> with one argument changed, and the print() method for "foobar" is just
> supposed to print the call that produced it:
>
> ########
>
> foo <- function(x, ...) UseMethod("foo")
> bar <- function(x, ...) UseMethod("bar")
> print.foobar <- function(x, ...) print(x$call)
>
> ## Using plain sys.call():
>
> foo.formula <- function(x, ...)
> {
> ans <- structure(list(), class = "foobar")
> ans$call <- sys.call()
> ans
> }
>
> bar.formula <- function(x, ..., panel)
> {
> foo.formula(x, ..., panel = panel.bar)
> }
>
> foo.table <- function(x, ...)
> {
> ans <- foo.formula(Freq ~ Var1,
> as.data.frame.table(x), ...)
> ans
> }
>
> ## I would get
>
> foo(y ~ x)
> # foo.formula(y ~ x)
>
> bar(y ~ x)
> # foo.formula(x, ..., panel = panel.bar)
>
> foo(as.table(1:10))
> # foo.formula(Freq ~ Var1, as.data.frame.table(x), ...)
>
> ## The last two are improved by
>
> foo.formula <- function(x, ...)
> {
> ans <- structure(list(), class = "foobar")
> ans$call <- sys.call(sys.parent())
> ans
> }
>
> bar(y ~ x)
> ## bar.formula(y ~ x)
>
> foo(as.table(1:10))
> ## foo.table(as.table(1:10))
>
> ########
>
> Adding
>
> ans$call[[1]] <- quote(foo)
>
> (or quote(bar) in bar.formula) is needed to replace the unexported
> method name (foo.formula) with the generic name (foo), but that's
> probably not the problem.
>
> With this approach in lattice,
>
> p <- some.function(...)
> eval(p$call)
>
> usually works, but not always, if I remember correctly.
>
> I'm happy to consider more robust solutions. Maybe I just need to have a
>
> ...$call <- sys.call()
>
> statement in every method?
>
> -Deepayan
>
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