Light-weight data.frame class: was: how to add method to .Primitive function

Hi,

Encouraged by a tip from Simon Urbanek I tried to use the S3 machinery
to write a faster version of the data.frame class.
This quickly hits a snag: the "[.default"(x, i) for some reason cares
about the dimensionality of x.
In the end there is a full transcript of my R session. It includes the
motivation for writing the class and the problems I have encountered.

As a result I see three issues here:
* why "[.default"(x, i) doesn't work if dim(x) is 2? After all a single
subscript into a vector works regardless of whether it's a matrix or
not. Is there an alternative way to access "[.default"?
* why does unclass() make deep copy? This is a facet of the global
over-conservatism of R with respect to copying.
* is it possible to add some sort copy profiling to R? Something like
copyProfiling(TRUE), which should cause R to log sizes of each copied
object (just raw sizes w/o any attempt to identify the object). This
feature should at least help assess the magnitude of the problem.

Thanks,
Vadim

Now the transcript itself:

# the motivation: subscription of a data.frame is *much* (almost 20

times) slower than that of a list

# compare
n = 1e6
i = seq(n)

x = data.frame(a=seq(n), b=seq(n))
system.time(x[i,], gcFirst=TRUE)

[1] 1.01 0.14 1.14 0.00 0.00

x = list(a=seq(n), b=seq(n))
system.time(lapply(x, function(col) col[i]), gcFirst=TRUE)

[1] 0.06 0.00 0.06 0.00 0.00

# the solution: define methods for the light-weight data.frame class
lwdf = function(...) structure(list(...), class = "lwdf")

# dim
dim.lwdf = function(x) c(length(x[[1]]), length(x))

# for pretty printing we define print.lwdf via a conversion to

data.frame

# as.data.frame.lwdf
as.data.frame.lwdf = function(x) structure(unclass(x),

class="data.frame", row.names=as.character(seq(nrow(x))))

# print
print.lwdf = function(x) print.data.frame(as.data.frame.lwdf(x))

# now the real stuff

# "["
# the naive "[.lwdf" = function (x, i, j) lapply(x[j], function(col)

col[i])

# won't work because evaluation of x[j] calls "[.lwdf" again and not

"[.default"

# so we switch by the number of arguments
"[.lwdf" = function (x, i, j) {

+   if (nargs() == 2)
+     NextMethod("[", x, i)
+   else
+     structure(lapply(x[j], function(col) col[i]),  class = "lwdf")
+ }

x = lwdf(a=seq(3), b=letters[seq(3)], c=as.factor(letters[seq(3)]))
i = c(1,3); j = c(1,3)

# unfortunately, for some reasons "[.default" cares about

dimensionality of its argument

x[i,j]

Error in "[.default"(x, j) : incorrect number of dimensions

# we could use unclass to get it right
"[.lwdf" = function (x, i, j) {

+   structure(lapply(unclass(x)[j], function(col) col[i]),  class =
"lwdf")
+ }

x[i,j]

 a c
1 1 a
2 3 c

# *but* unclass creates a deep copy of its argument as indirectly

evidenced by the following timing

x = lwdf(a=seq(1e6)); system.time(unclass(x))

[1] 0.01 0.00 0.01 0.00 0.00

x = lwdf(a=seq(1e8)); system.time(unclass(x))

[1] 0.44 0.39 0.82 0.00 0.00

version

        _
platform x86_64-unknown-linux-gnu
arch     x86_64
os       linux-gnu
system   x86_64, linux-gnu
status
major    2
minor    0.1
year     2004
month    11
day      15
language R