On 3/28/07, Henrik Bengtsson <[EMAIL PROTECTED]> wrote: > Hi, > > when doing as.double() on an object that is already a double, the > object seems to be copied internally, doubling the memory requirement. > See example below. Same for as.character() etc. Is this intended? > > Example: > > % R --vanilla > > x <- double(1e7) > > gc() > used (Mb) gc trigger (Mb) max used (Mb) > Ncells 234019 6.3 467875 12.5 350000 9.4 > Vcells 10103774 77.1 11476770 87.6 10104223 77.1 > > x <- as.double(x) > > gc() > used (Mb) gc trigger (Mb) max used (Mb) > Ncells 234113 6.3 467875 12.5 350000 9.4 > Vcells 10103790 77.1 21354156 163.0 20103818 153.4 > > However, couldn't this easily be avoided by letting as.double() return > the object as is if already a double? > > Example: > > % R --vanilla > > as.double.double <- function(x, ...) x > > x <- double(1e7) > > gc() > used (Mb) gc trigger (Mb) max used (Mb) > Ncells 234019 6.3 467875 12.5 350000 9.4 > Vcells 10103774 77.1 11476770 87.6 10104223 77.1 > > x <- as.double(x) > > gc() > used (Mb) gc trigger (Mb) max used (Mb) > Ncells 234028 6.3 467875 12.5 350000 9.4 > Vcells 10103779 77.1 12130608 92.6 10104223 77.1 > > What's the catch?
Ok, one catch that my example didn't illustrate is: "as.double' attempts to coerce its argument to be of double type: like 'as.vector' it strips attributes including names." (from ?as.double). So, answering my own question, I can see how stripping the attributes "requires" a internal copy. Anyhow, when there are stripping attributes, the same idea still applies, with a more clever as.double() function. In the case when one want to coerce to a double, and keep existing attributes, one could extend as.double() with: as.double(x, stripAttributes=FALSE) and that code could be clever enough not to create and internal copy. /Henrik > > > The reason why I bring it up, is because many (most?) methods are > using as.double() etc "just in case" when passing arguments to > .Call(), .Fortran() etc, e.g. stats::smooth.spline(): > > fit <- .Fortran(R_qsbart, as.double(penalty), as.double(dofoff), > x = as.double(xbar), y = as.double(ybar), w = as.double(wbar), <etc>) > > Your memory usage is peaking in the actual call and the garbage > collector cannot clean it up until after the call. This seems to be > waste of memory, especially when the objects are large (100-1000MBs). > > Cheers > > Henrik > ______________________________________________ R-devel@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-devel
