Thanks,
That helped. Maybe when I get a chance I will do some blog posts on the
basics of ff
I think some tutorials would be a good idea
Steve
On Mon, Feb 27, 2012 at 3:47 AM, Djordje Bajic <je.li....@gmail.com> wrote:
> Steven, sorry for the delay in responding,
>
> I have been investigating this also and here is the way I do it (though
> probably not the best way):
>
> # .. define a 3D array
> > ngen = 904
> > gratios <- ff(NA, dim=rep(ngen,3), vmode="double")
>
> # .. fill the array with standard R functions
>
> > ffsave (gratios, file="mydir/myfile") # without extension
> > finalizer(gratios) <- "delete"
>
> # ..
>
> so, you firstly define the ff object, you put the data inside, and you
> ffsave it. The ffsave function will generate two files, with extensions
> ffdata and a Rdata. Then you set 'delete' to be the 'finalizer' of the
> object; in this way you avoid ff to save it in some tmp dir and occupy disk
> space forever. Then, you can access your object in the next R session:
>
> > ffload("mydir/myfile") # also without extension
>
> I hope this helped.
>
> Cheers,
>
> djordje
>
>
>
> 2012/2/23 steven mosher <mosherste...@gmail.com>
>
> > Did you have to use a particular filename? or extension.
> >
> > I created a similar file but then could not read it back in
> >
> > Steve
> >
> > On Mon, Feb 13, 2012 at 6:45 AM, Djordje Bajic <je.li....@gmail.com
> >wrote:
> >
> >> I've been investigating and I partially respond myself. I tried the
> >> packages 'bigmemory' and 'ff' and for me the latter did the work I need
> >> pretty straightforward. I create the array in filebacked form with the
> >> function ff, and it seems that the usual R indexing works well. I have
> yet
> >> to see the limitations, but I hope it helps.
> >>
> >> a foo example:
> >>
> >> myArr <- ff(NA, dim=rep(904,3), filename="arr.ffd", vmode="double")
> >> myMat <- matrix(1:904^2, ncol=904)
> >> for ( i in 1:904 ) {
> >> myArr[,,i] <- myMat
> >> }
> >>
> >> Thanks all,
> >>
> >> 2012/2/11 Duncan Murdoch <murdoch.dun...@gmail.com>
> >>
> >> > On 12-02-10 9:12 AM, Djordje Bajic wrote:
> >> >
> >> >> Hi all,
> >> >>
> >> >> I am trying to fill a 904x904x904 array, but at some point of the
> loop
> >> R
> >> >> states that the 5.5Gb sized vector is too big to allocate. I have
> >> looked
> >> >> at
> >> >> packages such as "bigmemory", but I need help to decide which is the
> >> best
> >> >> way to store such an object. It would be perfect to store it in this
> >> >> "cube"
> >> >> form (for indexing and computation purpouses). If not possible, maybe
> >> the
> >> >> best is to store the 904 matrices separately and read them
> individually
> >> >> when needed?
> >> >>
> >> >> Never dealed with such a big dataset, so any help will be appreciated
> >> >>
> >> >> (R+ESS, Debian 64bit, 4Gb RAM, 4core)
> >> >>
> >> >
> >> > I'd really recommend getting more RAM, so you can have the whole thing
> >> > loaded in memory. 16 Gb would be nice, but even 8Gb should make a
> >> > substantial difference. It's going to be too big to store as an array
> >> > since arrays have a limit of 2^31-1 entries, but you could store it
> as a
> >> > list of matrices, e.g.
> >> >
> >> > x <- vector("list", 904)
> >> > for (i in 1:904)
> >> > x[[i]] <- matrix(0, 904,904)
> >> >
> >> > and then refer to entry i,j,k as x[[i]][j,k].
> >> >
> >> > Duncan Murdoch
> >> >
> >> >
> >> >
> >>
> >> [[alternative HTML version deleted]]
> >>
> >> ______________________________________________
> >> R-help@r-project.org mailing list
> >> https://stat.ethz.ch/mailman/listinfo/r-help
> >> PLEASE do read the posting guide
> >> http://www.R-project.org/posting-guide.html
> >> and provide commented, minimal, self-contained, reproducible code.
> >>
> >
> >
>
> [[alternative HTML version deleted]]
>
> ______________________________________________
> R-help@r-project.org mailing list
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide
> http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>
[[alternative HTML version deleted]]
______________________________________________
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
