On Thu, 14 Jul 2005, Kenneth Cabrera wrote: > Thank you Dr. Spencer Graves for your answer. > > What kind of matrices? They come form an image of about 3000x5000, and > I need to generate arround 1024 matrices of the same size, they are not > sparse > matrices. > > What function can I use to, once generated one matrix, I could save into disk > and then use the same space for the following, and so on.
You can use either save or .saveRDS/serialize followed by rm() and gc(). You cannot use the same space, but you can free up the space. Then when you need the data again, load/.readRDS/unserialize can pull the object back. (If you arrange this right the object will only go into a temporary frame and so only be needed one at a time.) > > Thank you very much for your help > > Kenneth > > Spencer Graves wrote: > >> What kinds of matrices? There are facilities in the Matrix and >> SparseM packages that might help for sparse matrices. If they are N x k >> where N is large and k is not, can you compute something like the QR >> decomposition and get away with keeping only the R part for most of your >> matrices? >> >> One could potentially define a class of matrices that are only kept >> in memory only when needed; I think S-Plus may do that. It would take a >> lot of work to make that work generally, but you might be able to >> accomplish what you need with a much smaller effort. >> >> spencer graves >> >> Kenneth Roy Cabrera Torres wrote: >> >> >>> Hi R users and developers: >>> >>> I want to know how can I save memory in R >>> for example: >>> - saving on disk a matrix. >>> - using again the matrix (changing their values) >>> - saving again the matrix on disk in a different file. >>> >>> The idea is that I have a process that generate several >>> matrices, but if I keep them all in memory it will overflow. >>> >>> How can I save them in different files, so I use the same >>> amount of memory for each processed matrix? >>> >>> Thank you for your help. >>> >>> >> >> > -- Brian D. Ripley, [EMAIL PROTECTED] Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/ University of Oxford, Tel: +44 1865 272861 (self) 1 South Parks Road, +44 1865 272866 (PA) Oxford OX1 3TG, UK Fax: +44 1865 272595 ______________________________________________ [email protected] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
