I've read in Phil Spector's new book that it's a good idea to preallocate a big matrix, like
u <- matrix(0,nrow,ncol) # (1) Now, I read contents of a huge matrix from a Fortran binary dump. u <- readBin(con,what="double",n=nrow*ncol) # (2) If I do (1) and then (2), u is a vector, obviously it's either reallocated or its matrix nature is lost -- overridden? overwritten? Instead, I do it now as u <- matrix(readBin(con,what="double",n=nrow*ncol),nrow=nrow,ncol=ncol) # (3) What's going on with memory management here and what's the right way to make it efficient -- and how to preallocate? After that, I'm saving u as R binary object in an rda file. Does it make sense to preallocate u before reading it back now from the rda file? Cheers, Alexy ______________________________________________ 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.
