Why not place them in the package environment? Gabor On Wed, Aug 6, 2014 at 2:10 PM, Paul Johnson <pauljoh...@gmail.com> wrote: > I'm writing to ask for a policy exception, or advice on how to make > this package CRAN allowable. > > http://rweb.quant.ku.edu/kran/src/contrib/portableParallelSeeds_0.9.tar.gz > > Yesterday I tried to submit a package on CRAN and Dr Ripley pointed > out that I had not understood the instructions about packages. Here's > the part where the R check gives a Note > > * checking R code for possible problems ... NOTE > Found the following assignments to the global environment: > File ‘portableParallelSeeds/R/initPortableStreams.R’: > assign("currentStream", n, envir = .GlobalEnv) > assign("currentStates", curStates, envir = .GlobalEnv) > assign("currentStream", 1L, envir = .GlobalEnv) > assign("startStates", runSeeds, envir = .GlobalEnv) > assign("currentStates", runSeeds, envir = .GlobalEnv) > assign("currentStream", as.integer(currentStream), envir = .GlobalEnv) > assign("startStates", runSeeds, envir = .GlobalEnv) > assign("currentStates", runSeeds, envir = .GlobalEnv) > > Altering the user's environment requires a special arrangement with > CRAN. I believe this is justified, I'll sketch the reasons now. But, > mostly, I'm at your mercy and if there is any way to make this > possible, I would be very grateful. > > To control & replace random number streams, it really is necessary to > alter the workspace. That's where the random generator state is > stored. It is acknowledged in Robert Gentleman' s Book, R Programming > for Bionformatics "The decision to have these [random generator] > functions manipulate a global variable, .Random.seed, is slightly > unfortunate as it makes it somewhat more difficult to manage several > different random number streams simultaneously” (Gentleman, 2009, p. > 201). > > I have developed an understandable set of wrapper functions that handle this. > > Some of you may recall this project. I've asked about it here a couple > of times. We allow separate streams of randoms for different purposes > within a single R run. There is a framework to save 1000s of those > sets in a file, so it can be used on a cluster or in a single > workstation. This is handy because, when 1 run in 10,000 on the > cluster exhibits some weird behavior, we can easily re-initiate that > interactively and see what's going on. > > I have a vignette "pps" that explains. I dropped a copy of that here > in case you don't want to get the package: > > http://pj.freefaculty.org/scraps/pps.pdf > > While working on that, I gained a considerably deeper understanding of > random generators and seeds. That is what this vignette is about > > http://pj.freefaculty.org/scraps/PRNG-basics.pdf > > > We've been running simulations on our cluster with the > portableParallelSeeds framework for 2 years, we've never had any > trouble. We are able to re-start runs, verify random number draws in > separate streams. > > PJ > -- > Paul E. Johnson > Professor, Political Science Assoc. Director > 1541 Lilac Lane, Room 504 Center for Research Methods > University of Kansas University of Kansas > http://pj.freefaculty.org http://quant.ku.edu > > ______________________________________________ > R-devel@r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-devel
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