On Wednesday 13 February 2008, Moritz Lennert wrote: > On 12/02/08 03:43, Dylan Beaudette wrote: > > On Monday 11 February 2008, Moritz Lennert wrote: > >> Hello, > >> > >> I've finally gotten around to continue working on the d.thematic.* > >> modules, and more specifically on the classification code. As mentioned > >> earlier, I think it makes sense to make the latter into a library, so I > >> decided to create lib_arraystats which contains functions for collecting > >> basic statistics and for finding class breaks in arrays of doubles. In > >> the future this could be filled with more statistical functions on such > >> arrays. > >> > >> Could the gurus please have a look and tell me if the attached files are > >> decent enough (except for the lacking documentation) to be committed to > >> svn for further development ? Once that's done, I can also commit the > >> d.thematic.area and v.class modules. > >> > >> Moritz > > > > Nice work Moritz. > > > > On this thread-- it would be neat if we can use (along side Moritz's and > > existinf stat libs) the shared R library, when available. I think that it > > would have to be a compile-time option, and the user would have to have R > > installed, and compiled with the '--enable-R-shlib' flag. This would > > allow us to switch between the default, basic set of algorithms, and the > > entire suite of R codes. Some of these functions might not work with huge > > datasets (R works with data in-memory)-- but it would allow us to program > > more complicated algorithms without re-inventing them. > > I agree that having a more direct link to R would be nice. At the same, > I'm not sure if we should do this across all modules using stats. Maybe > a g.rstats or v.rstats could be an option ?
A follow-up: instead of linking to the R libs, we could use something like: Rscript --vanilla --slave --default-packages=stats -e 'mean(rnorm(100))' via some kind of system() function, to access R in a simple and relatively fast way. Dylan > > > This thread reminded me of doing this, as sometimes it is useful to look > > for "natural classes" within data. Instead of re-implementing a variation > > of K-means, we could just pass an array to the appropriate (set of) R > > functions. > > I've done this, but via the plr interface between R and PostgreSQL. See > attached script for an example. > > Moritz -- Dylan Beaudette Soil Resource Laboratory http://casoilresource.lawr.ucdavis.edu/ University of California at Davis 530.754.7341 _______________________________________________ grass-dev mailing list [email protected] http://lists.osgeo.org/mailman/listinfo/grass-dev
