Thanks Laurent. I noticed the lack of support for windows, and I completely understand. Maintaining installers for multiple platforms is a real pain. I am using rpy2 for the Red-R project and we really must support windows... Kyle is working on making the newest version of RPy2 run on windows. We'll let you know if and when we have something.
Thanks, Anup On Sat, Jan 8, 2011 at 1:47 PM, Laurent <lgaut...@gmail.com> wrote: > > That part of the documentation should apply to 2.0.8 > http://rpy.sourceforge.net/rpy2/doc-2.1/html/performances.html#memory-usage > > Manual invocation of the garbage collector is sometimes needed. Example of a > discussion around that: > http://stackoverflow.com/questions/1740394/python-behavior-of-the-garbage-collector > > > L. > > PS: rpy2 under MSWindows is not very well supported. > > > > On 08/01/11 20:34, Anup Parikh wrote: >> >> seems like this is a problem with large datasets and rpy2. The python >> code will fail, the R will not. >> If I reduce the data size to 5000000, both snippets will work. >> >> ===python code run in IDLE=== >> import os >> os.environ['R_HOME'] = 'C:/Users/anup/Documents/red/develop/R/R-2.9.2' >> import rpy2.robjects as rpy2 >> >> count = 200 >> for x in range(count): >> print 'round' , x >> rpy2.r('a<-rnorm(50000000)') >> rpy2.r('gc()') >> >> ===ERROR=== >> rpy2.r('a<-rnorm(50000000)') >> File "C:\Python26\lib\site-packages\rpy2\robjects\__init__.py", line >> 536, in __call__ >> res = self.eval(p) >> File "C:\Python26\lib\site-packages\rpy2\robjects\__init__.py", line >> 423, in __call__ >> res = super(RFunction, self).__call__(*new_args, **new_kwargs) >> RRuntimeError: Error: cannot allocate vector of size 381.5 Mb >> >> >> >> ==R code run in windows RGui.exe== >> for( x in 1:200){ >> print(x) >> a<-rnorm(50000000) >> gc() >> } >> >> Any suggestions?? >> >> Thanks, >> Anup >> >> >> On Sun, Jan 2, 2011 at 11:13 PM, Anup Parikh<anup.par...@gmail.com> >> wrote: >>> >>> I am using rpy2.0.8 on windows and finding that the following script >>> keeps taking memory as it processes the loop. since the call to rnorm >>> is never assigned, i'm not sure how to release the memory? Is this a >>> bug in 2.0.8? Any suggestions would be helpful. >>> >>> >>> import os >>> os.environ['R_HOME'] = 'C:/Users/anup/Documents/red/develop/R/R-2.9.2' >>> import rpy2.robjects as rpy2 >>> >>> for x in range(20): >>> rpy2.r('rnorm(50000000)') >>> rpy2.r('gc()') >>> >>> >>> Thanks, >>> Anup >>> >> >> >> ------------------------------------------------------------------------------ >> Gaining the trust of online customers is vital for the success of any >> company >> that requires sensitive data to be transmitted over the Web. Learn how >> to >> best implement a security strategy that keeps consumers' information >> secure >> and instills the confidence they need to proceed with transactions. >> http://p.sf.net/sfu/oracle-sfdevnl >> _______________________________________________ >> rpy-list mailing list >> rpy-list@lists.sourceforge.net >> https://lists.sourceforge.net/lists/listinfo/rpy-list > > ------------------------------------------------------------------------------ Protect Your Site and Customers from Malware Attacks Learn about various malware tactics and how to avoid them. Understand malware threats, the impact they can have on your business, and how you can protect your company and customers by using code signing. http://p.sf.net/sfu/oracle-sfdevnl _______________________________________________ rpy-list mailing list rpy-list@lists.sourceforge.net https://lists.sourceforge.net/lists/listinfo/rpy-list
