[Rd] C vs. C++ as learning and development tool for R
I have 3 years of experience with R and have an interest in becoming a better programmer so that I might someday be able to contribute packages. Other than R, my only experience was taking Lisp from Daniel Friedman in the 1970's. I would like to learn either C or C++ for several reasons: To gain a better concept of object oriented programming so that I can begin to use S4 methods in R. To perhaps speed up some things I do repeatedly in R To be able to contribute a package someday. I have been doing some reading and from what I can tell R is more compatible with C, but C++ has much greater capabilities for OO programming. I have just started reading The C++ Programming Language: Special Edition by Bjarne Stroustrup http://search.barnesandnoble.com/booksearch/results.asp?ATH=Bjarne+Stro ustrupz=y , he recommends first learning C++ and then then C if necessary, but as a developer of C++, he is probably biased. I would greatly appreciate the advice of the R developers and package contributors on this subject. C or C++? Thanks, Mark Mark W. Kimpel MD Official Business Address: Department of Psychiatry Indiana University School of Medicine PR M116 Institute of Psychiatric Research 791 Union Drive Indianapolis, IN 46202 Preferred Mailing Address: 15032 Hunter Court Westfield, IN 46074 (317) 490-5129 Work, Mobile (317) 663-0513 Home (no voice mail please) 1-(317)-536-2730 FAX [[alternative HTML version deleted]] __ R-devel@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-devel
Re: [Rd] C vs. C++ as learning and development tool for R
Thanks to all for your excellent suggestions. I think will I proceed working through the Stroustrup book. He has a section on comparing C with C++ and one on working with legacy C code that may prove helpful. I also have a C for Dummies (something like that, I don't have it right next to me) that I have also been reading. A couple of follow-up questions: 1. As I understand it, if I just wanted to distribute compiled code, I could use whatever extended C or C++ libraries that I wanted to use, however, since R is open source and people need to be able to compile things themselves, I imagine I would get into trouble (figuratively) using, say, the C++ STL. Would I need to distribute these files as well? For example, iostream instead of stdio.h. Or, should I just not use those? 2. For those of you who develop C on Windows (probably a small bunch!), what is your preferred development environment? I have the free Borland Turbo C++ and Visual C++ 6.0 (I knew enough to stay away from .NET). I tried to install the C++ module for Eclipse and, for me at least, it was a nightmare. I am not UNIX or DOS savvy and setting path variables and the like just made things too complicated. 3. Lastly, is there a C or C++ community similar to R that I could address questions relating to those languages to? I don't want to abuse the R list as I learn. Thanks, Mark Mark W. Kimpel MD (317) 490-5129 Work, Mobile (317) 663-0513 Home (no voice mail please) 1-(317)-536-2730 FAX __ R-devel@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-devel
[Rd] lazyLoadDBfetch error
I am getting the following output when I try to load R package gmodels under R-devel. This does not occur in R 2.3.1. In searching the R archives it appears that this message regarding lazyLoadDBfetch should not be occurring in recent R releases. I have redownloaded R-devel and gmodels and the problem persists. Ideas? Thanks, Mark require(gmodels) Loading required package: gmodels Error in lazyLoadDBfetch(key, datafile, compressed, envhook) : internal error in R_decompress1 [1] FALSE sessionInfo() R version 2.4.0 Under development (unstable) (2006-06-15 r38348) i386-pc-mingw32 locale: LC_COLLATE=English_United States.1252;LC_CTYPE=English_United States.1252;LC_MONETARY=English_United States.1252;LC_NUMERIC=C;LC_TIME=English_United States.1252 attached base packages: [1] splines tools methods stats graphics grDevices utils datasets base other attached packages: gtools gdataGOstats Category hgu95av2 KEGG multtest xtable RBGL annotate GO graph Ruuid limma 2.2.32.1.21.6.01.4.1 1.10.01.8.11.9.5 1.3-21.8.1 1.10.01.6.5 1.11.9 1.10.02.7.5 genefilter survival rgu34a affy affyioBiobaseRWinEdt 1.10.1 2.26 1.12.0 1.10.01.1.3 1.10.01.7-4 Mark W. Kimpel MD Official Business Address: Department of Psychiatry Indiana University School of Medicine PR M116 Institute of Psychiatric Research 791 Union Drive Indianapolis, IN 46202 Preferred Mailing Address: 15032 Hunter Court Westfield, IN 46074 (317) 490-5129 Work, Mobile (317) 663-0513 Home (no voice mail please) 1-(317)-536-2730 FAX __ R-devel@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-devel
