Comment (caveat emptor): If I understand correctly, your difficulties all stem from your use of the word "script," which betrays a fundamental misunderstanding of the nature of R as a programming language.
R is based (mostly) on the concepts of functional programming. So instead of doing what as you have done -- spreading mishmosh of code around in a bunch of files -- all that code should be made into functions. These then can be organized formally into a package (with documentation, namespaces, etc.) or informally into a saved .Rdata file. In either case, the whole thing then functions as an organic whole. By doing as you have done (are you a former SAS or maybe JAVA programmer?) you are contravening the programming strategy around which R is built, leaving you with a clumsy mess. This is not to say that you can't get it to work -- you probably can. Only that it's a mess. Moral: Use R as it is intended to be used, not as you would like it to be used. Cheers, Bert On Thu, Apr 19, 2012 at 12:57 PM, Alexander <juschitz_alexan...@yahoo.de> wrote: > Hi > > thank you for your suggestions, but I am not sure if I explained my problem > well enough. Lets asume, that I have 30 different script files and 1 script > which calls these 30 scripts one after the other by "source". Some of the 30 > scripts only contain definitions of functions which are called in other > scripts, some only execute code, load, save, and interact with the user via > tcl tk. Together they represent a big programm which asks from the user a > lot of input, treats and manipulates the input. At the end, the user obtains > some results files. > As there are many script sources during the execution, there are a lot of > different variables initialized etc... Some are only of temporary need, some > are necessary for later steps in other scripts. > Now the question: Is there any methodology to ensure the running ? For > example after every script I could save the whole workingspace into > script1.Rdata, delete all variable which are not needed in a later script > (perhabs a little bit difficult to manage that, but possible), and continue > with the execution. > > I don't know if I was able to describe my problem more precisely. > > Alexander > > cberry wrote >> >> Alexander, >> >> If Tal's suggestion to use caching in Sweave doesn't appeal to you, you >> might look at 'R.cache' and other packages mentioned in >> >> http://cran.r-project.org/web/views/ReproducibleResearch.html >> >> under 'Caching of R Objects'. >> >> However, an advantage of the Sweave-like approaches is that you can >> generate a brief report that includes the versions of scripts used, >> summarizes the data processing, and gives intermediate results for later >> inspection and sanity checks. >> >> HTH, >> >> Chuck >> >> Tal Galili <tal.galili@> writes: >> >>> Hi Alexander, >>> Saving full environments is possible, but it is very easy to start >>> loosing >>> track on where each variable came from. >>> You might want to use this process: >>> http://www.r-bloggers.com/a-better-way-of-saving-and-loading-objects-in-r/ >>> It depends on how many variables you work with, but it might help. >>> >>> Another way is to do all of the work through Sweave, and combine it with >>> caching: http://cran.r-project.org/web/packages/cacheSweave/index.html >>> This will ensure that every code chunk will keep the variables you >>> created, >>> without the need to re-run the code from scratch. >>> >>> For extracting data from outside sources, I would often use the first >>> method, and for analysis I would use the later option. >>> >>> Good luck, >>> Tal >>> >>> >>> ----------------Contact >>> Details:------------------------------------------------------- >>> Contact me: Tal.Galili@ | 972-52-7275845 >>> Read me: www.talgalili.com (Hebrew) | www.biostatistics.co.il (Hebrew) | >>> www.r-statistics.com (English) >>> ---------------------------------------------------------------------------------------------- >>> >>> >>> >>> >>> On Thu, Apr 19, 2012 at 11:15 AM, Alexander >>> <juschitz_alexander@>wrote: >>> >>>> Hello, I am working under R2.11 Windows and currently I work on a big R >>>> progjet which executes different R script in a row. Every R script >>>> represents a module. As every module depends of the variables created in >>>> the >>>> modules previously executed, I want to be shure, that I don't create or >>>> change a variable in a scriptwithout being aware that this affects the >>>> results in a later executed script. Therefore, I was think to save all >>>> important variables to keep in a seperate "backup" environment. >>>> Everytime a >>>> script starts, it loads the variables of the "backup" environment in >>>> .GlobalEnv. At the end of the script, I want to add all new obtained >>>> variables to the "backup" environment (and check automaticaly if any >>>> variables of "backup"environment is going to be overwritten) and clean >>>> the >>>> workspace .GlobalEnv to start the next script neat and tidy. What do you >>>> think of this solution? Does anyone have better ideas or experience to >>>> share? >>>> >>>> Thank you in advance >>>> >>>> Alexander >>>> >>>> -- >>>> View this message in context: >>>> http://r.789695.n4.nabble.com/working-with-environments-to-ensure-code-quality-for-long-R-scripts-tp4570195p4570195.html >>>> Sent from the R help mailing list archive at Nabble.com. >>>> >>>> ______________________________________________ >>>> R-help@ 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. >>>> >>> >>> [[alternative HTML version deleted]] >>> >> >> -- >> Charles C. Berry Dept of Family/Preventive >> Medicine >> cberry at ucsd edu UC San Diego >> http://famprevmed.ucsd.edu/faculty/cberry/ La Jolla, San Diego 92093-0901 >> >> ______________________________________________ >> R-help@ 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. >> > > > -- > View this message in context: > http://r.789695.n4.nabble.com/working-with-environments-to-ensure-code-quality-for-long-R-scripts-tp4570195p4571989.html > Sent from the R help mailing list archive at Nabble.com. > > ______________________________________________ > 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. -- Bert Gunter Genentech Nonclinical Biostatistics Internal Contact Info: Phone: 467-7374 Website: http://pharmadevelopment.roche.com/index/pdb/pdb-functional-groups/pdb-biostatistics/pdb-ncb-home.htm ______________________________________________ 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.
