Dear Martin,
Thanks a lot for your help, apologies for this very late reply. I decided to go with your suggestion, write a regular function. I guess this avoids doing obj <- as(foo(as(obj, 'Base')), 'Derived') and then repopulating the extra slots of of the 'Derived' class. Regards, gopi. On Wed, Feb 25, 2009 at 9:36 AM, Martin Morgan <mtmor...@fhcrc.org> wrote: > Hi Gopi -- > > Gopi Goswami <grgosw...@gmail.com> writes: > >> Hi there, >> >> >> I want to write helper functions for a base class, which will be used >> by its subclasses in the S4 world. This function ___will___ update >> certain slots of its argument object. Please help me decide which one >> of the following is a better approach with respect to coding style, >> memory usage and speed: >> > > My opinion: > >> o Write a regular function. > > memory and speed > >> o Declare a generic and implement it just for the base class. > > coding 'style', but style is subjective. > > There are other aspects of S4, e.g., type checking, method dispatch, > programmatically defined and discoverable API, ... (positives), > cumbersome documentation (negative). > > My usual pattern of development is to be seduced by the siren of > speed, only to regret boxing myself in. > > I find that my S4 objects typically serve as containers for > coordinating other entities. The important methods typically extract > R 'base' objects from the S4 class, manipulate them, and repackage the > result as S4. The time and speed issues are in the manipulation, not > in the extraction / repackaging. This is contrast to, say, an > implementation of a tree-like data structure with a collection of > 'Node' objects, where tree operations would require access to each > object and would be horribly slow in S4 (and perhaps R when nodes were > represented as a list, say, at least compared to a C-level > representation, or an alternative representation that took advantage > of R's language characteristics). > > Martin > >> >> Thanks for sharing your insight and time, >> gopi. >> http://gopi-goswami.net/ >> >> ______________________________________________ >> R-devel@r-project.org mailing list >> https://stat.ethz.ch/mailman/listinfo/r-devel > > -- > Martin Morgan > Computational Biology / Fred Hutchinson Cancer Research Center > 1100 Fairview Ave. N. > PO Box 19024 Seattle, WA 98109 > > Location: Arnold Building M2 B169 > Phone: (206) 667-2793 > ______________________________________________ R-devel@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-devel
