David: Thanks! Is it generally frowned upon (if I'm Incorporating this into a package) to "override" a generic function like "predict", even if I plan on making it a pass-through function (same parameters, and if the data type doesn't match my "weird" data type, it will simply pass the parameters through to the generic S3 "predict")?
--j On Mon, Mar 17, 2014 at 4:08 AM, David Winsemius <dwinsem...@comcast.net> wrote: > S3 classes only dispatch on the basis of the first parameter class. That was > one of the reasons for the development of S4-classed objects. You say you > have the expectation that the object is of a class that has an ordinary > `predict` method presumably S3 in character, so you probably need to write a > function that will mask the existing method. You would rewrite the existing > test for the existence of 'newdata' and the the definition of the new > function would persist through the rest of the session and could be > source()-ed in further sessions. > > -- > David. > > > On Mar 16, 2014, at 2:09 PM, Jonathan Greenberg wrote: > >> R-helpers: >> >> I'm having some trouble with this one -- I figure because I'm a bit of >> a noob with S3 classes... Here's my challenge: I want to write a >> custom predict statement that is triggered based on the presence and >> class of a *newdata* parameter (not the "object" parameter). The >> reason is I am trying to write a custom function based on an oddly >> formatted dataset that has been assigned an R class. If the predict >> function "detects" it (class(newdata) == "myweirdformat") it does a >> conversion of the newdata to what most predict statements expect (e.g. >> a dataframe) and then passes the converted dataset along to the >> generic predict statement. If newdata is missing or is not of the odd >> class it should just pass everything along to the generic predict as >> usual. >> >> What would be the best way to approach this problem? Since (my >> understanding) is that predict is dispatched based on the object >> parameter, this is causing me confusion -- my object should still >> remain the model, I'm just allowing a new data type to be fed into the >> predict model(s). >> >> Cheers! >> >> --j >> >> -- >> Jonathan A. Greenberg, PhD >> Assistant Professor >> Global Environmental Analysis and Remote Sensing (GEARS) Laboratory >> Department of Geography and Geographic Information Science >> University of Illinois at Urbana-Champaign >> 259 Computing Applications Building, MC-150 >> 605 East Springfield Avenue >> Champaign, IL 61820-6371 >> Phone: 217-300-1924 >> http://www.geog.illinois.edu/~jgrn/ >> AIM: jgrn307, MSN: jgrn...@hotmail.com, Gchat: jgrn307, Skype: jgrn3007 >> >> ______________________________________________ >> 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. > > David Winsemius > Alameda, CA, USA > -- Jonathan A. Greenberg, PhD Assistant Professor Global Environmental Analysis and Remote Sensing (GEARS) Laboratory Department of Geography and Geographic Information Science University of Illinois at Urbana-Champaign 259 Computing Applications Building, MC-150 605 East Springfield Avenue Champaign, IL 61820-6371 Phone: 217-300-1924 http://www.geog.illinois.edu/~jgrn/ AIM: jgrn307, MSN: jgrn...@hotmail.com, Gchat: jgrn307, Skype: jgrn3007 ______________________________________________ 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.
