[Rd] Patch proposal for R style consistency (concerning deparse.c)

[Paul Johnson]

Hello, everybody.

I recognize I'm asking you to deal with a not-very-important problem.
But its important to me :)

I've noticed a little inconsistency in the print.function() output. I
traced the matter to deparse.c, for which I attach a patch that
addresses 3 separate things. There's one important thing that I'm
willing to stand behind and 2 litter things that I think would be
good, but won't argue too much about. I ask if this is a legitimate
wishlist item in your bug tracker.

Here are the changes I'm trying to achieve.

1. I want this:

} else {

and not the current
   }
      else {

2 & 3. I want to omit space after if and for.   Since if and for are
functions in R, not keywords, I suggest that there should not be a
space before the opening parentheses.

Item 1 brings the output into line with the advice of the help page
for "if".  The output looks more like the a randomly selected R file
from the R source or the recommended packages. I'm teaching new users
that they should study the R source code itself as a guide for
programming (http://pj.freefaculty.org/R/Rstyle.pdf).  My argument
there would go more smoothly if print.function obeyed the "} else {"
policy that most of your source code and packages adhere to. We do see
r-help questions about the problem that user code can't be run
line-by-line, even when it is styled like the print.function() output.

As you know, this is discussed in R Extensions Section 3.1 on tidying
R code.  In my opinion, the current approach makes code less tidy,
rather than more.

Consider an excerpt from the top of predict.glm.R.  This R code is
correctly formatted, it is consistent with most of the rest of R:

  if (!se.fit) {
        ## No standard errors
        if(missing(newdata)) {
            pred <- switch(type,
                           link = object$linear.predictors,
                           response = object$fitted.values,
                           terms = predict.lm(object,  se.fit=se.fit,
                               scale = 1, type="terms", terms=terms)
                           )
            if(!is.null(na.act)) pred <- napredict(na.act, pred)
        } else {

But the output from '> predict.glm' is not as good:

   if (!se.fit) {
        if (missing(newdata)) {
            pred <- switch(type, link = object$linear.predictors,
                response = object$fitted.values, terms = predict.lm(object,
                  se.fit = se.fit, scale = 1, type = "terms",
                  terms = terms))
            if (!is.null(na.act))
                pred <- napredict(na.act, pred)
        }
        else {


I have applied the attached patch with R 3.0.0. I don't see any damage
from it, just more tidier output:

> predict.glm
function (object, newdata = NULL, type = c("link", "response",
    "terms"), se.fit = FALSE, dispersion = NULL, terms = NULL,
    na.action = na.pass, ...)
{
    type <- match.arg(type)
    na.act <- object$na.action
    object$na.action <- NULL
    if(!se.fit) {
        if(missing(newdata)) {
            pred <- switch(type, link = object$linear.predictors,
                response = object$fitted.values, terms = predict.lm(object,
                  se.fit = se.fit, scale = 1, type = "terms",
                  terms = terms))
            if(!is.null(na.act))
                pred <- napredict(na.act, pred)
        } else {
            pred <- predict.lm(object, newdata, se.fit, scale = 1,
                type = ifelse(type == "link", "response", type),
                terms = terms, na.action = na.action)
            switch(type, response = {
                pred <- family(object)$linkinv(pred)
            }, link = , terms = )
        }
    } else {

Of course, you know much better than I do what else might break as a
result of this change.

In case the email list processor scrubs the patch, please try here:
http://pj.freefaculty.org/scraps/deparse-pj-20130417.patch

pj

--
Paul E. Johnson
Professor, Political Science      Assoc. Director
1541 Lilac Lane, Room 504      Center for Research Methods
University of Kansas                 University of Kansas
http://pj.freefaculty.org               http://quant.ku.edu