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
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