>From commits to R devel, I saw attempts to speed up subsetting and
'match', and to cache results of conversion of small nonnegative
integers to character string. That's good.
I am sorry for pushing, still.
Is the partial new behavior of function 'factor' with respect to NA
really worthy?
match(xlevs, nlevs)[f] looks nice, too.
- Using
f <- match(xlevs, nlevs)[f]
instead of
f <- match(xlevs[f], nlevs)
for remapping
- Remapping only if length(nlevs) differs from length(xlevs)
Applying changes similar to above to function 'levels<-.factor' will
not change 'levels<-.factor' result at all. So, the corresponding
part of functions 'factor' and 'levels<-.factor' can be kept
in sync.
--------------------------------------------
Subject: Re: [Rd] Function 'factor' issues
To: r-devel at r-project.org
Date: Sunday, 22 October, 2017, 6:43 AM
My idea (like in https://bugs.r-project.org/bugzilla/attachment.cgi?id=1540 ):
- For remapping, use
f <- match(xlevs, nlevs)[f]
instead of
f <- match(xlevs[f], nlevs)
(I have mentioned it).
- Remap only if length(nlevs) differs from length(xlevs) .
[snip]
--------------------------------------------
On Wed, 18/10/17, Martin Maechler <maechler at stat.math.ethz.ch> wrote:
Subject: Re: [Rd] Function 'factor' issues
Cc: r-devel at r-project.org
Date: Wednesday, 18 October, 2017, 11:54 PM
>>>>> Suharto Anggono Suharto Anggono via R-devel <r-devel at
r-project.org>
>>>>> on Sun, 15 Oct 2017 16:03:48 +0000 writes:
> In R devel, function 'factor' has been changed, allowing and
merging duplicated 'labels'.
Indeed. That had been asked for and discussed a bit on this
list from June 14 to June 23, starting at
https://stat.ethz.ch/pipermail/r-devel/2017-June/074451.html
> Issue 1: Handling of specified 'labels' without duplicates is
slower than before.
> Example:
> x <- rep(1:26, 40000)
> system.time(factor(x, levels=1:26, labels=letters))
> Function 'factor' is already rather slow because of conversion
to character. Please don't add slowdown.
Indeed, I doo see a ~ 20% performance loss for the example
above, and I may get to look into this.
However, in R-devel there have been important internal
changes (ALTREP additions) some of which are currently giving
some performance losses in some cases (but they have the
potential to give big performance _gains_ e.g. for simple
indexing into large vectors which may apply here !).
For factor(), these C level "ALTREP" changes may not be the reason at
all for the slow down;
I may find time to investigate further.
{{ For the ALTREP-change slowdowns I've noticed in some
indexing/subset operations, we'll definitely have time to look into
before R-devel is going to be released next spring... and as mentioned,
these operations may even become considerably faster *thanks*
to ALTREP ... }}
> Issue 2: While default 'labels' is 'levels', not
specifying 'labels' may be different from specifying 'labels' to
be the same as 'levels'.
> Example 1:
> as.integer(factor(c(NA,2,3), levels = c(2, NA), exclude = NULL))
> is different from
> as.integer(factor(c(NA,2,3), levels = c(2, NA), labels = c(2, NA),
exclude = NULL))
You are right. But this is not so exceptional and part of the new feature of
'labels' allowing to "fix up" things in such cases. While it
would be nice if this was not the case the same phenomenon
happens in other functions as well because of lazy evaluation.
I think I had noticed that already and at the time found
"not easy" to work around.
(There are many aspects about changing such important base functions:
1. not breaking back compatibility ((unless in rare
border cases, where we are sure it's worth))
2. Keeping code relatively transparent
3. Keep the semantics "simple" to document and as intuitive as
possible
)
> File reg-tests-1d.R indicates that 'factor' behavior with NA is
slightly changed, for the better. NA entry (because it is unmatched to
'levels' argument or is in 'exclude') is absorbed into NA in
"levels" attribute (comes from 'labels' argument), if any. The
issue is that it happens only when 'labels' is specified.
I'm not sure anymore, but I think I had noticed that also in
June, considered to change it and found that such a changed
factor() would be too different from what it has "always been".
So, yes, IIRC, this current behavior is on purpose, if only for back
compatibility.
> Function 'factor' could use match(xlevs, nlevs)[f]. It
doesn't match NA to NA level. When 'f' is long enough, longer than
'xlevs', it is faster than match(xlevs[f], nlevs).
> Example 2:
> With
> levs <- c("A","A") ,
> factor(levs, levels=levs)
> gives error, but
> factor(levs, levels=levs, labels=levs)
> doesn't.
yes, again that is a consequence of what you said above (before
'Example 1')
> Note: In theory, if function 'factor' merged duplicated
'labels' in all cases, at least in
> factor(c(sqrt(2)^2, 2)) ,
> function 'factor' could do matching on original 'x'
(without conversion to character), as in R before version 2.10.0. If function
'factor' did it,
> factor(c(sqrt(2)^2, 2), levels = c(sqrt(2)^2, 2), labels =
c("sqrt(2)^2", "2"))
> could take sqrt(2)^2 and 2 as distinct.
Well, that may be interesting.. but I doubt if that's somewhere
we should go, easily, because factor() has been documented to do
what it does now (with very slightly rounding such numbers via as.character(.))
and hence such a change would typically lead to much work for
too many people.
I do see that indeed the as.character(.) inside factor() takes
most of the CPU time used in largish factor() examples [as your
first], and indeed, for the case of integer 'x', we really could
be much faster in factor construction.
[snip]
