[FORGED] Re: identical() versus sapply()
On 11/04/2016 10:18 PM, Bert Gunter wrote:
"The documentation aims to be accurate, not necessarily clear." !!! I hope that is not the case! Accurate documentation that is confusing is not very useful.
I don't think it is ever intentionally confusing, but it is often concise to the point of obscurity. Words are chosen carefully, and explanations are not repeated. It takes an effort to read it. It will be clear to careful readers, but not to all readers. I was thinking of the statement quoted earlier, 'as(x, "numeric") uses the existing as.numeric function'. That is different than saying 'as(x, "numeric") is the same as as.numeric(x)'. Duncan Murdoch I understand that it is challenging to write docs
that are both clear and accurate; but I hope that is always the goal. Cheers, Bert Bert Gunter "The trouble with having an open mind is that people keep coming along and sticking things into it." -- Opus (aka Berkeley Breathed in his "Bloom County" comic strip ) On Mon, Apr 11, 2016 at 6:09 PM, Duncan Murdoch <murdoch.duncan at gmail.com> wrote:
On 11/04/2016 8:25 PM, Paulson, Ariel wrote:
Hi Jeff, We are splitting hairs because R is splitting hairs, and causing us problems. Integer and numeric are different R classes with different properties, mathematical relationships notwithstanding. For instance, the counterintuitive result:
The issue here is that R has grown. The as() function is newer than the as.numeric() function, it's part of the methods package. It is a much more complicated thing, and there are cases where they differ. In this case, the problem is that is(1L, "numeric") evaluates to TRUE, and nobody has written a coerce method that specifically converts "integer" to "numeric". So the as() function defaults to doing nothing. It takes a while to do nothing, approximately 360 times longer than as.numeric() takes to actually do the conversion:
microbenchmark(as.numeric(1L), as(1L, "numeric"))
Unit: nanoseconds
expr min lq mean median uq max neval
as.numeric(1L) 133 210 516.92 273.5 409.5 9444 100
as(1L, "numeric") 51464 64501 119294.31 99768.5 138321.0 1313669 100
R performance is not always simple and easy to predict, but I think anyone
who had experience with R would never use as(x, "numeric"). So this just
isn't a problem worth fixing.
Now, you might object that the documentation claims they are equivalent, but
it certainly doesn't. The documentation aims to be accurate, not
necessarily clear.
Duncan Murdoch
identical(as.integer(1), as.numeric(1))
[1] FALSE Unfortunately the reply-to chain doesn't extend far enough -- here is the original problem:
sapply(1, identical, 1)
[1] TRUE
sapply(1:2, identical, 1)
[1] FALSE FALSE
sapply(1:2, function(i) identical(as.numeric(i),1) )
[1] TRUE FALSE
sapply(1:2, function(i) identical(as(i,"numeric"),1) )
[1] FALSE FALSE These are the results of R's hair-splitting!
Ariel
________________________________
From: Jeff Newmiller <jdnewmil at dcn.davis.ca.us>
Sent: Monday, April 11, 2016 6:49 PM
To: Bert Gunter; Paulson, Ariel
Cc: Rolf Turner; r-help at r-project.org
Subject: Re: [R] [FORGED] Re: identical() versus sapply()
Hypothesis regarding the thought process: integer is a perfect subset of
numeric, so why split hairs?
--
Sent from my phone. Please excuse my brevity.
On April 11, 2016 12:36:56 PM PDT, Bert Gunter <bgunter.4567 at gmail.com>
wrote:
Indeed!
Slightly simplified to emphasize your point:
class(as(1:2,"numeric"))
[1] "integer"
class(as.numeric(1:2))
[1] "numeric"
whereas in ?as it says:
"Methods are pre-defined for coercing any object to one of the basic
datatypes. For example, as(x, "numeric") uses the existing as.numeric
function. "
I suspect this is related to my ignorance of S4 classes (i.e. as() )
and how they relate to S3 classes, but I certainly don't get it
either.
Cheers,
Bert
Bert Gunter
"The trouble with having an open mind is that people keep coming along
and sticking things
into it."
-- Opus (aka Berkeley Breathed in his "Bloom County" comic strip )
On Mon, Apr 11, 2016 at 9:30 AM, Paulson, Ariel <apa at stowers.org> wrote:
Ok, I see the difference between 1 and 1:2, I'll just leave it as one of
those "only in R" things.
But it seems then, that as.numeric() should guarantee a FALSE outcome,
yet it does not.
To build on what Rolf pointed out, I would really love for someone to
explain this one:
str(1)
num 1
str(1:2)
int [1:2] 1 2
str(as.numeric(1:2))
num [1:2] 1 2
str(as(1:2,"numeric"))
int [1:2] 1 2
Which doubly makes no sense. 1) Either the class is "numeric" or it
isn't; I did not call as.integer() here. 2) method of recasting should not
affect final class.
Thanks,
Ariel
-----Original Message-----
From: Rolf Turner [mailto:r.turner at auckland.ac.nz]
Sent: Saturday, April 09, 2016 5:27 AM
To: Jeff Newmiller
Cc: Paulson, Ariel; 'r-help at r-project.org'
Subject: Re: [FORGED] Re: [R] identical() versus sapply()
On 09/04/16 16:24, Jeff Newmiller wrote:
I highly
recommend making friends with the str function. Try
str( 1 )
str( 1:2 )
Interesting. But to me counter-intuitive. Since R makes no distinction
between scalars and vectors of length 1 (or more accurately I think, since
in R there is *no such thing as a scalar*, only a vector of length
1) I don't see why "1" should be treated in a manner that is
categorically different from the way in which "1:2" is treated.
Can you, or someone else with deep insight into R and its rationale,
explain the basis for this difference in treatment?
for the clue you need, and then
sapply( 1:2, identical, 1L )
cheers,
Rolf
--
Technical Editor ANZJS
Department of Statistics
University of Auckland
Phone: +64-9-373-7599 ext. 88276
________________________________
R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see
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.
[[alternative HTML version deleted]]
______________________________________________
R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see
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.