On 26/03/2014 22:00, peter dalgaard wrote:
On 26 Mar 2014, at 18:24 , Radford Neal <radf...@cs.toronto.edu> wrote:
From: Richard Cotton <richiero...@gmail.com>
The rep function is very versatile, but that versatility comes at a
cost: it takes a bit of effort to learn (and remember) its syntax.
This is a problem, since rep is one of the first functions many
beginners will come across. Of the three main uses of rep, two have
simpler alternatives.
rep(x, times = ) has rep.int
rep(x, length.out = ) has rep_len
I think that a rep_each function would be a worthy addition for the
third use case
rep(x, each = )
(It might also be worth having rep_times as a synonym for rep.int.)
I think this is exactly the wrong approach. Indeed, the aim should be
to get rid of functions like rep.int (or at least discourage their
use, even if they have to be kept for compatibility).
Why is rep_each(x,n) better than rep(x,each=n)? There is no saving in
typing (which would be trivial anyway). There *ought* to be no
significant difference in speed (though that seems to have been the
motive for rep.int). Are you trying to let students learn R without
ever learning about specifying arguments by name?
And where would you stop? How about seq_by(a,b,s) rather than having
to arduously type seq(a,b,by=s)? Maybe we should have glm_binomial,
glm_poisson, etc. so we don't have to remember the "family" argument?
This way lies madness...
Spot on.
Well, maybe a slight disagreement: In a weakly typed language like R, you will
always have performance losses due to type testing and dispatching, and no
compiler/interpreter is intelligent enough to predict the types so that this
can be avoided. Some amout of hinting is needed for reliable speedups, either
by having special functions for simple cases (allowed to make assumptions on
their inputs), or some sort of #pragma-like construction.
Actually, rep.int seems to be a poor example of this since the speedup is
pretty negligible unless you do huge amounts of short replicates. I expect that
the S-PLUS compatibility was the main reason to have it. Case in point:
As the help says:
Function ‘rep.int’ is a simple case handled by internal code, and
provided as a separate function partly for S compatibility and
partly for speed (especially when names can be dropped).
E.g.
> a <- letters[1:10]; names(a) <- a
> system.time(for(i in 1:1000000) rep.int(a,10))
user system elapsed
1.568 0.001 1.574
> system.time(for(i in 1:1000000) rep(a,10))
user system elapsed
2.804 0.002 2.816
There are also rare occasions where it is useful to use rep.int to
circumvent method dispatch.
Note that rep() was an interpreted function when that comment was first
written, and the gap was much larger then. (Nor was it byte-compiled,
nor generic.) For the version of rep in R 0.65.1:
> system.time(for(i in 1:1000000) rep("a",10))
user system elapsed
1.612 0.000 1.616
vs the current
> system.time(for(i in 1:1000000) rep("a",10))
user system elapsed
0.518 0.000 0.519
> system.time(for(i in 1:1000000) rep.int("a",10))
user system elapsed
0.471 0.000 0.473
system.time(for(i in 1:10000000) rep("a",10))
user system elapsed
16.721 0.125 19.037
system.time(for(i in 1:10000000) rep.int("a",10))
user system elapsed
14.356 0.050 14.611
system.time(for(i in 1:1000000) rep("a",1000))
user system elapsed
11.655 2.157 14.263
system.time(for(i in 1:1000000) rep.int("a",1000))
user system elapsed
10.957 1.708 12.917
--
Brian D. Ripley, rip...@stats.ox.ac.uk
Professor of Applied Statistics, http://www.stats.ox.ac.uk/~ripley/
University of Oxford, Tel: +44 1865 272861 (se3lf)
1 South Parks Road, +44 1865 272866 (PA)
Oxford OX1 3TG, UK Fax: +44 1865 272595
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