[Rd] R-devel does not update the C++ returned variables

[Hervé Pagès]

On 03/02/2015 01:00 PM, Hervé Pagès wrote:
> Hi,
>
> On 03/02/2015 12:18 PM, Dénes Tóth wrote:
>>
>>
>> On 03/02/2015 04:37 PM, Martin Maechler wrote:
>>>
>>>> On 2 March 2015 at 09:09, Duncan Murdoch wrote:
>>>> | I generally recommend that people use Rcpp, which hides a lot of the
>>>> | details.  It will generate your .Call calls for you, and generate the
>>>> | C++ code that receives them; you just need to think about the real
>>>> | problem, not the interface.  It has its own learning curve, but I
>>>> think
>>>> | it is easier than using the low-level code that you need to work
>>>> with .Call.
>>>
>>>> Thanks for that vote, and I second that.
>>>
>>>> And these days the learning is a lot flatter than it was a decade ago:
>>>
>>>> R> Rcpp::cppFunction("NumericVector doubleThis(NumericVector x) {
>>>> return(2*x); }")
>>>> R> doubleThis(c(1,2,3,21,-4))
>>>> [1]  2  4  6 42 -8
>>>> R>
>>>
>>>> That defined, compiled, loaded and run/illustrated a simple function.
>>>
>>>> Dirk
>>>
>>> Indeed impressive,  ... and it also works with integer vectors
>>> something also not 100% trivial when working with compiled code.
>>>
>>> When testing that, I've went a step further:
>>>
>>> ##---- now "test":
>>> require(microbenchmark)
>>> i <- 1:10
>>
>> Note that the relative speed of the algorithms also depends on the size
>> of the input vector. i + i becomes the winner for longer vectors (e.g. i
>> <- 1:1e6), but a proper Rcpp version is still approximately twice as
>> fast.
>
> The difference in speed is probably due to the fact that R does safe
> arithmetic. C or C++ do not:
>
>    > doubleThisInt(i)
>    [1]  2147483642  2147483644  2147483646          NA -2147483646
> -2147483644
>
>    > 2L * i
>    [1] 2147483642 2147483644 2147483646         NA         NA         NA
>    Warning message:
>    In 2L * i : NAs produced by integer overflow

That was with

   i <- as.integer(2^30-4) + 1:6

Cheers,
H.

>
> H.
>
>>
>> Rcpp::cppFunction("NumericVector doubleThisNum(NumericVector x) {
>> return(2*x); }")
>> Rcpp::cppFunction("IntegerVector doubleThisInt(IntegerVector x) {
>> return(2*x); }")
>> i <- 1:1e6
>> mb <- microbenchmark::microbenchmark(doubleThisNum(i), doubleThisInt(i),
>> i*2, 2*i, i*2L, 2L*i, i+i, times=100)
>> plot(mb, log="y", notch=TRUE)
>>
>>
>>> (mb <- microbenchmark(doubleThis(i), i*2, 2*i, i*2L, 2L*i, i+i,
>>> times=2^12))
>>> ## Lynne (i7; FC 20), R Under development ... (2015-03-02 r67924):
>>> ## Unit: nanoseconds
>>> ##           expr min  lq      mean median   uq   max neval cld
>>> ##  doubleThis(i) 762 985 1319.5974   1124 1338 17831  4096   b
>>> ##          i * 2 124 151  258.4419    164  221 22224  4096  a
>>> ##          2 * i 127 154  266.4707    169  216 20213  4096  a
>>> ##         i * 2L 143 164  250.6057    181  234 16863  4096  a
>>> ##         2L * i 144 177  269.5015    193  237 16119  4096  a
>>> ##          i + i 152 183  272.6179    199  243 10434  4096  a
>>>
>>> plot(mb, log="y", notch=TRUE)
>>> ## hmm, looks like even the simple arithm. differ slightly ...
>>> ##
>>> ## ==> zoom in:
>>> plot(mb, log="y", notch=TRUE, ylim = c(150,300))
>>>
>>> dev.copy(png, file="mbenchm-doubling.png")
>>> dev.off() # [ <- why do I need this here for png ??? ]
>>> ##--> see the appended *png graphic
>>>
>>> Those who've learnt EDA or otherwise about boxplot notches, will
>>> know that they provide somewhat informal but robust pairwise tests on
>>> approximate 5% level.
>>>  From these, one *could* - possibly wrongly - conclude that
>>> 'i * 2' is significantly faster than both 'i * 2L' and also
>>> 'i + i' ---- which I find astonishing, given that  i is integer here...
>>>
>>> Probably no reason for deep thoughts here, but if someone is
>>> enticed, this maybe slightly interesting to read.
>>>
>>> Martin Maechler, ETH Zurich
>>>
>>>
>>>
>>> ______________________________________________
>>> R-devel at r-project.org mailing list
>>> https://stat.ethz.ch/mailman/listinfo/r-devel
>>>
>>
>> ______________________________________________
>> R-devel at r-project.org mailing list
>> https://stat.ethz.ch/mailman/listinfo/r-devel
>

-- 
Hervé Pagès

Program in Computational Biology
Division of Public Health Sciences
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