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

[Hervé Pagès]

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

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
>>
>>
>>
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>> R-devel at r-project.org mailing list
>> https://stat.ethz.ch/mailman/listinfo/r-devel
>>
>
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> https://stat.ethz.ch/mailman/listinfo/r-devel

-- 
Hervé Pagès

Program in Computational Biology
Division of Public Health Sciences
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