[Rcpp-devel] trying to insert a number as first element of already existing vector
Serguei Sokol
serguei.sokol at gmail.com
Mon Dec 10 14:42:19 CET 2018
Le 10/12/2018 à 13:04, Jan van der Laan a écrit :
> Small addendum: A large part of the performance gain in my example comes
> from using NumericVector instead of std::vector<double>. Which avoids a
> conversion. An example using std::copy with Numeric vector runs in the
> same time as the version using memcpy.
Yep.
Few more percents of mean cpu time can be saved by using "const &" trick :
// [[Rcpp::export]]
NumericVector mybar5(const NumericVector &x, const NumericVector &y) {
NumericVector result(x.size() + y.size());
std::memcpy(result.begin(), x.begin(), x.size()*sizeof(double));
std::memcpy(result.begin()+x.size(), y.begin(),
y.size()*sizeof(double));
return result;
}
# output
Unit: microseconds
expr min lq mean median uq
max
c(testelem, testvec) 258.343 338.3110 418.0047 343.4450 378.7850
3077.347
mybar(testvec, testelem) 352.699 366.8770 498.3948 374.6635 450.4420
3046.408
mybar2(testvec, testelem) 334.820 348.3685 425.0098 354.7240 366.5270
3024.128
mybar3(testvec, testelem) 233.689 244.8640 315.7256 247.5180 255.0955
2945.068
mybar4(testvec, testelem) 232.083 241.9655 340.0751 245.0035 252.8260
2934.312
mybar5(testvec, testelem) 150.787 242.7685 285.4264 245.9465 254.1880
2049.493
Serguei.
>
> Jan
>
>
>
> On 10-12-18 12:28, Jan van der Laan wrote:
>>
>> For performance memcpy is probably fastest. This gives the same
>> performance a c().
>>
>> // [[Rcpp::export]]
>> NumericVector mybar3(NumericVector x, double firstelem) {
>> NumericVector result(x.size() + 1);
>> result[0] = firstelem;
>> std::memcpy(result.begin()+1, x.begin(), x.size()*sizeof(double));
>> return result;
>> }
>>
>>
>> Or a more general version concatenating vector of arbitrary lengths:
>>
>>
>> // [[Rcpp::export]]
>> NumericVector mybar4(NumericVector x, NumericVector y) {
>> NumericVector result(x.size() + y.size());
>> std::memcpy(result.begin(), x.begin(), x.size()*sizeof(double));
>> std::memcpy(result.begin()+x.size(), y.begin(),
>> y.size()*sizeof(double));
>> return result;
>> }
>>
>>
>>
>> > n=1E7
>> > testvec = c(1,seq_len(n))
>> > testelem <- 7
>> > microbenchmark(c(testelem, testvec), mybar(testvec,testelem),
>> + mybar2(testvec,testelem),
>> + mybar3(testvec,testelem),
>> + mybar4(testvec,testelem)
>> + )
>> Unit: milliseconds
>> expr min lq mean median
>> uq max neval
>> c(testelem, testvec) 36.48577 36.93754 41.10550 43.76742
>> 44.20709 46.09741 100
>> mybar(testvec, testelem) 102.54042 103.21756 106.88749 104.32033
>> 110.31527 119.55512 100
>> mybar2(testvec, testelem) 95.64696 96.19447 100.24691 102.61380
>> 103.58189 109.28290 100
>> mybar3(testvec, testelem) 36.45794 36.87915 40.43486 37.18063
>> 43.49643 95.49049 100
>> mybar4(testvec, testelem) 36.51334 37.05409 41.39680 43.20627
>> 43.57958 94.95482 100
>>
>>
>> Best,
>> Jan
>>
>>
>>
>> On 10-12-18 12:10, Serguei Sokol wrote:
>>> Le 09/12/2018 à 09:35, Mark Leeds a écrit :
>>>> Hi All: I wrote below and it works but I have a strong feeling
>>>> there's a better way to do it.
>>> If performance is an issue, you can save few percents of cpu time by
>>> using std::copy() instead of explicit for loop. Yet, for this
>>> operation R's c() remains the best bet. It is more then twice faster
>>> than both Rcpp versions below:
>>>
>>> #include <Rcpp.h>
>>> using namespace Rcpp;
>>>
>>> // [[Rcpp::export]]
>>> std::vector<double> mybar(const std::vector<double>& x, double
>>> firstelem) {
>>> std::vector<double> tmp(x.size() + 1);
>>> tmp[0] = firstelem;
>>> for (int i = 1; i < (x.size()+1); i++)
>>> tmp[i] = x[i-1];
>>> return tmp;
>>> }
>>> // [[Rcpp::export]]
>>> std::vector<double> mybar2(const std::vector<double>& x, double
>>> firstelem) {
>>> std::vector<double> tmp(x.size() + 1);
>>> tmp[0] = firstelem;
>>> std::copy(x.begin(), x.end(), tmp.begin()+1);
>>> return tmp;
>>> }
>>>
>>> /*** R
>>> library(microbenchmark)
>>> n=100000
>>> testvec = c(1,seq_len(n))
>>> testelem <- 7
>>> microbenchmark(c(testelem, testvec), mybar(testvec,testelem),
>>> mybar2(testvec,testelem))
>>> */
>>>
>>> # Ouput
>>> Unit: microseconds
>>> expr min lq mean
>>> median uq
>>> c(testelem, testvec) 247.098 248.5655 444.8657 257.3300
>>> 630.7725
>>> mybar(testvec, testelem) 594.978 622.3560 1226.5683 637.0230
>>> 1386.8385
>>> mybar2(testvec, testelem) 576.191 604.7565 1029.2124 616.1055
>>> 1351.6740
>>> max neval
>>> 7587.977 100
>>> 22149.605 100
>>> 11651.831 100
>>>
>>>
>>> Best,
>>> Serguei.
>>>
>>>> I looked on the net and found some material from back in ~2014 about
>>>> concatenating
>>>> vectors but I didn't see anything final about it. Thanks for any
>>>> insights.
>>>>
>>>> Also, the documentation for Rcpp is beyond incredible (thanks to
>>>> dirk, romain, kevin and all the other people I'm leaving out ) but
>>>> is there a general methodology for finding equivalents of R
>>>> functions. For example, if I want a cumsum function in Rcpp, how do
>>>> I know whether to use the stl with accumulate or if there's already
>>>> one built in so
>>>> that I just call cumsum.
>>>>
>>>> Thanks.
>>>>
>>>> #=======================================================
>>>>
>>>> #include <Rcpp.h>
>>>> using namespace Rcpp;
>>>>
>>>> // [[Rcpp::export]]
>>>> std::vector<double> mybar(const std::vector<double>& x, double
>>>> firstelem) {
>>>> std::vector<double> tmp(x.size() + 1);
>>>> tmp[0] = firstelem;
>>>> for (int i = 1; i < (x.size()+1); i++)
>>>> tmp[i] = x[i-1];
>>>> return tmp;
>>>> }
>>>>
>>>> /*** R
>>>>
>>>> testvec = c(1,2,3)
>>>> testelem <- 7
>>>> mybar(testvec,testelem)
>>>>
>>>> */
>>>>
>>>> #===============================
>>>> # OUTPUT FROM RUNNING ABOVE
>>>> #=================================
>>>> > testvec <- c(1,2,3)
>>>> > testelem <- 7
>>>> > mybar(testvec,testelem)
>>>> [1] 7 1 2 3
>>>> >
>>>>
>>>>
>>>>
>>>>
>>>>
>>>>
>>>>
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>>>>
>>>
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