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arma::colvecRcppArmadillo ベクトル (例: ) をRcpp ベクトル ( )に変換しようとしていNumericVectorます。temp がオブジェクトであると仮定すると、最初に に変換してから (たとえば ) に変換arma::colvecできることがわかっています)。しかし、それを行う良い方法は何ですか?SEXPSEXPNumericVectoras<NumericVector>(wrap(temp)arma::colvec

arma::colvecオブジェクトをパラメーターとしてオブジェクトに渡してもよいかどうかわからないという理由だけで、それを行いたいのですRcpp::Function。

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3 に答える 3

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I was trying to Evaluate a Rcpp::Function with argument arma::vec, it seems that it takes the argument in four forms without compilation errors. That is, if f is a Rcpp::Function and a is a arma::vec, then

  1. f(a)
  2. f(wrap(a))
  3. f(as<NumericVector>(wrap(a)))
  4. f(NumericVector(a.begin(),a.end()))

produce no compilation and runtime errors, at least apparently.

For this reason, I have conducted a little test for the four versions of arguments. Since I suspect that somethings will go wrong in garbage collection, I test them again gctorture.

gctorture(on=FALSE)
Rcpp::sourceCpp(code = '
#include <RcppArmadillo.h>
// [[Rcpp::depends(RcppArmadillo)]]

using namespace Rcpp;

// [[Rcpp::export]]
double foo1(arma::vec a, arma::vec b, Function f){
    double sum = 0.0;
    for(int i=0;i<100;i++){
        sum += as<double>(f(a, b));
    }
    return sum;
}

// [[Rcpp::export]]
double foo2(arma::vec a, arma::vec b, Function f){
    double sum = 0.0;
    for(int i=0;i<100;i++){
        sum += as<double>(f(wrap(a),wrap(b)));
    }
    return sum;
}

// [[Rcpp::export]]
double foo3(arma::vec a, arma::vec b, Function f){
    double sum = 0.0;
    for(int i=0;i<100;i++){
        sum += as<double>(f(as<NumericVector>(wrap(a)),as<NumericVector>(wrap(b))));
    }
    return sum;
}

// [[Rcpp::export]]
double foo4(arma::vec a, arma::vec b, Function f){
    double sum = 0.0;
    for(int i=0;i<100;i++){
        sum += as<double>(f(NumericVector(a.begin(),a.end()),NumericVector(b.begin(),b.end())));
    }
    return sum;
}
')
# note that when gctorture is on, the program will be very slow as it
# tries to perfrom GC for every allocation.
# gctorture(on=TRUE)
f = function(x,y) {
    mean(x) + mean(y)
}
# all three functions should return 700
foo1(c(1,2,3), c(4,5,6), f) # error
foo2(c(1,2,3), c(4,5,6), f) # wrong answer (occasionally)!
foo3(c(1,2,3), c(4,5,6), f) # correct answer
foo4(c(1,2,3), c(4,5,6), f) # correct answer

As a result, the first method produces an error, the second method produces a wrong answer and only the third and the fourth method return the correct answer.

> # they should return 700
> foo1(c(1,2,3), c(4,5,6), f) # error
Error: invalid multibyte string at '<80><a1><e2>'
> foo2(c(1,2,3), c(4,5,6), f) # wrong answer (occasionally)!
[1] 712
> foo3(c(1,2,3), c(4,5,6), f) # correct answer
[1] 700
> foo4(c(1,2,3), c(4,5,6), f) # correct answer
[1] 700

Note that, if gctorture is set FALSE, then all functions will return a correct result.

> foo1(c(1,2,3), c(4,5,6), f) # error
[1] 700
> foo2(c(1,2,3), c(4,5,6), f) # wrong answer (occasionally)!
[1] 700
> foo3(c(1,2,3), c(4,5,6), f) # correct answer
[1] 700
> foo4(c(1,2,3), c(4,5,6), f) # correct answer
[1] 700

It means that method 1 and method 2 are subjected to break when garbage is collected during runtime and we don't know when it happens. Thus, it is dangerous to not wrap the parameter properly.

Edit: as of 2017-12-05, all four conversions produce the correct result.

  1. f(a)
  2. f(wrap(a))
  3. f(as<NumericVector>(wrap(a)))
  4. f(NumericVector(a.begin(),a.end()))

and this is the benchmark 

> microbenchmark(foo1(c(1,2,3), c(4,5,6), f), foo2(c(1,2,3), c(4,5,6), f), foo
3(c(1,2,3), c(4,5,6), f), foo4(c(1,2,3), c(4,5,6), f))
Unit: milliseconds
                            expr      min       lq     mean   median       uq
 foo1(c(1, 2, 3), c(4, 5, 6), f) 2.575459 2.694297 2.905398 2.734009 2.921552
 foo2(c(1, 2, 3), c(4, 5, 6), f) 2.574565 2.677380 2.880511 2.731615 2.847573
 foo3(c(1, 2, 3), c(4, 5, 6), f) 2.582574 2.701779 2.862598 2.753256 2.875745
 foo4(c(1, 2, 3), c(4, 5, 6), f) 2.378309 2.469361 2.675188 2.538140 2.695720
      max neval
 4.186352   100
 5.336418   100
 4.611379   100
 3.734019   100

And f(NumericVector(a.begin(),a.end())) is marginally faster than other methods.

于 2014-03-12T07:08:26.340 に答える
1

同じ質問がありました。forループのいくつかのレイヤーのコアで変換を行うためにラップを使用しましたが、非常に遅かったです。速度を遅くするのはラップ機能のせいだと思うので、これを行うエレガントな方法があるかどうか知りたいです。

レイモンドの質問については、Rcpp::as<Rcpp::NumericVector>(wrap(A))代わりに次のような名前空間を含めるか、using namespace Rcpp;コードの先頭に行を含めることをお勧めします。

于 2013-01-12T19:47:18.203 に答える