Question

我有以下计划。

#include <iostream>
#include <vector>
#include <algorithm>
#include <cassert>
#include <ctime>
#include <cmath>
#include <RInside.h>
using std::cout;
using std::endl;
using std::vector;
using namespace Rcpp;
int main(int argc, char** argv){
    RInside R;
    R.parseEvalQ("set.seed(1)"); Rcpp::RNGScope();
    const Function sample("sample");
    vector<int> vv = as<vector<int> >(sample(NumericVector::create(0,1,2,3), 1e6, true,NumericVector::create(.3,.3,.2,.2)));
    cout<<"1"<<endl<<std::flush;
    const vector<int> vv2 = as<vector<int> >(sample(NumericVector::create(0,1,2,3), 2e6, true,NumericVector::create(.3,.3,.2,.2)));
    cout<<"2"<<endl;
}

输出

1
Segmentation fault

这意味着无法初始化C ++向量vv2。为什么不能分配vv2？

使用内联，这是我得到的：

> body <- '
+ using namespace Rcpp;
+ using std::vector;
+ using std::cout;
+ using std::endl;
+      Rcpp::RNGScope();
+     const Function sample("sample");
+     vector<int> vv = as<vector<int> >(sample(NumericVector::create(0,1,2,3), 1e6, true,NumericVector::create(.3,.3,.2,.2)));
+     cout<<"1"<<endl<<std::flush;
+     const vector<int> vv2 = as<vector<int> >(sample(NumericVector::create(0,1,2,3), 2e6, true,NumericVector::create(.3,.3,.2,.2)));
+     cout<<"2"<<endl;
+     List vecs(2);
+     vecs[1]=vv;
+     vecs[1]=vv2;
+     return(vecs);
+     '
> require( inline )
Loading required package: inline
> require( Rcpp )
Loading required package: Rcpp
Loading required package: int64
> 
> signatures <- NULL
> fx <- cxxfunction( signatures, body, plugin = "Rcpp" )
> a <- fx()

 *** caught segfault ***
address 0x7f2b850eb013, cause 'memory not mapped'

Traceback:
 1: .Primitive(".Call")(<pointer: 0x7f2b8627d2c0>)
 2: fx()

Possible actions:
1: abort (with core dump, if enabled)
2: normal R exit
3: exit R without saving workspace
4: exit R saving workspace

Answer 1

您可以在机器上的R中执行相同的操作吗？ 200万元素相当多。

此外，我几乎从不以这种方式回调R函数，因为它效率低下。如果你想加速，在C ++中重新实现sample()这不会太难。

接下来，我还建议首先通过内联尝试更简单的表达式。

最后，我听起来像是破纪录，试试rcpp-devel列表。

分配大向量的问题

1 个答案: