在 R 包的 rcpp 函数中使用自定义 Rcpp class。 class 和函数都在同一个 .cpp 文件中定义

Question

我正在尝试使用 Rcpp 加速 R 数组维度的循环。数组 class 来自 rcpp-gallery: (https://github.com/RcppCore/rcpp-gallery/blob/gh-pages/src/2014-03-21-simple-array-class.Rmd

// [[Rcpp::depends(RcppArmadillo)]]
#include <RcppArmadillo.h>
#include <Rcpp.h>
using namespace Rcpp ;

/*
  ******************************************************************************
  Offset and Array classes based on code by Romain Francois copied from
http://comments.gmane.org/gmane.comp.lang.r.rcpp/5932 on 2014-01-07.
******************************************************************************
  */
  
  class Offset{
    private:
      IntegerVector dim ;
    
    public:
      Offset( IntegerVector dim ) : dim(dim) {}
    
    int operator()( IntegerVector ind ){
      int ret = ind[0] ;
      int offset = 1 ;
      for(int d=1; d < dim.size(); d++) {
        offset = offset * dim[d-1] ; 
        ret = ret + ind[d] * offset ;
      }
      return ret ;
    } ;
    
    IntegerVector getDims() const {
      return(dim) ;
    };
    
  } ;

class Array : public NumericVector {
  private:
    // NumericVector value;
  Offset dims ;
  
  public:
    //Rcpp:as
  Array( SEXP x) : NumericVector(x), 
  dims( (IntegerVector)((RObject)x).attr("dim") ) {}
  
  Array( NumericVector x,  Offset d ): NumericVector(x), 
  dims(d) {}
  
  Array( Dimension d ): NumericVector( d ), dims( d ) {}
  
  IntegerVector getDims() const {
    return(dims.getDims());
  };
  
  NumericVector getValue()  const {
    return(*((NumericVector*)(this)));
  };
  
  inline double& operator()( IntegerVector ind) {
    int vecind = dims(ind);
    NumericVector value = this->getValue();  
    return value(vecind);
  } ;
  
  // change dims without changing order of elements (!= aperm)
  void resize(IntegerVector newdim) {
    int n = std::accumulate((this->getDims()).begin(), (this->getDims()).end(), 1, 
                            std::multiplies<int>());
    int nnew = std::accumulate(newdim.begin(), newdim.end(), 1, 
                               std::multiplies<int>());
    if(n != nnew)  stop("old and new old dimensions don't match.");
    this->dims = Offset(newdim);
  } ;
  
} ;

namespace Rcpp {
  // wrap(): converter from Array to an R array
  template <> SEXP wrap(const Array& A) {
    IntegerVector dims = A.getDims();
    //Dimension dims = A.getDims();
    Vector<REALSXP> x = A;
    x.attr( "dim" ) = wrap(dims);
    return x; 
  }
}


// [[Rcpp::export]]
int runloop(Array& myarray) {
  IntegerVector myarrayDims  = myarray.getDims();
  for (int j = 0; j < myarrayDims[1]; j++) {
    for (int k = 0; k < myarrayDims[2]; k++) {
      for (int l = 0; l < myarrayDims[3]; l++) {
        for (int i = 0; i < myarrayDims[0]; i++) {
          myarray({i, j, k, l}) = i + j + k +l;
        }
      }
    }
  }
  return 0;
}

从交互式 R 会话获取和执行此代码按预期工作。

library(Rcpp)
sourceCpp(file.path(".", "minimalExample.cpp"))

inputArray <- array(data = rnorm(10^4), dim = c(10, 10, 10, 10))
runloop(inputArray)
inputArray

但是，当我将 .cpp 文件移动到我的 R 包结构的 src 文件夹中时，构建失败，因为无法识别 class 数组 (see screenshot of build errors)

构建失败后RcppExports.cpp内容如下：

// Generated by using Rcpp::compileAttributes() -> do not edit by hand
// Generator token: 10BE3573-1514-4C36-9D1C-5A225CD40393

#include <RcppArmadillo.h>
#include <Rcpp.h>

using namespace Rcpp;

// runloop
int runloop(Array& myarray);
RcppExport SEXP _foobar_runloop(SEXP myarraySEXP) {
BEGIN_RCPP
    Rcpp::RObject rcpp_result_gen;
    Rcpp::RNGScope rcpp_rngScope_gen;
    Rcpp::traits::input_parameter< Array& >::type myarray(myarraySEXP);
    rcpp_result_gen = Rcpp::wrap(runloop(myarray));
    return rcpp_result_gen;
END_RCPP
}

static const R_CallMethodDef CallEntries[] = {
    {"_foobar_runloop", (DL_FUNC) &_foobar_runloop, 1},
    {NULL, NULL, 0}
};

RcppExport void R_init_foobar(DllInfo *dll) {
    R_registerRoutines(dll, NULL, CallEntries, NULL, NULL);
    R_useDynamicSymbols(dll, FALSE);
}

如何获得我的简单循环运行？谢谢:)

ps：我在 R-Studio 中的 sessionInfo() returns：

R version 3.6.1 (2019-07-05)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 19041)

Matrix products: default

locale:
[1] LC_COLLATE=English_Germany.1252  LC_CTYPE=English_Germany.1252    LC_MONETARY=English_Germany.1252 LC_NUMERIC=C                    
[5] LC_TIME=English_Germany.1252    

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
[1] Rcpp_1.0.5

loaded via a namespace (and not attached):
[1] compiler_3.6.1 tools_3.6.1

Answer 1

有句话叫先走后走运行。您错过了步行和短跑之间的慢跑步骤 ;-)。

在您提供的单个函数中编译的代码与在 full-blown 包中不同。你想做的可以完成而且已经完成了。简而言之，虽然您在 source 文件中编写了代码，但它还需要出现在 generated file src/RcppExports.cpp 中。

生成代码中的类型 部分的 Rcpp 属性小插图中描述了您现在缺少的一个技巧，我引用（编辑掉 markdown/latex）

Types in Generated Code

In some cases the signatures of the C++ functions that are generated within RcppExports.cpp may have additional type requirements beyond the core standard library and Rcpp types (e.g. CharacterVector, NumericVector, etc.). Examples might include convenience typedefs, as/wrap handlers for marshaling between custom types and SEXP, or types wrapped by the Rcpp XPtr template.

In this case, you can create a header file that contains these type definitions (either defined inline or by including other headers) and have this header file automatically included in RcppExports.cpp. Headers named with the convention pkgname_types are automatically included along with the generated C++ code. For example, if your package is named fastcode then any of the following header files would be automatically included in RcppExports.cpp:
src/fastcode_types.h
src/fastcode_types.hpp
inst/include/fastcode_types.h
inst/include/fastcode_types.hpp
[...]

在 R 包的 rcpp 函数中使用自定义 Rcpp class。 class 和函数都在同一个 .cpp 文件中定义

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Types in Generated Code