当我期望R中的数据帧输出时，为什么Rccp返回类似列表的输出？

分类：编程问答

如何解决当我期望R中的数据帧输出时，为什么Rccp返回类似列表的输出？

我正在尝试编写一个.cpp文件，该文件接受一个输入向量，并输出一个两列数据帧，其中包含来自输​​入向量的所有可能组合。我的输出给出了所需的值，但没有给出数据框。如何更改.cpp文件以获取数据帧输出？

我的 possible_combos.cpp 文件如下所示：

#include <Rcpp.h>
using namespace Rcpp;

// [[Rcpp::export]]
GenericVector C_all_combos(GenericVector a) {
  int vec_length = a.size();
  int vec_length_sq = vec_length*vec_length; 
  GenericVector expand_vector_a(vec_length_sq);
  GenericVector expand_vector_b(vec_length_sq);  
  for (int i=0; i<vec_length_sq; i++) { expand_vector_a[i] = a[i / vec_length]; };
  for (int i=0; i<vec_length_sq; i++) { expand_vector_b[i] = a[i % vec_length]; };
  DataFrame my_df = DataFrame::create(Named("v_1") = expand_vector_a,Named("v_2") = expand_vector_b);
return my_df;
}

/*** R
C_all_combos(c(1,"Cars",2.3))
  */

运行Rcpp::sourceCpp("possible_combos.cpp")所需的输出是：

    v_1    v_2
    1       1
    1       Cars
    1       2.3
    Cars    1
    Cars    Cars
    Cars    2.3
    2.3     1
    2.3     Cars
    2.3     2.3

但是我得到的是：

    v_1..1. v_1..1..1 v_1..1..2 v_1..Cars. v_1..Cars..1 v_1..Cars..2 v_1..2.3. v_1..2.3..1 v_1..2.3..2
1       1         1         1       Cars         Cars         Cars       2.3         2.3         2.3
  v_2..1. v_2..Cars. v_2..2.3. v_2..1..1 v_2..Cars..1 v_2..2.3..1 v_2..1..2 v_2..Cars..2 v_2..2.3..2
1       1       Cars       2.3         1         Cars         2.3         1         Cars         2.3

感谢任何提示！我熟悉expand.grid()之类的出色R函数，但想尝试其他方法。

解决方法

主要问题是Rcpp::GenericVector是list，因此行为与R一致。我在下面显示了此信息，并给出了一种使用模板函数针对每种输入类型的特殊情况的解决方案 

#include <Rcpp.h>
using namespace Rcpp;

// essentially your code
// [[Rcpp::export]]
DataFrame C_all_combos(GenericVector a) {
  size_t const vec_length = a.size(),vec_length_sq = vec_length * vec_length; 
  GenericVector expand_vector_a(vec_length_sq),expand_vector_b(vec_length_sq);  
  
  for (size_t i = 0; i < vec_length_sq; i++){ 
    expand_vector_a[i] = a[i / vec_length];
    expand_vector_b[i] = a[i % vec_length];
  }
  
  return DataFrame::create(_["v_1"] = expand_vector_a,_["v_2"] = expand_vector_b,_["stringsAsFactors"] = false);
}

// template function used in the new solution
template<class T>
DataFrame C_all_combos_gen(T a) {
  size_t const vec_length = a.size(),vec_length_sq = vec_length * vec_length; 
  T expand_vector_a(vec_length_sq),_["stringsAsFactors"] = false);
}

// export particular versions
// [[Rcpp::export]]
DataFrame C_all_combos_int(IntegerVector a){
  return C_all_combos_gen<IntegerVector>(a);
}

// [[Rcpp::export]]
DataFrame C_all_combos_char(CharacterVector a){
  return C_all_combos_gen<CharacterVector>(a);
}

// [[Rcpp::export]]
DataFrame C_all_combos_num(NumericVector a){
  return C_all_combos_gen<NumericVector>(a);
}

// [[Rcpp::export]]
DataFrame C_all_combos_log(LogicalVector a){
  return C_all_combos_gen<LogicalVector>(a);
}

我们现在可以运行以下R代码

  1. 说明您的代码中的行为与R一致。
  2. 表明该解决方案有效。
######
# the issue with your code. Repeat your call
C_all_combos(c(1,"Cars",2.3))
#R>   v_1..1. v_1..1..1 v_1..1..2 v_1..Cars. v_1..Cars..1 v_1..Cars..2 v_1..2.3. v_1..2.3..1 v_1..2.3..2 v_2..1. v_2..Cars. v_2..2.3. v_2..1..1 v_2..Cars..1 v_2..2.3..1 v_2..1..2
#R> 1       1         1         1       Cars         Cars         Cars       2.3         2.3         2.3       1       Cars       2.3         1         Cars         2.3         1
#R>   v_2..Cars..2 v_2..2.3..2
#R> 1         Cars         2.3

# amounts to doing the following in R which yields the same
all_combs <- expand.grid(v_1 = c(1,2.3),v_2 = c(1,stringsAsFactors = FALSE)
data.frame(v_1 = as.list(all_combs$v_2),v_2 = as.list(all_combs$v_1))
#R>   v_1..1. v_1..1..1 v_1..1..2 v_1..Cars. v_1..Cars..1 v_1..Cars..2 v_1..2.3. v_1..2.3..1 v_1..2.3..2 v_2..1. v_2..Cars. v_2..2.3. v_2..1..1 v_2..Cars..1 v_2..2.3..1 v_2..1..2
#R> 1       1         1         1       Cars         Cars         Cars       2.3         2.3         2.3       1       Cars       2.3         1         Cars         2.3         1
#R>   v_2..Cars..2 v_2..2.3..2
#R> 1         Cars         2.3

######
# here is a solution with the template function
C_all_combos_R <- function(a){
  if(is.logical(a))
    return(C_all_combos_log(a))
  else if(is.integer(a))
    return(C_all_combos_int(a))
  else if(is.numeric(a))
    return(C_all_combos_num(a))
  else if(is.character(a))
    return(C_all_combos_char(a))
  
  stop("C_all_combos_R not implemented")
}

# it works
C_all_combos_R(c(1,2.3))
#R>    v_1  v_2
#R> 1    1    1
#R> 2    1 Cars
#R> 3    1  2.3
#R> 4 Cars    1
#R> 5 Cars Cars
#R> 6 Cars  2.3
#R> 7  2.3    1
#R> 8  2.3 Cars
#R> 9  2.3  2.3

在C ++等中进行类型检查

您还可以在C ++中进行所有类型检查，避免使用昂贵的整数除法和模运算，并避免像AEF这样的DataFrame构造函数

#include <Rcpp.h>
using namespace Rcpp;

template<int T>
SEXP C_all_combos_gen_two(Vector<T> a) {
  size_t const vec_length = a.size(),vec_length_sq = vec_length * vec_length; 
  Vector<T> expand_vector_a(vec_length_sq),expand_vector_b(vec_length_sq);  
  
  size_t i(0L);
  for(size_t jj = 0L; jj < vec_length; ++jj)
    for(size_t ii = 0L; ii < vec_length; ++i,++ii){
      expand_vector_a[i] = a[jj];
      expand_vector_b[i] = a[ii];
    }
  
  List out = List::create(_["v_1"] = expand_vector_a,_["v_2"] = expand_vector_b);
  
  out.attr("class") = "data.frame";
  out.attr("row.names") = Rcpp::seq(1,vec_length_sq);
  
  return out;
}

// [[Rcpp::export]]
SEXP C_all_combos_cpp(SEXP a){
  switch( TYPEOF(a) ){
  case INTSXP : return C_all_combos_gen_two<INTSXP>(a);
  case REALSXP: return C_all_combos_gen_two<REALSXP>(a);
  case STRSXP : return C_all_combos_gen_two<STRSXP>(a);
  case LGLSXP : return C_all_combos_gen_two<LGLSXP>(a);
  case VECSXP : return C_all_combos_gen_two<VECSXP>(a);
  default: Rcpp::stop("C_all_combos_cpp not implemented");
  }
  
  return DataFrame();
}

新版本产生

C_all_combos_cpp(c(1,2.3))
#R>    v_1  v_2
#R> 1    1    1
#R> 2    1 Cars
#R> 3    1  2.3
#R> 4 Cars    1
#R> 5 Cars Cars
#R> 6 Cars  2.3
#R> 7  2.3    1
#R> 8  2.3 Cars
#R> 9  2.3  2.3

，与AEF's解决方案相比，它是快速的

C_all_combos_cpp(c(1,2.3))

options(digits = 3)
library(bench)
mark(C_all_combos_cpp = C_all_combos_cpp(c(1,2.3)),AEF              = C_all_combos_aef(c(1,check = FALSE)
#R> # A tibble: 2 x 13
#R>   expression            min   median `itr/sec` mem_alloc `gc/sec` n_itr  n_gc total_time  
#R>   <bch:expr>       <bch:tm> <bch:tm>     <dbl> <bch:byt>    <dbl> <int> <dbl>   <bch:tm> 
#R> 1 C_all_combos_cpp   4.05µs   5.49µs   169097.    6.62KB     16.9  9999     1     59.1ms
#R> 2 AEF               15.76µs  16.96µs    57030.    2.49KB     45.7  9992     8    175.2ms

larger_num <- rnorm(100)
mark(C_all_combos_cpp = C_all_combos_cpp(larger_num),AEF              = C_all_combos_aef(larger_num),check = FALSE)
#R> # A tibble: 2 x 13
#R>   expression            min   median `itr/sec` mem_alloc `gc/sec` n_itr  n_gc total_time
#R>   <bch:expr>       <bch:tm> <bch:tm>     <dbl> <bch:byt>    <dbl> <int> <dbl>   <bch:tm>
#R> 1 C_all_combos_cpp   30.9µs   37.7µs    20817.     198KB     88.0  6862    29      330ms
#R> 2 AEF               167.9µs  178.4µs     5558.     199KB     21.5  2585    10      465ms

为完整起见，这是多余的C ++代码

// [[Rcpp::export]]
SEXP C_all_combos_aef(GenericVector a) {
  int vec_length = a.size();
  int vec_length_sq = vec_length * vec_length;
  GenericVector expand_vector_a(vec_length_sq);
  GenericVector expand_vector_b(vec_length_sq);
  for (int i=0; i<vec_length_sq; i++) { expand_vector_a[i] = a[i / vec_length]; };
  for (int i=0; i<vec_length_sq; i++) { expand_vector_b[i] = a[i % vec_length]; };
  
  List my_df = List::create(Named("v_1") = expand_vector_a,Named("v_2") = expand_vector_b);
  
  
  my_df.attr("class") = "data.frame";
  my_df.attr("row.names") = Rcpp::seq(1,vec_length_sq);
  
  return my_df;
}
,

如另一个答案所述，GenericVector是一个列表，并且不能使用Rcpp DataFrame构造函数创建具有List列的DataFrame。但是，您可以创建一个List并将其手动转换为data.frame，并将其返回为SEXP：

#include <Rcpp.h>
using namespace Rcpp;

// [[Rcpp::export]]
SEXP C_all_combos(GenericVector a) {
  int vec_length = a.size();
  int vec_length_sq = vec_length*vec_length;
  GenericVector expand_vector_a(vec_length_sq);
  GenericVector expand_vector_b(vec_length_sq);
  for (int i=0; i<vec_length_sq; i++) { expand_vector_a[i] = a[i / vec_length]; };
  for (int i=0; i<vec_length_sq; i++) { expand_vector_b[i] = a[i % vec_length]; };

  List my_df = List::create(Named("v_1") = expand_vector_a,Named("v_2") = expand_vector_b);


  my_df.attr("class") = "data.frame";
  my_df.attr("row.names") = Rcpp::seq(1,vec_length_sq);

  return my_df;
}

/*** R
C_all_combos(c(1,2.3))
*/

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