rcpp

I have a large, wide data.table (20m rows) keyed by a person ID but with lots of columns (~150) that have lots of null values. Each column is a recorded state / attribute that I wish to carry forward for each person. Each person may have anywhere from 10 to 10,000 observations and there are about 500,000 people in the set. Values from one person can not 'bleed' into the following person, so my solution must respect the person ID column and group appropriately. For demonstration purposes - here's a very small sample input: DT = data.table( id=c(1, 1, 1, 1, 2, 2, 2, 2, 3, 3, 3, 3), aa=c("A", NA,

In R when using the cxxfunction from the inline package , how does one change the optimization flag for the cpp compiler? By default, on my machine, it compiles with -g -O2 . But I would like to use the -O3 optimization to gain speed. I use the Rcpp plugin if that makes any difference. I have tried creating my own plugin, and I have tried to set the different arguments of the cxxfunction but nothing worked. I guess one option would be to compile it using R CMD SHLIB instead of using cxxfunction . But Rcpp recommends the use of inline because most of their test cases are using it. thanks for

I want to replicate the following R function in Rcpp : fR = function(x) x[1:2] fR(c(1,2,3)) #[1] 1 2 fR(c('a','b','c')) #[1] "a" "b" I can do it for a fixed output type like so: library(inline) library(Rcpp) fint = cxxfunction(signature(x = "SEXP"), ' List xin(x); IntegerVector xout; for (int i = 0; i < 2; ++i) xout.push_back(xin[i]); return xout;', plugin = "Rcpp") But this will only work for integers, and if I try replacing the xout type with List (or GenericVector , which are the same) - it works with any input type, but I get back a list instead of a vector. What's the correct Rcpp way of

Recently I've been experimenting with Rcpp (inline) to generate DLLs that perform various tasks on supplied R inputs. I'd like to be able to debug the code in these DLLs line by line, given a specific set of R inputs. (I'm working under Windows.) To illustrate, let's consider a specific example that anybody should be able to run... The code below is a really simple cxxfunction which simply doubles the input vector. Note however that there's an additional variable myvar that changes value a few times but doesn't affect the output - this has been added so that we'll be able to see when the

I'm writing an Rcpp module an would like to return as one element of the RcppResultSet list a list whose elements are vectors. E.g., .Call("myfunc")$foo should be something like: [[1]] [1] 1 [[2]] [1] 1 1 [[3]] [1] 1 1 1 (the exact numbers are not important here). The issue is that I don't know the right Rcpp way of doing this. I tried passing a vector<vector<int> > but this constructs a matrix by silently taking the length of the first vector as the width (even if the matrix is ragged!). I've tried constructing an RcppList but have a hard time casting various objects (like RcppVector ) safely

I am trying to understand the role and relationship of the macros/variables set in ~/.R/Makevars and package_directory/src/Makevars when installing/building own R packages. Suppose these files look like ~/.R/Makevars CXX = g++ CXXSTD = -std=c++11 CXXFLAGS = -fsanitize=undefined,address -fno-omit-frame-pointer CXX98 = g++ CXX98STD = -std=c++98 CXX11 = g++ CXX11STD = -std=c++11 CXX14 = g++ CXX14STD = -std=c++14 package_directory/src/Makevars PKG_CPPFLAGS = -I../inst/include CXX_STD = CXX11 As I understand it, with CXX we can select the compiler for C++ when building R packages, with CXXSTD we