rcpp

问题 This question was migrated from Cross Validated because it can be answered on Stack Overflow. Migrated 3 years ago . 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

问题 I am creating a DataFrame to hold a parsed haproxy http log files which has quite a few fields (25+). If I add more than 20 vectors (one for each field), I get the compilation error: no matching function call to 'create' The create method: return DataFrame::create( _["clientIp"] = clientIp, _["clientPort"] = clientPort, _["acceptDate"] = acceptDate, _["frontendName"] = frontendName, _["backendName"] = backendName, _["serverName"] = serverName, _["tq"] = tq, _["tw"] = tw, _["tc"] = tc, _["tr"]

问题 I upgraded from R-3.1 to R-3.2. OK ( Standard upgrade) But this upgrade seems to have lost all the installed packages ( ggplot2, quantmod, Rcpp among dozens and dozens of others). So installed many from the RStudio tools menu option. Most were successful. But problem with Rcpp (when installing as dependency from ggplot2). The same issue occurs when installing package data.table : Warning in install.packages : unable to move temporary installation ‘C:\Users\euclid\Documents\R\win-library\3.2

问题 I have a new iMac and I'm trying to run code using the Rcpp library that has been working on both my old iMac and Macbook Pro without issue. I have tried everything I can't seem to figure out what the issue is. Xcode 5.0 downloaded. Command line Tools then installed. R3.0.2 is installed. I downloaded a gcc compiler. When I type gcc in terminal - I get "clang:" - which is good, I think. The error I get is copied below. Thanks in advance for any ideas and advice. Error (in R console): llvm-g++

问题 I need to evaluate a function (posterior distribution) which requires long loops. Clearly I don't want to do this within R itself, and so I'm using "inline" and "Rcpp" to implement C++. However, I'm finding that in the case where each loop uses an R function, the cxxfunction is running just as slow as running the R code (see code and output below). In particular, I'm needing to use a multivariate normal cumulative distribution function within each loop, and so I'm using pmvnorm() from the

问题 As an OpenMP & Rcpp performance test I wanted to check how fast I could calculate the Mandelbrot set in R using the most straightforward and simple Rcpp + OpenMP implementation. Currently what I did was: #include <Rcpp.h> #include <omp.h> // [[Rcpp::plugins(openmp)]] using namespace Rcpp; // [[Rcpp::export]] Rcpp::NumericMatrix mandelRcpp(const double x_min, const double x_max, const double y_min, const double y_max, const int res_x, const int res_y, const int nb_iter) { Rcpp::NumericMatrix

问题 I made a first stab at an Rcpp function via inline and it solved my speed problem (thanks Dirk!): R: Replacing negative values by zero The initial version looked like this: library(inline) cpp_if_src <- ' Rcpp::NumericVector xa(a); int n_xa = xa.size(); for(int i=0; i < n_xa; i++) { if(xa[i]<0) xa[i] = 0; } return xa; ' cpp_if <- cxxfunction(signature(a="numeric"), cpp_if_src, plugin="Rcpp") But when called cpp_if(p) , it overwrote p with the output, which was not as intended. So I assumed it

问题 I've written a function in Rcpp and compiled it with inline . Now, I want to run it in parallel on different cores, but I'm getting a strange error. Here's a minimal example, where the function funCPP1 can be compiled and runs well by itself, but cannot be called by snow 's clusterCall function. The function runs well as a single process, but gives the following error when ran in parallel: Error in checkForRemoteErrors(lapply(cl, recvResult)) : 2 nodes produced errors; first error: NULL value

问题 I am trying to reimplement an R function using C++ and RCpp to speed up the computation. And in the C++ implementation, I need to use a Fortran function mvtdst found in link. #include <Rcpp.h> #include "mvtnorm.h" using namespace Rcpp; // [[Rcpp::export]] NumericVector pmvnorm_rcpp(NumericVector upper, NumericMatrix corr) { double error; double mvnP = pmvnorm_P(2, upper, corr, &error) ; return mvnP ; } /*** R pmvnorm_rcpp(c(1.5,1.5),c(0.0)) */ Here, pmvnorm_P is defined in the mvtnorm.cpp

问题 Closed. This question is off-topic. It is not currently accepting answers. Want to improve this question? Update the question so it's on-topic for Stack Overflow. Closed 2 years ago . I am a newbie trying to learn data structure and algorithm implementation using Standard Template Library (STL) in Rcpp. I am trying to implement a very basic hash table using unordered_map in Rcpp, taking a hint from Hadley's Advanced R Here is the C++ code I want to implement in Rcpp (taken from element14 blog