I was wondering whether it is possible to make an infix function, e.g. A %o% B with Rcpp.
I know that this is possible using the inline package, but have yet been able to find a method for doing this when using sourceCpp().
I have made the following infix implementation of %o% / outer() when arguments are sure to be vectors using RcppEigen and inline:
`%op%` <- cxxfunction(signature(v1="NumericVector",
v2="NumericVector"),
plugin = "RcppEigen",
body = c("
NumericVector xx(v1);
NumericVector yy(v2);
const Eigen::Map<Eigen::VectorXd> x(as<Eigen::Map<Eigen::VectorXd> >(xx));
const Eigen::Map<Eigen::VectorXd> y(as<Eigen::Map<Eigen::VectorXd> >(yy));
Eigen::MatrixXd op = x * y.transpose();
return Rcpp::wrap(op);
"))
This can easily be implemented in to be imported using sourceCpp(), however not as an infix function.
My current attempt is as follows:
#include <Rcpp.h>
using namespace Rcpp;
#include <RcppEigen.h>
// [[Rcpp::depends(RcppEigen)]]
// [[Rcpp::export]]
NumericMatrix outerProd(NumericVector v1, NumericVector v2) {
NumericVector xx(v1);
NumericVector yy(v2);
const Eigen::Map<Eigen::VectorXd> x(as<Eigen::Map<Eigen::VectorXd> >(xx));
const Eigen::Map<Eigen::VectorXd> y(as<Eigen::Map<Eigen::VectorXd> >(yy));
Eigen::MatrixXd op = x * y.transpose();
return Rcpp::wrap(op);
}
So to summarize my question.. Is it possible to make an infix function available through sourceCpp?
Is it possible to make an infix function available through sourceCpp?
Yes.
As always, one should read the Rcpp vignettes!
In particular here, if you look in Section 1.6 of the Rcpp attributes vignette, you'd see you can modify the name of a function using the name parameter for Rcpp::export.
For example, we could do:
#include <Rcpp.h>
// [[Rcpp::export(name = `%+%`)]]
Rcpp::NumericVector add(Rcpp::NumericVector x, Rcpp::NumericVector y) {
return x + y;
}
/*** R
1:3 %+% 4:6
*/
Then we'd get:
Rcpp::sourceCpp("~/infix-test.cpp")
> 1:3 %+% 4:6
[1] 5 7 9
So, you still have to name C++ functions valid C++ names in the code, but you can export it to R through the name parameter of Rcpp::export without having to do anything further on the R side.
John Chambers states three principles on page four of the (highly recommended) "Extending R" book:
Everything that exists in R is an object.
Everything that happens in R is a function call.
Interfaces to other software are part of R.
So per point two, you can of course use sourceCpp() to create your a compiled function and hang that at any odd infix operator you like.
Code Example
library(Rcpp)
cppFunction("std::string cc(std::string a, std::string b) { return a+b; }")
`%+%` <- function(a,b) cc(a,b)
cc("Hello", "World")
"hello" %+% "world"
Output
R> library(Rcpp)
R> cppFunction("std::string cc(std::string a, std::string b) { return a+b; }")
R> `%+%` <- function(a,b) cc(a,b)
R>
R> cc("Hello", "World")
[1] "HelloWorld"
R>
R> "hello" %+% "world"
[1] "helloworld"
R>
Summary
Rcpp is really just one cog in the machinery.
Edit
It also works with your initial function, with some minor simplification. For
`%op%` <- cppFunction("Eigen::MatrixXd op(Eigen::VectorXd x, Eigen::VectorXd y) { Eigen::MatrixXd op = x * y.transpose(); return op; }", depends="RcppEigen")
as.numeric(1:3) %op% as.numeric(3:1)
we get
R> `%op%` <- cppFunction("Eigen::MatrixXd op(Eigen::VectorXd x, Eigen::VectorXd y) { Eigen::MatrixXd op = x * y.transpose(); return op; }", depends="RcppEigen")
R> as.numeric(1:3) %op% as.numeric(3:1)
[,1] [,2] [,3]
[1,] 3 2 1
[2,] 6 4 2
[3,] 9 6 3
R>
(modulo some line noise from the compiler).
I want to access non-consecutive matrix elements and then pass the sub-selection to (for instance) the sum() function. In the example below I get a compile error about invalid conversion.
I am relatively new to Rcpp, so I am sure the answer is simple. Perhaps I am missing some type of cast?
#include <Rcpp.h>
using namespace Rcpp;
// [[Rcpp::plugins("cpp11")]]
double sumExample() {
// these are the matrix row elements I want to sum (the column in this example will be fixed)
IntegerVector a = {2,4,6};
// create 10x10 matrix filled with random numbers [0,1]
NumericVector v = runif(100);
NumericMatrix x(10, 10, v.begin());
// sum the row elements 2,4,6 from column 0
double result = sum( x(a,0) );
return(result);
}
You were close. Indexing uses [] only -- see this write up at the Rcpp Gallery -- and you missed the export tag. The main issue is that compound expresssion are sometimes too much for the compiler and the template programming. So it works if you take it apart.
Corrected Code
#include <Rcpp.h>
using namespace Rcpp;
// [[Rcpp::plugins("cpp11")]]
// [[Rcpp::export]]
double sumExample() {
// these are the matrix row elements I want to sum
// (the column in this example will be fixed)
IntegerVector a = {2,4,6};
// create 10x10 matrix filled with random numbers [0,1]
NumericVector v = runif(100);
NumericMatrix x(10, 10, v.begin());
// sum the row elements 2,4,6 from column 0
NumericVector z1 = x.column(0);
NumericVector z2 = z1[a];
double result = sum( z2 );
return(result);
}
/*** R
sumExample()
*/
Demo
R> Rcpp::sourceCpp("~/git/stackoverflow/56739765/question.cpp")
R> sumExample()
[1] 0.758416
R>
I have a matrix of the form
vector<vector<int>> K
which has size NxN. How can i swap two elements of this vector say K[i]k[j] with K[n-j][i]?
In general, how can i swap two elements of an 2D vector?
Because vector's [] operator returns a reference, a std::swap() will work. For example:
swap(K[i][j], K[n-i][i]);
The general swapping could look something like this
void swap(int& a, int& b)
{
int temp = a;
a = b;
b = tmp;
}
Then you call it with
swap(K[i][j], K[n - j][i]);
Or you can just call std::swap as #Jeffrey suggests
I want to create a sequence of integer numbers for indexing within a matrix. The R pendant would be:
indexRow <- max(0,1):min(2,12)
matrix1[indexRow, ]
This is what i have tried in Rcpp to create the sequence of integers:
#include <Rcpp.h>
#include <algorithm>
#include <vector>
#include <numeric>
using namespace Rcpp;
using namespace std;
// [[Rcpp::export]]
NumericVector test(NumericVector x) {
IntegerVector indexRow = Rcpp::seq_along(max(0, 1), min(1, 12));
}
However I get the Error message:
no matching function for call to 'seq_along(const int&, const int&)'
How can I create a sequence of integers in Rcpp?
Here is a possible Rcpp implementation :
library(Rcpp)
cppFunction(plugins='cpp11','NumericVector myseq(int &first, int &last) {
NumericVector y(abs(last - first) + 1);
if (first < last)
std::iota(y.begin(), y.end(), first);
else {
std::iota(y.begin(), y.end(), last);
std::reverse(y.begin(), y.end());
}
return y;
}')
#> myseq(max(0,1), min(13,17))
#[1] 1 2 3 4 5 6 7 8 9 10 11 12 13
This code generates a function myseq which takes two arguments: The first and the last number in an integer series. It is similar to R's seq function called with two integer arguments seq(first, last).
A documentation on the C++11 function std::iota is given here.
seq_along takes in a vector, what you want to use is seq combined with min and max, both take vectors. seq returns an IntegerVector. Here is an example.
#include <Rcpp.h>
using namespace Rcpp;
// [[Rcpp::export]]
IntegerVector test(IntegerVector a, IntegerVector b) {
IntegerVector vec = seq(max(a), min(b));
return vec;
}
In R you use
> test(c(0,1), c(2,12))
[1] 1 2
I am trying to convert RcppArmadillo vector (e.g. arma::colvec) to a Rcpp vector (NumericVector). I know I can first convert arma::colvec to SEXP and then convert SEXP to NumericVector (e.g. as<NumericVector>(wrap(temp)), assuming temp is an arma::colvec object). But what is a good way to do that?
I want to do that simply because I am unsure if it is okay to pass arma::colvec object as a parameter to an Rcpp::Function object.
I was trying to Evaluate a Rcpp::Function with argument arma::vec, it seems that it takes the argument in four forms without compilation errors. That is, if f is a Rcpp::Function and a is a arma::vec, then
f(a)
f(wrap(a))
f(as<NumericVector>(wrap(a)))
f(NumericVector(a.begin(),a.end()))
produce no compilation and runtime errors, at least apparently.
For this reason, I have conducted a little test for the four versions of arguments. Since I suspect that somethings will go wrong in garbage collection, I test them again gctorture.
gctorture(on=FALSE)
Rcpp::sourceCpp(code = '
#include <RcppArmadillo.h>
// [[Rcpp::depends(RcppArmadillo)]]
using namespace Rcpp;
// [[Rcpp::export]]
double foo1(arma::vec a, arma::vec b, Function f){
double sum = 0.0;
for(int i=0;i<100;i++){
sum += as<double>(f(a, b));
}
return sum;
}
// [[Rcpp::export]]
double foo2(arma::vec a, arma::vec b, Function f){
double sum = 0.0;
for(int i=0;i<100;i++){
sum += as<double>(f(wrap(a),wrap(b)));
}
return sum;
}
// [[Rcpp::export]]
double foo3(arma::vec a, arma::vec b, Function f){
double sum = 0.0;
for(int i=0;i<100;i++){
sum += as<double>(f(as<NumericVector>(wrap(a)),as<NumericVector>(wrap(b))));
}
return sum;
}
// [[Rcpp::export]]
double foo4(arma::vec a, arma::vec b, Function f){
double sum = 0.0;
for(int i=0;i<100;i++){
sum += as<double>(f(NumericVector(a.begin(),a.end()),NumericVector(b.begin(),b.end())));
}
return sum;
}
')
# note that when gctorture is on, the program will be very slow as it
# tries to perfrom GC for every allocation.
# gctorture(on=TRUE)
f = function(x,y) {
mean(x) + mean(y)
}
# all three functions should return 700
foo1(c(1,2,3), c(4,5,6), f) # error
foo2(c(1,2,3), c(4,5,6), f) # wrong answer (occasionally)!
foo3(c(1,2,3), c(4,5,6), f) # correct answer
foo4(c(1,2,3), c(4,5,6), f) # correct answer
As a result, the first method produces an error, the second method produces a wrong answer and only the third and the fourth method return the correct answer.
> # they should return 700
> foo1(c(1,2,3), c(4,5,6), f) # error
Error: invalid multibyte string at '<80><a1><e2>'
> foo2(c(1,2,3), c(4,5,6), f) # wrong answer (occasionally)!
[1] 712
> foo3(c(1,2,3), c(4,5,6), f) # correct answer
[1] 700
> foo4(c(1,2,3), c(4,5,6), f) # correct answer
[1] 700
Note that, if gctorture is set FALSE, then all functions will return a correct result.
> foo1(c(1,2,3), c(4,5,6), f) # error
[1] 700
> foo2(c(1,2,3), c(4,5,6), f) # wrong answer (occasionally)!
[1] 700
> foo3(c(1,2,3), c(4,5,6), f) # correct answer
[1] 700
> foo4(c(1,2,3), c(4,5,6), f) # correct answer
[1] 700
It means that method 1 and method 2 are subjected to break when garbage is collected during runtime and we don't know when it happens. Thus, it is dangerous to not wrap the parameter properly.
Edit: as of 2017-12-05, all four conversions produce the correct result.
f(a)
f(wrap(a))
f(as<NumericVector>(wrap(a)))
f(NumericVector(a.begin(),a.end()))
and this is the benchmark
> microbenchmark(foo1(c(1,2,3), c(4,5,6), f), foo2(c(1,2,3), c(4,5,6), f), foo
3(c(1,2,3), c(4,5,6), f), foo4(c(1,2,3), c(4,5,6), f))
Unit: milliseconds
expr min lq mean median uq
foo1(c(1, 2, 3), c(4, 5, 6), f) 2.575459 2.694297 2.905398 2.734009 2.921552
foo2(c(1, 2, 3), c(4, 5, 6), f) 2.574565 2.677380 2.880511 2.731615 2.847573
foo3(c(1, 2, 3), c(4, 5, 6), f) 2.582574 2.701779 2.862598 2.753256 2.875745
foo4(c(1, 2, 3), c(4, 5, 6), f) 2.378309 2.469361 2.675188 2.538140 2.695720
max neval
4.186352 100
5.336418 100
4.611379 100
3.734019 100
And f(NumericVector(a.begin(),a.end())) is marginally faster than other methods.
This should works with arma::vec, arma::rowvec and arma::colvec:
template <typename T>
Rcpp::NumericVector arma2vec(const T& x) {
return Rcpp::NumericVector(x.begin(), x.end());
}
I had the same question. I used wrap to do the conversion at the core of several layers of for loops and it was very slow. I think the wrap function is to blame for dragging the speed down so I wish to know if there is an elegant way to do this.
As for Raymond's question, you might want to try including the namespace like: Rcpp::as<Rcpp::NumericVector>(wrap(A)) instead or include a line using namespace Rcpp; at the beginning of your code.