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PORcpp function to be SLOWER than same R function
 

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  1. PORcpp function to be SLOWER than same R function
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    <p>I have been coding a R function to compute an integral with respect to certain distributions, see code below.</p> <pre><code>EVofPsi = function(psi, probabilityMeasure, eps=0.01, ...){ distFun = function(u){ probabilityMeasure(u, ...) } xx = yy = seq(0,1,length=1/eps+1) summand=0 for(i in 1:(length(xx)-1)){ for(j in 1:(length(yy)-1)){ signPlus = distFun(c(xx[i+1],yy[j+1]))+distFun(c(xx[i],yy[j])) signMinus = distFun(c(xx[i+1],yy[j]))+distFun(c(xx[i],yy[j+1])) summand = c(summand, psi(c(xx[i],yy[j]))*(signPlus-signMinus)) } } sum(summand) } </code></pre> <p>It works fine, but it is pretty slow. It is common to hear that re-programming the function in a compiled language such as C++ would speed it up, especially because the R code above involves a double loop. So did I, using Rcpp:</p> <pre><code>#include &lt;Rcpp.h&gt; using namespace Rcpp; // [[Rcpp::export]] double EVofPsiCPP(Function distFun, Function psi, int n, double eps) { NumericVector xx(n+1); NumericVector yy(n+1); xx[0] = 0; yy[0] = 0; // discretize [0,1]^2 for(int i = 1; i &lt; n+1; i++) { xx[i] = xx[i-1] + eps; yy[i] = yy[i-1] + eps; } Function psiCPP(psi); Function distFunCPP(distFun); double signPlus; double signMinus; double summand = 0; NumericVector topRight(2); NumericVector bottomLeft(2); NumericVector bottomRight(2); NumericVector topLeft(2); // compute the integral for(int i=0; i&lt;n; i++){ //printf("i:%d \n",i); for(int j=0; j&lt;n; j++){ //printf("j:%d \n",j); topRight[0] = xx[i+1]; topRight[1] = yy[j+1]; bottomLeft[0] = xx[i]; bottomLeft[1] = yy[j]; bottomRight[0] = xx[i+1]; bottomRight[1] = yy[j]; topLeft[0] = xx[i]; topLeft[1] = yy[j+1]; signPlus = NumericVector(distFunCPP(topRight))[0] + NumericVector(distFunCPP(bottomLeft))[0]; signMinus = NumericVector(distFunCPP(bottomRight))[0] + NumericVector(distFunCPP(topLeft))[0]; summand = summand + NumericVector(psiCPP(bottomLeft))[0]*(signPlus-signMinus); //printf("summand:%f \n",summand); } } return summand; } </code></pre> <p>I'm pretty happy since this C++ function works fine. However, when I tested both functions, the C++ one ran SLOWER:</p> <pre><code>sourceCpp("EVofPsiCPP.cpp") pFGM = function(u,theta){ u[1]*u[2] + theta*u[1]*u[2]*(1-u[1])*(1-u[2]) } psi = function(u){ u[1]*u[2] } print(system.time( for(i in 1:10){ test = EVofPsi(psi, pFGM, 1/100, 0.2) } )) test print(system.time( for(i in 1:10){ test = EVofPsiCPP(psi, function(u){pFGM(u,0.2)}, 100, 1/100) } )) </code></pre> <p>So, is there some kind expert around willing to explain me this? Did I code like a monkey and is there a way to speed up that function? Moreover, I would have a second question. Indeed, I could have replaced the output type double by SEXP, and the argument types Function by SEXP as well, it doesn't seem to change anything. So what is the difference?</p> <p>Thank you very much in advance, Gildas </p>
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    1. USuser2635870
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    1. COAlthough there is no code for `NumericVector`, I would guess that creating so many temporaries of this class might be the bottleneck.
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    2. COPassing R functions to C++ functions is slow. If you want things to go fast, you need to re-define those R functions in C++ / Rcpp code.
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      1. USKevin Ushey
 

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