piBySimulation.r

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#!/usr/bin/env r
 
library(Rcpp)
library(rbenchmark)
 
piR <- function(N) {
    x <- runif(N)
    y <- runif(N)
    d <- sqrt(x^2 + y^2)
    return(4 * sum(d < 1.0) / N)
}
 
sourceCpp("piSugar.cpp")
 
N <- 1e6
 
set.seed(42)
resR <- piR(N)
 
set.seed(42)
resCpp <- piSugar(N)
 
## important: check results are identical with RNG seeded
stopifnot(identical(resR, resCpp))
 
res <- benchmark(piR(N), piSugar(N), order="relative")
 
print(res[,1:4])