Comparison of binary matrix algorithms (minus the Rcpparmadillo versions).

binmat_comparison.r

library(inline); library(compiler); library(rbenchmark)

n <- 500
k <- 100

scott <- function(N, K) {
	mm <- matrix(0, N, K)
	apply(mm, c(1, 2), function(x) sample(c(0, 1), 1))
}
scottComp <- cmpfun(scott)

ted <- function(N, K) {
	matrix(rbinom(N * K, 1, 0.5), ncol = K, nrow = N)
}

david <- function(m, n) {
	matrix(sample(0:1, m * n, replace = TRUE), m, n)
}

luis <- function(m, n) {
	round(matrix(runif(m * n), m, n))
}

josh <- function(m, n) {
	x <- sample.int(2, m*n, TRUE)-1L
	dim(x) <- c(m,n)
	x
}

sugar <- cxxfunction(signature(ns="integer", ks="integer"), plugin = "Rcpp", body='
   int n = Rcpp::as<int>(ns);
   int k = Rcpp::as<int>(ks);
   Rcpp::RNGScope tmp;
   Rcpp::NumericVector draws = Rcpp::runif(n*k);
   return Rcpp::NumericMatrix(n, k, draws.begin());
')

sugarFloor <- cxxfunction(signature(ns="integer", ks="integer"), plugin = "Rcpp", body='
   int n = Rcpp::as<int>(ns);
   int k = Rcpp::as<int>(ks);
   Rcpp::RNGScope tmp;
   Rcpp::NumericVector draws = Rcpp::floor(Rcpp::runif(n*k)+0.5);
   return Rcpp::NumericMatrix(n, k, draws.begin());
')

res <- benchmark(scott(n, k), scottComp(n,k),
		ted(n, k), david(n, k), luis(n, k), josh(n, k),
		sugar(n,k), sugarFloor(n, k),
		order="relative", replications=100)

> print(res[,1:4])
              test replications elapsed relative
7      sugar(n, k)          100   0.113    1.000
6       josh(n, k)          100   0.124    1.097
8 sugarFloor(n, k)          100   0.147    1.301
4      david(n, k)          100   0.190    1.681
3        ted(n, k)          100   0.375    3.319
5       luis(n, k)          100   0.462    4.088
1      scott(n, k)          100  54.378  481.221
2  scottComp(n, k)          100  56.330  498.496